IEEE Networking 2016 Title and Abstract

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2016
TOPICS
Resource Allocation for a Massive MIMO Relay Aided Secure Communication
Abstract - In this paper, we address the problem of joint power and time allocation for secure
communications in a decode-and-forward massive multiple-input multiple-output (M-MIMO)
relaying system in the presence of a passive eavesdropper. We apply the M-MIMO relaying
technique to enhance the secrecy performance under very practical and adverse conditions, i.e.,
no availability of instantaneous eavesdropper channel state information (CSI) and only imperfect
instantaneous legitimate CSI. We first provide a performance analysis of secrecy outage
capacity, which reveals the minimum required number of relay antennas for achieving a positive
secrecy outage capacity. Then, we propose an optimization framework to jointly optimize source
transmit power, relay transmit power, and transmission time in each hop, with the goal of
maximizing the secrecy outage capacity. Although the secrecy outage capacity is not a concave
function with respect to the optimization variables, we show that it can be maximized by first
maximizing over some of the variables, and then maximizing over the rest. To this end, we first
derive a closed-form solution of optimal relay transmit power, afterward obtain that of optimal
source transmit power, and then derive the optimal ratio of the first-hop duration to a complete
transmission time. Moreover, several important system design insights are provided through
asymptotic performance analysis. Finally, simulation results validate the effectiveness of the
proposed joint resource allocation scheme.
IEEE Transactions on Information Forensics and Security (Aug. 2016)
Enabling data-centric distribution technology for partitioned embedded systems
Abstract - Modern complex embedded systems are evolving into mixed-criticality systems in
order to satisfy a wide set of non-functional requirements such as security, cost, weight, timing
or power consumption. Partitioning is an enabling technology for this purpose, as it provides an
environment with strong temporal and spatial isolation which allows the integration of
applications with different requirements into a common hardware platform. At the same time,
embedded systems are increasingly networked (e.g., cyber-physical systems) and they even
might require global connectivity in open environments so enhanced communication

mechanisms are needed to develop distributed partitioned systems. To this end, this work
proposes an architecture to enable the use of data-centric real-time distribution middleware in
partitioned embedded systems based on a hypervisor. This architecture relies on distribution
middleware and a set of virtual devices to provide mixed-criticality partitions with a
homogeneous and interoperable communication subsystem. The results obtained show that this
approach provides low overhead and a reasonable trade-off between temporal isolation and
performance
IEEE Transactions on Parallel and Distributed Systems (February 2016)
Covert Communication Over Noisy Channels: A Resolvability Perspective
Abstract - We consider the situation in which a transmitter attempts to communicate reliably
over a discrete memoryless channel, while simultaneously ensuring covertness (low probability
of detection) with respect to a warden, who observes the signals through another discrete
memoryless channel. We develop a coding scheme based on the principle of channel
resolvability, which generalizes and extends prior work in several directions. First, it shows that
irrespective of the quality of the channels, it is possible to communicate on the order of √n
reliable and covert bits over n channel uses if the transmitter and the receiver share on the order
of √n key bits. This improves upon earlier results requiring on the order of √n log n key bits.
Second, it proves that if the receiver's channel is better than the warden's channel in a sense that
we make precise, it is possible to communicate on the order of √n reliable and covert bits over n
channel uses without a secret key. This generalizes earlier results established for binary
symmetric channels. We also identify the fundamental limits of covert and secret
communications in terms of the optimal asymptotic scaling of the message size and key size, and
we extend the analysis to Gaussian channels. The main technical problem that we address is how
to develop concentration inequalities for low-weight sequences. The crux of our approach is to
define suitably modified typical sets that are amenable to concentration inequalities.
IEEE Transactions on Information Theory (May 2016)
Agent-Based Distributed Security Constrained Optimal Power Flow
Abstract - The need for the coordination of distributed energy resources in the future electric
power system provides motivation to move from the current highly centralized control of

resources towards a more distributed control structure. This paper presents an agent-based fully
distributed DC Security Constrained Optimal Power Flow (DC-SCOPF) approach. The
algorithm is based on a multi-agent system, in which geographically distributed network entities
are designated as agents with local sensing, communication, and computation abilities as
envisioned for a smart grid. This distributed approach is based on solving the first order
optimality conditions associated with DC-SCOPF formulation through an iterative process. At
each iteration, each agent updates a few local variables through simple computations, and
exchanges information with its neighboring agents. In particular, the updates for each agent
incorporate local information such as the Lagrange multipliers, as well as enforcing the
supply/demand balance through a local innovation term. Also, the performance is evaluated
using the IEEE test systems with 14 and 57 buses and a 944-bus system consisting of 8 IEEE
118-bus systems. Finally, analytical arguments concerning the convergence of the proposed
method to the optimal solution of the DC-SCOPF are provided.
IEEE Transactions on Smart Grid (June 2016)
Visual Analysis of Cloud Computing Performance Using Behavioral Lines
Abstract - Cloud computing is an essential technology to Big Data analytics and services. A
cloud computing system is often comprised of a large number of parallel computing and storage
devices. Monitoring the usage and performance of such a system is important for efficient
operations, maintenance, and security. Tracing every application on a large cloud system is
untenable due to scale and privacy issues. But profile data can be collected relatively efficiently
by regularly sampling the state of the system, including properties such as CPU load, memory
usage, network usage, and others, creating a set of multivariate time series for each system.
Adequate tools for studying such large-scale, multidimensional data are lacking. In this paper,
we present a visual based analysis approach to understanding and analyzing the performance and
behavior of cloud computing systems. Our design is based on similarity measures and a layout
method to portray the behavior of each compute node over time. When visualizing a large
number of behavioral lines together, distinct patterns often appear suggesting particular types of
performance bottleneck. The resulting system provides multiple linked views, which allow the
user to interactively explore the data by examining the data or a selected subset at different levels

of detail. Our case studies, which use datasets collected from two different cloud systems, show
that this visual based approach is effective in identifying trends and anomalies of the systems.
IEEE Transactions on Visualization and Computer Graphics (June 2016)
Automated Review of Distance Relay Settings Adequacy After the Network Topology
Changes
Abstract - A challenge raised in today’s power system is assessing the system protection security
and dependability after the topology has been changed due to relay operation upon occurrence of
cascading faults or intentional operator switching action. This paper proposes an automated
setting calculation module which could be used to review the adequacy of the distance relay
settings following network topology changes. The calculation procedure is broken down into
blocks which could be processed in parallel in order to improve the computation speed. A new
concept called distance-of-impact (DoI) is proposed to reduce the computational burden by
conducting the calculations on a limited portion of the network affected by the topology change.
The module performance is tested on synthetic IEEE 118- bus and real-life Alberta transmission
operator systems. A sensitivity analysis in the form of N-2 contingency impact on the network
relay settings coordination is conducted on the test systems.
IEEE Transactions on Power Delivery (February 2016)
Power System Reliability Assessment Incorporating Cyber Attacks Against Wind Farm
Energy Management Systems
Abstract - By exploiting the vulnerabilities in cyber components, an attacker could intrude in the
wind farm supervisory control and data acquisition (SCADA) system and energy management
system (EMS), and maliciously trip one or multiple wind turbines. The reliability of the overall
power system could thus be impacted by the performance of wind farms. In this paper, cyber
attack scenarios concerning cyber components or networks are considered in the integrated wind
farm SCADA/EMS system architecture. Two Bayesian attack graph models are adopted to
represent the procedures of successful cyber attacks, and a mean time-to-compromise model is
used by considering different attack levels and various vulnerabilities. Frequencies of successful

cyber attacks on the wind farm SCADA/EMS system are estimated. A procedure for evaluating
the power system reliability is proposed by considering wind turbine trips caused by various
cyber attacks. Simulations are conducted based on a typical IEEE reliability test system.
Simulation results indicate that the overall system reliability decreases when the frequency of
successful attacks on the wind farm SCADA/EMS system and skill levels of attackers increase.
IEEE Transactions on Smart Grid (February 2016)
Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under
Multiple Keys
Abstract - Uploading data streams to a resource-rich cloud server for inner product evaluation, an
essential building block in many popular stream applications (e.g., statistical monitoring), is
appealing to many companies and individuals. On the other hand, verifying the result of the
remote computation plays a crucial role in addressing the issue of trust. Since the outsourced data
collection likely comes from multiple data sources, it is desired for the system to be able to
pinpoint the originator of errors by allotting each data source a unique secret key, which requires
the inner product verification to be performed under any two parties’ different keys. However,
the present solutions either depend on a single key assumption or powerful yet
practicallyinefficient fully homomorphic cryptosystems. In this paper, we focus on the more
challenging multi-key scenario where data streams are uploaded by multiple data sources with
distinct keys. We first present a novel homomorphic verifiable tag technique to publicly verify
the outsourced inner product computation on the dynamic data streams, and then extend it to
support the verification of matrix product computation. We prove the security of our scheme in
the random oracle model. Moreover, the experimental result also shows the practicability of our
design.
IEEE Transactions on Services Computing (February 2016)
A Novel Graph-based Descriptor for the Detection of Billing-related Anomalies in Cellular
Mobile Networks
Abstract - Mobile devices are evolving and becoming increasingly popular over the last few
years. This growth, however, has exposed mobile devices to a large number of security threats.

Malware installed in smartphones can be used for a variety of malicious purposes, including
stealing personal data, sending spam SMSs, and launching Denial of Service (DoS) attacks
against core network components. Authentication and accesscontrol- based techniques,
employed by network operators fail to provide integral protection against malware threats. In
order to solve this issue, the activity of each mobile device in the network must be taken into
account, and combined with the activities of all the other devices. The communication activity in
the mobile network has a source, a destination, and possibly communication weights (e.g. the
number of calls between two mobile devices). This relational nature of the communication
activity is naturally represented with graphs. This indicates that graphs can be utilized in order to
provide better representations of the entire network activity, and lead to better detection results
when compared to methods that consider the activity of each mobile device individually.
Towards this end, this paper proposes a novel graph-based descriptor for the detection of
anomalies in mobile networks, using billing-related information. The graph-based descriptor
represents the total activity in the network. Smaller graphs are afterwards extracted from the
graph-based descriptor, each one representing the activity of one mobile device (e.g. Calls or
SMSs), while multiple features are calculated for each such graph. These features are
subsequently used for the supervised classification on network events, and the identification of
anomalous mobile devices. Experimental results and comparison of the proposed anomaly
detection method to the existing work, show that the graph-based descriptor has superior
performance in a variety of scenarios.
IEEE Transactions on Mobile Computing (January 2016)
Near-Optimal Modulo-and-Forward Scheme for the Untrusted Relay Channel
Abstract - This paper studies an untrusted relay channel, in which the destination sends artificial
noise simultaneously with the source sending a message to the relay, in order to protect the
source's confidential message. The traditional amplify-and-forward (AF) scheme shows poor
performance in this situation because of the interference power dilemma. Providing better
security by using stronger artificial noise will consume more power of the relay, impairing the
confidential message's transmission. To solve this problem, this paper proposes a modulo-and-
forward (MF) operation at the relay with nested lattice encoding at the source. For the proposed

MF scheme with full channel state information at the transmitter (CSIT), theoretical analysis
shows that the MF scheme approaches the secrecy capacity within 1/2 bit for all channel
realizations, and, hence, achieves full generalized security degrees of freedom (G-SDoF). In
contrast, the AF scheme can only achieve a small fraction of the G-SDoF. For the MF scheme
without CSIT, the total outage event, defined as either connection outage or secrecy outage, is
introduced. Based on this total outage definition, analysis shows that the proposed MF scheme
achieves the full generalized secure diversity gain (G-SDG) of order one. On the other hand, the
AF scheme can achieve a G-SDG of only 1/2 at most.
Distributed Sequential Location Estimation of a Gas Source via Convex Combination in
WSNs
Abstract - Localization of the hazardous gas source plays an important role in the protection of
public security, since it can save a lot of time for subsequent rescue works. For gas source
localization (GSL), a large number of gas sensor nodes can be rapidly deployed to construct a
wireless sensor network (WSN) and cover the whole concerned area. Although least-squares
(LS) methods can solve the problem of GSL in WSNs regardless of the distribution of
measurement noises, centralized LS methods are not power efficient and robust since they
require the gathering and processing of large-scale measurements on a central node. In this
paper, we propose a novel distributed method for GSL in WSNs, which is performed on a
sequence of sensor nodes successively. Each sensor node in the sequence conducts an individual
estimation and a convex combination. The individual estimation is inspired by the LS
formulation of the problem of GSL in WSNs. The proposed method is fully distributed and
computationally efficient, and it does not rely on the absolute location of the sensor nodes.
Extensive simulation results and a set of experimental results demonstrate that the success rate
and localization accuracy of the proposed method are generally higher than those of the trust-
region-reflective method.
IEEE Transactions on Instrumentation and Measurement (June 2016)
Defining the Industrial Demilitarized Zone and Its Benefits for Mining Applications

Abstract - There are many organizations and standard bodies that recommend segmenting the
enterprise zone from the industrial zone by utilizing an industrial demilitarized zone (IDMZ).
This paper will discuss the basic principles and purpose behind an IDMZ. Additionally, this
paper will discuss various strategies and design considerations to help users understand their
application requirements for the development and deployment of an IDMZ.
IEEE Transactions on Industry Applications (May-June 2016)
Physical Layer Security with RF Energy Harvesting in AF Multi-Antenna Relaying
Networks
Abstract - In this paper we analyze the secrecy capacity of a halfduplex energy harvesting (EH)-
based multi-antenna amplify-andforward (AF) relay network in the presence of a passive
eavesdropper. During the first phase, while the source is in transmission mode, the legitimate
destination transmits an auxiliary artificial noise (AN) signal which has here two distinct
purposes, a) to transfer power to the relay b) to improve system security. Since the AN is known
at the legitimate destination, it is easily canceled at the intended destination which is not the case
at the eavesdropper. In this respect, we derive new exact analytical expressions for the ergodic
secrecy capacity for various well-known EH relaying protocols, namely, time switching relaying
(TSR), power splitting relaying (PSR) and ideal relaying receiver (IRR). Monte Carlo
simulations are also provided throughout our investigations to validate the analysis. The impacts
of some important system parameters such as EH time, power splitting ratio, relay location, AN
power, EH efficiency and the number of relay antennas, on the system performance are
investigated. The results reveal that the PSR protocol generally outperforms the TSR approach in
terms of the secrecy capacity.
IEEE Transactions on Communications (May 2016)
Resolving Multi-Party Privacy Conflicts in Social Media
Abstract - Items shared through Social Media may affect more than one user's privacy—e.g.,
photos that depict multiple users, comments that mention multiple users, events in which
multiple users are invited, etc. The lack of multi-party privacy management support in current
mainstream Social Media infrastructures makes users unable to appropriately control to whom
these items are actually shared or not. Computational mechanisms that are able to merge the

privacy preferences of multiple users into a single policy for an item can help solve this problem.
However, merging multiple users’ privacy preferences is not an easy task, because privacy
preferences may conflict, so methods to resolve conflicts are needed. Moreover, these methods
need to consider how users’ would actually reach an agreement about a solution to the conflict in
order to propose solutions that can be acceptable by all of the users affected by the item to be
shared. Current approaches are either too demanding or only consider fixed ways of aggregating
privacy preferences. In this paper, we propose the first computational mechanism to resolve
conflicts for multi-party privacy management in Social Media that is able to adapt to different
situations by modelling the concessions that users make to reach a solution to the conflicts. We
also present results of a user study in which our proposed mechanism outperformed other
existing approaches in terms of how many times each approach matched users’ behaviour.
IEEE Transactions on Knowledge and Data Engineering (July 2016)
Coordinated Operation of Natural Gas and Electricity networks with Microgrid
Aggregators
Abstract - The interdependence between the natural gas (NG) and electricity networks as two
primary energy carriers has attracted significant attention in smart grids. In this paper, a multi-
objective framework is proposed for the coordinated operation of NG and electricity networks,
addressing the economic, dynamic security of electricity network, as well as the security of the
NG network. The proposed electricity network includes thermal generation facilities such as NG-
fired generation units as well as the microgrid aggregators (MGAs) as price responsive demands.
The ε-constraint method is employed to solve the proposed multi-objective problem and the
index of critical clearing time (CCT) is employed to assess the dynamic stability of the electricity
network. The effectiveness of the proposed framework is addressed in a case study integrating
the Belgian gas network and modified IEEE 24-bus test system. The proposed coordinated
operation of electricity and NG networks is benchmarked against the independent operation of
individual networks.
IEEE Transactions on Smart Grid (March 2016)
An integrated cloud-based smart home management system with community hierarchy

Abstract - This paper presents a smart home management system in which a community broker
role is used for integrating community services, thereby reducing the workload of community
management staff, providing electronic information services, and deepening the community's
integration with the surrounding environment. At the home end, a home intranet was created by
integrating a fixed touch panel with a home controller system and various sensors and devices to
deliver, for example, energy, scenario information, and security functions. The community end
comprises a community server and community personal computers, and connects to devices
(e.g., video cameras and building automation devices) in other community systems and to the
home networks. Furthermore, to achieve multiple inhome displays, standard interface devices
can be employed to separate the logic and user interfaces. This study also determined that the
message queuing telemetry transport protocol can provide optimal home control services in
smart home systems, whereas hypertext transfer protocol is optimal for delivering location-based
information integration services.
IEEE Transactions on Consumer Electronics (April 2016)
Zero-one laws for connectivity in inhomogeneous random key graphs
Abstract - We introduce a new random key predistribution scheme for securing heterogeneous
wireless sensor networks. Each of the n sensors in the network is classified into r classes
according to some probability distribution = f1; : : : ; rg. Before deployment, a class-i sensor is
assigned Ki cryptographic keys that are selected uniformly at random from a common pool of P
keys. Once deployed, a pair of sensors can communicate securely if and only if they have a key
in common. We model the communication topology of this network by a newly defined
inhomogeneous random key graph. We establish scaling conditions on the parameters P and fK1;
: : : ;Krg so that this graph i) has no isolated nodes; and ii) is connected, both with high
probability. The results are given in the form of zero-one laws with the number of sensors n
growing unboundedly large; critical scalings are identified and shown to coincide for both graph
properties. Our results are shown to complement and improve those given by Godehardt et al.
and Zhao et al. for the same model, therein referred to as the general random intersection graph.
IEEE Transactions on Information Theory (June 2016)

Secrecy Outage on Transmit Antenna Selection/Maximal Ratio Combining in MIMO
Cognitive Radio Networks
Abstract - This paper investigates the secrecy outage performance of transmit antenna selection
(TAS)/maximal ratio combining (MRC) in multiple input multiple output (MIMO) cognitive
radio networks (CRNs) over Rayleigh fading channels. In the considered system, a secondary
user (SU-TX) equipped with NA (NA 1) antennas uses TAS to transmit confidential messages to
another secondary user (SU-RX), which is equipped with NB (NB 1) antennas and adopts MRC
scheme to process multiple received signals. Meanwhile, an eavesdropper equipped with NE (NE
1) antennas also adopts MRC scheme to overhear the transmitted information between SU-TX
and SU-RX. SU-TX adopts the underlay strategy to guarantee the quality of service of the
primary user without spectrum sensing. In this paper, we derive the exact and asymptotic closed-
form expressions for the secrecy outage probability. Simulations are conducted to validate the
accuracy of the analysis.
IEEE Transactions on Vehicular Technology (February 2016)
A Practical Security Architecture for In-Vehicle CAN-FD
Abstract - The controller area network with flexible data rate (CAN-FD) is attracting attention as
the next generation of in-vehicle network technology. However, security issues have not been
completely taken into account when designing CAN-FD, although every bit of information
transmitted could be critical to driver safety. If we fail to solve the security vulnerabilities of
CAN-FD, we cannot expect Vehicle-Information and Communications Technology (Vehicle-
ICT) convergence to continue to develop. Fortunately, secure in-vehicle CAN-FD
communication environments can be constructed using the larger data payload of CAN-FD. In
this paper, we propose a security architecture for in-vehicle CAN-FD as a countermeasure
(designed in accordance with CAN-FD specifications). We considered the characteristics of the
International Organization for Standardization (ISO) 26262 Automotive Safety Integrity Level
and the in-vehicle subnetwork to design a practical security architecture. We also evaluated the
feasibility of the proposed security architecture using three kinds of microcontroller unit and the
CANoe software. Our evaluation findings may be used as an indicator of the performance level
of electronic control units for manufacturing next-generation vehicles.

IEEE Transactions on Intelligent Transportation Systems (March 2016)
Anti-Eavesdropping Schemes for Interference Alignment (IA)-Based Wireless Networks
Abstract - In interference alignment (IA)-based networks, interferences are constrained into
certain subspaces at the unintended receivers, and the desired signal can be recovered free of
interference. Due to the superposition of signals from legitimate users at the eavesdropper, the
IA-based network seems to be more secure than conventional wireless networks. Nevertheless,
when adequate antennas are equipped, the legitimate information can still be eavesdropped. In
this paper, we analyze the performance of the external eavesdropper, and propose two anti-
eavesdropping schemes for IA-based networks. When the channel state information (CSI) of
eavesdropper is available, zero-forcing scheme can be utilized, in which the transmitted signals
are zero-forced at the eavesdropper through the precoding of transmitters in IA-based networks.
Furthermore, a more generalized artificial noise (AN) scheme is proposed for IA-based networks
without the knowledge of eavesdropper’s CSI. In this scheme, a singlestream AN is generated by
each user, which will disrupt the eavesdropping without introducing any additional interference
to the legitimate transmission of IA-based networks. In addition, the feasibility conditions,
transmission rate and eavesdropping rate are analyzed in detail, and an iterative algorithm to
achieve the scheme is also designed. Extensive simulation results are provided to verify our
analysis results and show the effectiveness of the proposed anti-eavesdropping schemes for IA-
based networks.
IEEE Transactions on Wireless Communications (May 2016)
Deploying Energy Router in an Energy Internet Based Electric Vehicles
Abstract - An energy internet is a system that enables energy sharing in a distribution system like
the Internet. It has been attracting a lot attention from both academia and industry. The main
purpose of this paper is to develop a model of EV (electric vehicle) energy network to transmit,
distribute and store energy by electric vehicles from renewable energy sources to places that
need the energy. We describe EV energy internet in detail, and then formulate an optimization
problem to place charging stations in an EV energy internet. We develop two solutions, one

using a greedy heuristic and the other based on diffusion. Simulation results using real-world
data show that the greedy heuristic requires less charging stations while the diffusion-based
algorithm incurs less energy transmission loss.
IEEE Transactions on Vehicular Technology (March 2016)
Dynamic Output Feedback Predictive Control of Takagi-Sugeno Model with Bounded
Disturbance
Abstract - This paper considers predictive control of a Takagi- Sugeno fuzzy model with
bounded disturbance, strictly satisfying the input and state constraints. The membership-
functionsdependent dynamic output feedback law, as in a previous work, is utilized. The novelty
lies in the following technical improvements. For the notion of quadratic boundedness (QB)
which specifies closed-loop stability and invariance properties, the full Lyapunov matrix is
utilized. The real-time ellipsoidal bound of true state is recursively optimized by invoking the
Sprocedure. Some relaxation scalars, being optimized by the normbounding technique, are
introduced for better handling the input and state constraints. The multi-step approach, where a
sequence of dynamic output feedback laws are optimized at each sampling instant, is given to
improve the single-step approach. Numerical examples are given to illustrate the effectiveness of
the proposed controllers.
IEEE Transactions on Fuzzy Systems (June 2016)
Cryptoleq: A Heterogeneous Abstract Machine for Encrypted and Unencrypted
Computation
Abstract - The rapid expansion and increased popularity of cloud computing comes with no
shortage of privacy concerns about outsourcing computation to semi-trusted parties. Leveraging
the power of encryption, in this paper we introduce Cryptoleq: an abstract machine based on the
concept of One Instruction Set Computer, capable of performing general-purpose computation
on encrypted programs. The program operands are protected using the Paillier partially
homomorphic cryptosystem, which supports addition on the encrypted domain. Full
homomorphism over addition and multiplication, which is necessary for enabling general-
purpose computation, is achieved by inventing a heuristically obfuscated software re-encryption
module written using Cryptoleq instructions and blended into the executing program. Cryptoleq

is heterogeneous, allowing mixing encrypted and unencrypted instruction operands in the same
program memory space. Programming with Cryptoleq is facilitated using an enhanced assembly
language that allows development of any advanced algorithm on encrypted datasets. In our
evaluation, we compare Cryptoleq’s performance against a popular fully homomorphic
encryption library, and demonstrate correctness using a typical Private Information Retrieval
problem.
IEEE Transactions on Information Forensics and Security (May 2016)
Secret Common Randomness From Routing Metadata in Ad Hoc Networks
Abstract - Establishing secret common randomness between two or multiple devices in a
network resides at the root of communication security. In its most frequent form of key
establishment, the problem is traditionally decomposed into a randomness generation stage
(randomness purity is subject to employing often costly true random number generators) and an
information-exchange agreement stage, which relies either on public-key infrastructure or on
symmetric encryption (key wrapping). In this paper, we propose a secret-common-randomness
establishment algorithm for ad hoc networks, which works by harvesting randomness directly
from the network routing metadata, thus achieving both pure randomness generation and
(implicitly) secret-key agreement. Our algorithm relies on the route discovery phase of an ad hoc
network employing the dynamic source routing protocol, is lightweight, and requires relatively
little communication overhead. The algorithm is evaluated for various network parameters in an
OPNET ad hoc network simulator. Our results show that, in just 10 min, thousands of secret
random bits can be generated network-wide, between different pairs in a network of 50 users.
Attraction Region Seeking For Power Grids
Abstract - Motivated by the growing interests in the smart grid technology and architecture, this
paper explores an attraction region for the asymptotical locked phase agreement and frequency
synchronization in power networks with a symmetrically connected interaction topology. By
placing attention on the complicated system dynamics and network structure, two cases
consisting of uniform and non-uniform ratios of the damping coefficient and the inertia strength
are discussed, respectively. The quantitative estimate on the attraction region is characterized

explicitly that relates the initial configurations and the system parameters. For the uniform case,
by resorting to the second-order Gronwall’s differential inequality and the phase and frequency
diameters, the uniform boundedness of fluctuations of phase and frequency is established, which
requires that the network diameter is smaller than or equal to two. For the non-uniform case, an
energy estimate method is applied to ensure the uniform boundedness of fluctuations of phase
and frequency, however, which does not require the network spectral information. The
convergence of phase and frequency to a certain equilibrium point is achieved by employing a
second-order gradient-like system with an analytic nonlinearity. The obtained results are helpful
to the insight into the stability study of large power grids since the model we considered can be
highly heterogeneous.
IEEE Transactions on Circuits and Systems II: Express Briefs (May 2016)
Hardware-based Malware Detection using Low level Architectural Features
Abstract - Security exploits and ensuant malware pose an increasing challenge to computing
systems as the variety and complexity of attacks continue to increase. In response, software-
based malware detection tools have grown in complexity, thus making it computationally
difficult to use them to protect systems in real-time. Therefore, software detectors are applied
selectively and at a low frequency, creating opportunities for malware to remain undetected. In
this paper, we propose Malware-Aware Processors (MAP) - processors augmented with a
hardware-based online malware detector to serve as the first line of defense to differentiate
malware from legitimate programs. The output of this detector helps the system prioritize how to
apply more expensive softwarebased solutions. The always-on nature of MAP detector helps
protect against intermittently operating malware. We explore the use of different features for
classification and study both logistic regression and neural networks. We show that the detectors
can achieve excellent performance, with little hardware overhead. We integrate the MAP
implementation with an open-source x86-compatible core, synthesizing the resulting design to
run on an FPGA.
IEEE Transactions on Computers (March 2016)
ActiveTrust: Secure and Trustable Routing in Wireless Sensor Networks

Abstract - Wireless sensor networks (WSNs) are increasingly being deployed in security-critical
applications. Because of their inherent resource-constrained characteristics, they are prone to
various security attacks, and a black hole attack is a type of attack that seriously affects data
collection. To conquer that challenge, an active detection-based security and trust routing scheme
named ActiveTrust is proposed for WSNs. The most important innovation of ActiveTrust is that
it avoids black holes through the active creation of a number of detection routes to quickly detect
and obtain nodal trust and thus improve the data route security. More importantly, the generation
and distribution of detection routes are given in the ActiveTrust scheme, which can fully use the
energy in non-hotspots to create as many detection routes as needed to achieve the desired
security and energy efficiency. Both comprehensive theoretical analysis and experimental results
indicate that the performance of the ActiveTrust scheme is better than that of previous studies.
ActiveTrust can significantly improve the data route success probability and ability against black
hole attacks and can optimize network lifetime.
Botnet Detection based on Anomaly and Community Detection
Abstract - We introduce a novel two-stage approach for the important cyber-security problem of
detecting the presence of a botnet and identifying the compromised nodes (the bots), ideally
before the botnet becomes active. The first stage detects anomalies by leveraging large
deviations of an empirical distribution. We propose two approaches to create the empirical
distribution: a flow-based approach estimating the histogram of quantized flows, and a
graphbased approach estimating the degree distribution of node interaction graphs,
encompassing both Erd˝os-R´enyi graphs and scale-free graphs. The second stage detects the
bots using ideas from social network community detection in a graph that captures correlations
of interactions among nodes over time. Community detection is done by maximizing a
modularity measure in this graph. The modularity maximization problem is non-convex. We
propose a convex relaxation, an effective randomization algorithm, and establish sharp bounds
on the suboptimality gap. We apply our method to real-world botnet traffic and compare its
performance with other methods.
IEEE Transactions on Control of Network Systems (February 2016)

Secrecy Capacity Analysis over $kappa-mu$ Fading Channels: Theory and Applications
Abstract - In this paper, we consider the transmission of confidential information over a -μ
fading channel in the presence of an eavesdropper who also experiences -μ fading. In particular,
we obtain novel analytical solutions for the probability of strictly positive secrecy capacity
(SPSC) and a lower bound of secure outage probability (SOPL) for independent and
nonidentically distributed (i.n.i.d.) channel coefficients without parameter constraints. We also
provide a closed-form expression for the probability of SPSC when the μ parameter is assumed
to take positive integer values. Monte-Carlo simulations are performed to verify the derived
results. The versatility of the -μ fading model, means that the results presented in this paper can
be used to determine the probability of SPSC and SOPL for a large number of other fading
scenarios such as Rayleigh, Rice (Nakagami-n), Nakagami-m, One-Sided Gaussian and mixtures
of these common fading models. Additionally, due to the duality of the analysis of secrecy
capacity and co-channel interference (CCI), the results presented here will also have immediate
applicability in the analysis of outage probability in wireless systems affected by CCI and
background noise (BN). To demonstrate the efficacy of the novel formulations proposed here,
we use the derived equations to provide a useful insight into the probability of SPSC and SOPL
for a range of emerging wireless applications such as cellular device-to-device, peer-to-peer,
vehicle-to-vehicle and body centric communications using data obtained from real channel
measurements.
IEEE Transactions on Communications (May 2016 )
Delay-Aware Optimization of Physical Layer Security in Multi-Hop Wireless Body Area
Networks
Abstract - Joint optimization of the physical layer security with end-to-end delay management is
studied in the uniquely constrained context of wireless body area networks. A gametheoretic
framework is proposed wherein body-worn sensor devices interact in the presence of wiretappers
and under fading channel conditions to find the most secure multi-hop path to the hub, while
adhering to the end-to-end delay requirements imposed by the application. We model the
problem as the search for a Nash network topology where no unilateral deviation in strategy by
any single sensor node improves the secrecy of its transmissions, and provide a distributed

algorithm guaranteed to converge to a Pareto-dominant Nash solution. The framework is
evaluated through numerical simulations in conditions approximating actual deployment of
wireless body area networks for moving and stationary scenarios. Results validate the merits of
the proposed framework to improve the security of transmissions compared to the star topology
and IEEE 802.15.6 two-hop topology extension with a best-channel algorithm, at the expense of
an admissible increase in the end-to-end delay.
Runtime Semantic Security Analysis to Detect and Mitigate Control-related Attacks in
Power Grids
In this paper, we analyze control-related attacks in SCADA (supervisory control and data
acquisition) systems for power grids. This class of attacks introduces a serious threat to power
systems, because attackers can directly change the system’s physical configuration using
malicious control commands crafted in a legitimate format. To detect such attacks, we propose a
semantic analysis framework that integrates network intrusion detection systems (IDSes) with a
power flow analysis capable of estimating the execution consequences of control commands. To
balance detection accuracy and latency, the parameters of the power flow analysis algorithm are
dynamically adapted according to real-time system dynamics. Our experiments on IEEE 24-bus,
30-bus, and 39-bus systems and a 2736-bus system demonstrate that (1) by opening 3
transmission lines, an attacker can put the tested system into an insecure state, and (2) the
semantic analysis can complete detection in 200 milliseconds for the large-scale 2736-bus
system with about 0.78% false positives and 0.01% false negatives, which allow for timely
responses to intrusions.
IEEE Transactions on Smart Grid (March 2016)
Compressive Sensing-Based Topology Identification for Smart Grids
Smart grid (SG) technology transforms the traditional power grid from a single-layer physical
system to a cyber-physical network that includes a second layer of information. Collecting,
transferring, and analyzing the huge amount of data that can be captured from different
parameters in the network, together with the uncertainty that is caused by the distributed power
generators, challenge the standard methods for security and monitoring in future SGs. Other

important issues are the cost and power efficiency of data collection and analysis, which are
highlighted in emergency situations such as blackouts. This paper presents an efficient dynamic
solution for online SG topology identification (TI) and monitoring by combining concepts from
compressive sensing (CS) and graph theory. In particular, the SG is modeled as a huge
interconnected graph, and then using a dc power-flow model under the probabilistic optimal
power flow (P-OPF), TI is mathematically reformulated as a sparse-recovery problem (SRP).
This problem and challenges therein are efficiently solved using modified sparse-recovery
algorithms. Network models are generated using the MATPOWER toolbox. Simulation results
show that the proposed method represents a promising alternative for real-time monitoring in
SGs.
IEEE Transactions on Industrial Informatics (April 2016)
Multiagent Based Reactive Power Sharing and Control Model for Islanded Microgrids
Abstract - In islanded microgrids (MGs), the reactive power cannot be shared proportionally
among distributed generators (DGs) with conventional droop control, due to the mismatch in
feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system
(MAS) based distributed control model for droop-controlled MGs is proposed. The proposed
control model consists of two layers, where the bottom layer is the electrical distribution MG,
while the top layer is a communication network composed of agents. Moreover, agents on the
communication network exchange the information acquired from DGs with neighbors, and
calculate set points for DGs they connect to, according to the control laws. Further, a theorem is
demonstrated, which yields a systematic method to derive the control laws from a given
communication network. Finally, three cases are carried out to test the performance of the
control model, in which the uncertainty of intermittent DGs, variations in load demands, as well
as impacts of time delays are considered. The simulation results demonstrate the eectiveness of
the control model in proportional reactive power sharing, and the plug and play capability of the
control model is also verified.
IEEE Transactions on Sustainable Energy (March 2016)
Integrated Software Fingerprinting via Neural-Network-Based Control Flow Obfuscation

Abstract - Dynamic software fingerprinting has been an important tool in fighting against
software theft and pirating by embedding unique fingerprints into software copies. However,
existing work uses methods from dynamic software watermarking as direct solutions in which
secret marks are inside rather independent code modules attached to the software. This results in
an intrinsic weakness against targeted collusive attacks since differences among software copies
correspond directly to the fingerprint-related components. In this paper, we suggest a novel mode
of dynamic fingerprinting called integrated fingerprinting, of which the goal is to ensure all
fingerprinted software copies possess identical behaviors at semantic level. We then provide the
first implementation of integrated fingerprinting called Neuroprint on top of a control flow
obfuscator that replaces program’s conditional structures with neural networks trained to
simulate their branching behaviors [1]. Leveraging the rich entropy in the outputs of these neural
networks, Neuroprint embeds software fingerprints such that a one-time construction of the
networks serves both purposes of obfuscation and fingerprinting. Evaluations show that due to
the incomprehensibility of neural networks, it is infeasible to de-obfuscate the software
transformed by Neuroprint or attack the fingerprint using even the latest program analysis
techniques. Revealing information regarding the hidden fingerprints via collusive attacks on
Neuroprint is difficult as well. Finally, Neuroprint also demonstrates negligible runtime
overhead.
IEEE Transactions on Information Forensics and Security (April 2016)
Overlay Automata and Algorithms for Fast and Scalable Regular Expression Matching
Abstract - Regular expression (RegEx) matching, the core operation of intrusion detection and
prevention systems, remains a fundamentally challenging problem. A desired RegEx matching
scheme should satisfy four requirements: deterministic finite state automata (DFA) speed,
nondeterministic finite state automata (NFA) size, automated construction, and scalable
construction. Despite lots of work on RegEx matching, no prior scheme satisfies all four of these
requirements. In this paper, we approach this holy grail by proposing OverlayCAM, a RegEx
matching scheme that satisfies all four requirements. The theoretical underpinning of our scheme
is overlay delayed input DFA, a new automata model proposed in this paper that captures both
state replication and transition replication, which are inherent in DFAs. Our RegEx matching

solution processes one input character per lookup like a DFA, requires only the space of an NFA,
is grounded in sound automata models, is easy to deploy in existing network devices, and comes
with scalable and automated construction algorithms.
IEEE/ACM Transactions on Networking (April 2016)
SEAP: Secure and efficient authentication protocol for NFC applications using
pseudonyms
Abstract - Authentication protocol plays an important role in the short-range wireless
communications for the Near Field Communication (NFC) technology. Due to the shared nature
of wireless communication networks, there are several kinds of security vulnerabilities. Recently,
a pseudonym-based NFC protocol (PBNFCP) has been proposed to withstand the security
pitfalls found in the existing conditional privacy preserving security protocol (CPPNFC).
However, this paper further analyzes PBNFCP and shows that it still fails to prevent the claimed
security properties, such as impersonation attacks against an adversary, who is a malicious
registered user having a valid pseudonym and corresponding private key. In order to overcome
these security drawbacks, this paper proposes a secure and efficient authentication protocol
(SEAP) for NFC applications using lifetime-based pseudonyms. The proposed SEAP is
simulated for the formal security verification using the widely-accepted AVISPA (Automated
Validation of Internet Security Protocols and Applications) tool. The simulation results show that
SEAP is secure. The rigorous security and performance analysis shows that the proposed SEAP
is secure and efficient as compared to the related existing authentication protocols for NFC
applications.
Hybrid Tree-rule Firewall for High Speed Data Transmission
Abstract - Traditional firewalls employ listed rules in both configuration and process phases to
regulate network traffic. However, configuring a firewall with listed rules may create rule
conflicts, and slows down the firewall. To overcome this problem, we have proposed a Tree-rule
firewall in our previous study. Although the Tree-rule firewall guarantees no conflicts within its
rule set and operates faster than traditional firewalls, keeping track of the state of network
connections using hashing functions incurs extra computational overhead. In order to reduce this

overhead, we propose a hybrid Tree-rule firewall in this paper. This hybrid scheme takes
advantages of both Tree-rule firewalls and traditional listed-rule firewalls. The GUIs of our Tree-
rule firewalls are utilized to provide a means for users to create conflict-free firewall rules, which
are organized in a tree structure and called 'tree rules'. These tree rules are later converted into
listed rules that share the merit of being conflict-free. Finally, in decision making, the listed rules
are used to verify against packet header information. The rules which have matched with most
packets are moved up to the top positions by the core firewall. The mechanism applied in this
hybrid scheme can significantly improve the functional speed of a firewall.
IEEE Transactions on Cloud Computing (April 2016)
Channel Frequency Response Based Secret Key Generation in Underwater Acoustic
Systems
Y. Huang is with the Department of Electrical and Computer Engineering, University of
Connecticut, Storrs, CT, 06269, USA.(email:yi.huang@engr.uconn.edu)
Self-Sustainable Community of Electricity Prosumers in the Emerging Distribution System
Abstract - In distribution systems, a multitude of prosumers interact among themselves in social
networks and with the electricity network through a variety of information and communication
technology tools. In this paper, we propose a new vision for the distribution system in which
prosumers are encouraged by different balancing premiums to balance their electricity in a local
community. Price-responsive generation and demand of an individual prosumer are affected by
his/her attitudes and inherent characteristics. Further, the individual attitudes on benefit and
comfort would evolve during social interactions. A load aggregator, on behalf of prosumers,
participate the community market run by a local electricity coordinator who takes responsibilities
for operational securities and uses nodal prices to guide prosumers' physical behaviors. A
regulator is assumed to design balancing premiums schemes. Multi-agent based simulation with
a four-layered representation is employed to study features of the community and the best
incentive strategies for the desired performance.
IEEE Transactions on Smart Grid (January 2016)
Driven Stability of Nonlinear Feedback Shift Registers with Inputs

Abstract - Driven stable nonlinear feedback shift registers (NFSRs) with inputs are not only able
to limit error propagations in convolutional decoders, but also helpful to analyze the period
properties of sequences generated by a cascade connection of NFSRs in stream ciphers. An
NFSR is driven stable if and only if the reachable set is a subset of the basin. Due to lack of
efficient algebraic tools, the driven stability of NFSRs with inputs has been much less studied.
This paper continues to address this research using a Boolean control network approach.
Viewing an NFSR with input as a Boolean control network, we first give its Boolean control
network representation, which is characterized with a state transition matrix. Some properties of
the state transition matrix are then provided. Based on these, explicit forms are given for the
reachable set and the set of basin. Two algorithms for obtaining both sets are provided as well.
Compared to the exhaustive search and the existing state operator method, the Boolean control
network approach requires lower computational complexity for those NFSRs with their stages
greater than 1.
IEEE Transactions on Communications (April 2016)
PIF: A Personalized Fine-Grained Spam Filtering Scheme With Privacy Preservation in
Mobile Social Networks
Abstract - Mobile social network (MSN) emerges as a promising social network paradigm that
enables mobile users' information sharing in the proximity and facilitates their cyber-physical-
social interactions. As the advertisements, rumors, and spams spread in MSNs, it is necessary to
filter spams before they arrive at the recipients to make the MSN energy efficient. To this end,
we propose a personalized fine-grained filtering scheme (PIF) with privacy preservation in
MSNs. Specifically, we first develop a social-assisted filter distribution scheme, where the filter
creators send filters to their social friends (i.e., filter holders). These filter holders store filters
and decide to block spams or relay the desired packets through coarse-grained and fine-grained
keyword filtering schemes. Meanwhile, the developed cryptographic filtering schemes protect
creator's private information (i.e., keyword) embedded in the filters from directly disclosing to
other users. In addition, we establish a Merkle Hash tree to store filters as leaf nodes where filter
creators can check if the distributed filters need to be updated by retrieving the value of root
node. It is demonstrated that the PIF can protect users' private keywords included in the filter

from disclosure to others and detect forged filters. We also conduct the trace-driven simulations
to show that the PIF can not only filter spams efficiently but also achieve high delivery ratio and
low latency with acceptable resource consumption.
IEEE Transactions on Computational Social Systems (February 2016|)
Fingerprint Liveness Detection Using Convolutional Neural Networks
Abstract - With the growing use of biometric authentication systems in the recent years, spoof
fingerprint detection has become increasingly important. In this paper, we use convolutional
neural networks (CNNs) for fingerprint liveness detection. Our system is evaluated on the data
sets used in the liveness detection competition of the years 2009, 2011, and 2013, which
comprises almost 50 000 real and fake fingerprints images. We compare four different models:
two CNNs pretrained on natural images and fine-tuned with the fingerprint images, CNN with
random weights, and a classical local binary pattern approach. We show that pretrained CNNs
can yield the state-of-the-art results with no need for architecture or hyperparameter selection.
Data set augmentation is used to increase the classifiers performance, not only for deep
architectures but also for shallow ones. We also report good accuracy on very small training sets
(400 samples) using these large pretrained networks. Our best model achieves an overall rate of
97.1% of correctly classified samples-a relative improvement of 16% in test error when
compared with the best previously published results. This model won the first prize in the
fingerprint liveness detection competition 2015 with an overall accuracy of 95.5%.
IEEE Transactions on Information Forensics and Security (June 2016)
Artificial-Noise-Aided Message Authentication Codes With Information-Theoretic Security
Abstract - In the past, two main approaches for the purpose of authentication, including
information-theoretic authentication codes and complexity-theoretic message authentication
codes (MACs), were almost independently developed. In this paper, we consider to construct
new MACs, which are both computationally secure and information-theoretically secure.
Essentially, we propose a new cryptographic primitive, namely, artificial-noise-aided MACs
(ANA-MACs), where artificial noise is used to interfere with the complexity-theoretic MACs
and quantization is further employed to facilitate packet-based transmission. With a channel
coding formulation of key recovery in the MACs, the generation of standard authentication tags

can be seen as an encoding process for the ensemble of codes, where the shared key between
Alice and Bob is considered as the input and the message is used to specify a code from the
ensemble of codes. Then, we show that artificial noise in ANA-MACs can be well employed to
resist the key recovery attack even if the opponent has an unlimited computing power. Finally, a
pragmatic approach for the analysis of ANA-MACs is provided, and we show how to balance the
three performance metrics, including the completeness error, the false acceptance probability,
and the conditional equivocation about the key. The analysis can be well applied to a class of
ANA-MACs, where MACs with Rijndael cipher are employed.
Simultaneously Generating Secret and Private Keys in a Cooperative Pairwise-
Independent Network
This paper studies the problem of simultaneously generating a secret key (SK) and a private key
(PK) between Alice and Bob, in a cooperative pairwise-independent network (PIN) with two
relays. In the PIN, the pairwise source observed by every pair of terminals is independent of
those sources observed by any other pairs. The SK needs to be protected from Eve, while the PK
needs to be protected not only from Eve but also from the two relays. Two cooperative SK-PK
generation algorithms are proposed: both of them first generate common randomness, based on
the well-established pairwise key generation technique and the application of the one-time pad;
but then, the two algorithms utilize the XOR operation and a specific random-binning-based SK-
PK codebook to generate the expected keys, respectively. The achievable SK-PK rate regions of
both the two proposed algorithms are analyzed. Of particular interest is the second algorithm
with random-bing based codebook, whose achievable key rate region is demonstrated to be
exactly the same as the derived outer bound, a crucial step for establishing the key capacity of
this PIN model. Finally, the two proposed SK-PK generation algorithms are extended to a
cooperative wireless network, where the correlated source observations are obtained from
estimating wireless channels during a training phase.
Group Secret Key Generation in Wireless Networks: Algorithms and Rate Optimization

This paper investigates group secret key generation problems for different types of wireless
networks, by exploiting physical layer characteristics of wireless channels. A new group key
generation strategy with low complexity is proposed, which combines the well-established point-
to-point pairwise key generation technique, the multisegment scheme, and the one-time pad. In
particular, this group key generation process is studied for three types of communication
networks: 1) the three-node network; 2) the multinode ring network; and 3) the multinode mesh
network. Three group key generation algorithms are developed for these communication
networks, respectively. The analysis shows that the first two algorithms yield optimal group key
rates, whereas the third algorithm achieves the optimal multiplexing gain. Next, for the first two
types of networks, we address the time allocation problem in the channel estimation step to
maximize the group key rates. This non-convex max-min time allocation problem is first
reformulated into a series of geometric programming, and then, a single-condensation-method-
based iterative algorithm is proposed. Numerical results are also provided to validate the
performance of the proposed key generation algorithms and the time allocation algorithm.
Cooperation via Spectrum Sharing for Physical Layer Security in Device-to-Device
Communications Underlaying Cellular Networks
Abstract - In this paper, we investigate the cooperation issue via spectrum sharing when
employing physical layer security concept into the Device-to-Device (D2D) communications
underlaying cellular networks. First, we derive the optimal joint power control solutions of the
cellular communication links and D2D pairs in terms of the secrecy capacity under a simple
cooperation case and further propose a secrecy-based access control scheme with best D2D pair
selection mechanism. Then, we consider a more general case that multiple D2D pairs can access
the same resource block (RB) and one D2D pair is also permitted to access multiple RBs, and
provide a novel cooperation mechanism in the investigated network. Furthermore, we formulate
the provided cooperation mechanism among cellular communication links and D2D pairs as a
coalitional game. Then, based on a newly defined Max- Coalition order in the constructed game,
we further propose a merge-and-split based coalition formation algorithm for cellular
communication links and D2D pairs to achieve efficient and effective cooperation, leading to

improved system secrecy rate and social welfare. Simulation results indicate the efficiency of the
proposed secrecy-based access control scheme and the proposed merge-and-split based coalition
formation algorithm.
Secure Relay Beamforming for SWIPT in Amplify-and-Forward Two-Way Relay
Networks
Abstract - In this paper, we investigate secure relay beamforming problem for simultaneous
wireless information and power transfer in an amplify-and-forward two-way relay network. We
consider scenarios that the eavesdropper’s channel state information (CSI) is and is not available.
When the eavesdropper’s CSI is available, our objective is to maximize achievable secrecy sum
rate under transmit power constraint and energy harvesting constraint. Since the optimization
problem is nonconvex, we derive its performance upper bound which requires two-dimensional
search where in each step a semidefinite programming is solved.We also propose an upper bound
based rankone solution by employing Gaussian randomization method. To reduce computational
complexity, we transform the optimization problem into a difference of convex programming
and propose a sequential parametric convex approximation (SPCA) based iterative algorithm to
find a locally optimal solution. Furthermore, we also propose a zero-forcing (ZF) based
suboptimal solution. Simulation results demonstrate that the upper bound based rank-one
solution archives performance almost the same as upper bound while has high computational
complexity. The low-complexity SPCA based locally optimal solution performs close to upper
bound. The ZF based suboptimal solution has the lowest computational complexity among
proposed solutions. When the eavesdropper’s CSI is not available, we propose an artificial noise-
aided secure relay beamforming scheme.
IEEE Transactions on Vehicular Technology (January 2016)
Secrecy-Optimized Resource Allocation for Device-to-Device Communication Underlaying
Heterogeneous Networks
Abstract - Device-to-device (D2D) communications recently have attracted much attention for its
potential capability to improve spectral efficiency underlaying the existing heterogeneous
networks (HetNets). Due to no sophisticated control, D2D user equipments (DUEs) themselves

cannot resist eavesdropping or security attacks. It is urgent to maximize the secure capacity for
both cellular users and DUEs. This paper formulates the radio resource allocation problem to
maximize the secure capacity of DUEs for the D2D communication underlaying HetNets which
consist of high power nodes and low power nodes. The optimization objective function with
transmit bit rate and power constraints, which is non-convex and hard to be directly derived, is
firstly transformed into matrix form. Then the equivalent convex form of the optimization
problem is derived according to the Perron-Frobenius theory. A heuristic iterative algorithm
based on the proximal theory is proposed to solve this equivalent convex problem through
evaluating the proximal operator of Lagrange function. Numerical results show that the proposed
radio resource allocation solution significantly improves the secure capacity with a fast
convergence speed.
IEEE Transactions on Vehicular Technology (May 2016)
A Numerical Study on the Wiretap Network With a Simple Network Topology
Abstract - In this paper, we study a security problem on a simple wiretap network, consisting of a
source node S, a destination node D, and an intermediate node R. The intermediate node
connects the source and the destination nodes via a set of noiseless parallel channels, with sizes
n1 and n2, respectively. A message M is to be sent from S to D. The information in the network
may be eavesdropped by a set of wiretappers. The wiretappers cannot communicate with one
another. Each wiretapper can access a subset of channels, called a wiretap set. All the chosen
wiretap sets form a wiretap pattern. A random key K is generated at S, and a coding scheme on
(M, K) is employed to protect M. We define two decoding classes at D. In Class-I, only M is
required to be recovered, and in Class-II, both M and K are required to be recovered. The
objective is to minimize H(K)/H(M) for a given wiretap pattern under the perfect secrecy
constraint. The first question we address is whether routing is optimal on this simple network. By
enumerating all the wiretap patterns on the Class-I/II (3,3) networks and harnessing the power of
Shannon-type inequalities, we find that gaps exist between the bounds implied by routing and the
bounds implied by Shannon-type inequalities for a small fraction (c2%) of all the wiretap
patterns. The second question we investigate is the following: What is min H(K)/H(M) for the
remaining wiretap patterns where gaps exist? We study some simple wiretap patterns and find

that their Shannon bounds (i.e., the lower bound induced by Shannon-type inequalities) can be
achieved by linear codes, which means routing is not sufficient even for the (3, 3) network. For
some complicated wiretap patterns, we study the structures of linear coding schemes under the
assumption that they can achieve the corresponding Shannon bounds. This paper indicates that
the determination of the entropic region of six linear vector spaces cannot be sidestepped. Some
subtle issues o- the network models are discussed, and interesting observations are stated.
Optimal Demand Response Scheduling with Real Time Thermal Ratings of Overhead
Lines for Improved Network Reliability
Abstract - This paper proposes a probabilistic framework for optimal demand response
scheduling in the day-ahead planning of transmission networks. Optimal load reduction plans are
determined from network security requirements, physical characteristics of various customer
types and by recognising two types of reductions, voluntary and involuntary. Ranking of both
load reduction categories is based on their values and expected outage durations, whilst sizing
takes into account the inherent probabilistic components. The optimal schedule of load recovery
is then found by optimizing the customers’ position in the joint energy and reserve market, whilst
considering several operational and demand response constraints. The developed methodology is
incorporated in the sequential Monte Carlo simulation procedure and tested on several IEEE
networks. Here, the overhead lines are modelled with the aid of either seasonal or real-time
thermal ratings. Wind generating units are also connected to the network in order to model wind
uncertainty. The results show that the proposed demand response scheduling improves both
reliability and economic indices, particularly when emergency energy prices drive the load
recovery.
IEEE Transactions on Smart Grid (April 2016)
Secure firmware validation and update for consumer devices in home networking
Abstract - Embedded systems are more than ever present in consumer electronics devices such as
home routers, personal computers, smartphones, smartcards, various sensors to name a few.
Firmware, which is embedded software specifically designed for monitoring and control in
resource constrained conditions, was not a major attack target. However, recent serious cyber

attacks focus on firmware rather than application or operating system levels, because exploiting
the firmware level offers stealth capabilities, e.g., anti-virus software and operating system
cannot reveal such a firmware level exploit. A firmware validation that ensures firmware
integrity is thus required to detect firmware tempering attacks. A remote firmware update is also
required for consumer devices connected to the Internet. In this paper, a secure firmware
validation and update scheme is introduced for consumer devices in a home networking
environment. The proposed scheme utilizes an IDbased mutual authentication and key derivation
to securely distribute a firmware image. A firmware fragmentation with hash chaining is also
applied to guarantee authenticity of the fragmented firmware image. Security analysis results are
presented while considerations are discussed.
Jamming Resilient Communication Using MIMO Interference Cancellation
Abstract - Jamming attack is a serious threat to the wireless communications. Reactive jamming
maximizes the attack efficiency by jamming only when the targets are communicating, which
can be readily implemented using software-defined radios. In this paper, we explore the use of
the multi-input multi-output (MIMO) technology to achieve jamming resilient orthogonal
frequency-division multiplexing (OFDM) communication. In particular, MIMO interference
cancellation treats jamming signals as noise and strategically cancels them out, while transmit
precoding adjusts the signal directions to optimize the decoding performance. We first
investigate the reactive jamming strategies and their impacts on the MIMO-OFDM receivers. We
then present a MIMO-based anti-jamming scheme that exploits MIMO interference cancellation
and transmit precoding technologies to turn a jammed non-connectivity scenario into an
operational network. We implement our jamming resilient communication scheme using
software-defined radios. Our testbed evaluation shows the destructive power of reactive jamming
attack, and also validates the efficacy and efficiency of our defense mechanisms in the presence
of numerous types of reactive jammers with different jamming signal powers.
IEEE Transactions on Information Forensics and Security (July 2016)
Understanding Smartphone Sensor and App Data for Enhancing the Security of Secret
Questions

Abstract - Many web applications provide secondary authentication methods, i.e., secret
questions (or password recovery questions), to reset the account password when a user’s login
fails. However, the answers to many such secret questions can be easily guessed by an
acquaintance or exposed to a stranger that has access to public online tools (e.g., online social
networks); moreover, a user may forget her/his answers long after creating the secret questions.
Today’s prevalence of smartphones has granted us new opportunities to observe and understand
how the personal data collected by smartphone sensors and apps can help create personalized
secret questions without violating the users’ privacy concerns. In this paper, we present a Secret-
Question based Authentication system, called ―Secret-QA‖, that creates a set of secret questions
on basic of people’s smartphone usage. We develop a prototype on Android smartphones, and
evaluate the security of the secret questions by asking the acquaintance/stranger who participate
in our user study to guess the answers with and without the help of online tools; meanwhile, we
observe the questions’ reliability by asking participants to answer their own questions. Our
experimental results reveal that the secret questions related to motion sensors, calendar, app
installment, and part of legacy app usage history (e.g., phone calls) have the best memorability
for users as well as the highest robustness to attacks.
IEEE Transactions on Mobile Computing (March 2016)
Decision Tree and SVM-Based Data Analytics for Theft Detection in Smart Grid
Abstract - Nontechnical losses, particularly due to electrical theft, have been a major concern in
power system industries for a long time. Large-scale consumption of electricity in a fraudulent
manner may imbalance the demand–supply gap to a great extent. Thus, there arises the need to
develop a scheme that can detect these thefts precisely in the complex power networks. So,
keeping focus on these points, this paper proposes a comprehensive top-down scheme based on
decision tree (DT) and support vector machine (SVM). Unlike existing schemes, the proposed
scheme is capable enough to precisely detect and locate real-time electricity theft at every level
in power transmission and distribution (T&D). The proposed scheme is based on the
combination of DT and SVM classifiers for rigorous analysis of gathered electricity consumption
data. In other words, the proposed scheme can be viewed as a two-level data processing and
analysis approach, since the data processed by DT are fed as an input to the SVM classifier.

Furthermore, the obtained results indicate that the proposed scheme reduces false positives to a
great extent and is practical enough to be implemented in real-time scenarios.
IEEE Transactions on Industrial Informatics (June 2016)
A Clean Slate Approach to Secure Ad Hoc Wireless Networking - Open Unsynchronized
Networks
Abstract - Distributed cyberphysical systems depend on secure wireless ad-hoc networks to
ensure that the sensors, controllers, and actuators (or nodes) in the system can reliably
communicate. Such networks are difficult to design because, being inherently complex, they are
vulnerable to attack. As a result, the current process of designing secure protocols for wireless
ad-hoc networks is effectively an arms race between discovering attacks and creating fixes. At
no point in the process is it possible to make provable performance and security guarantees. This
paper proposes a system-theoretic framework for the design of secure open wireless ad-hoc
networks, that provides precisely such guarantees. The nodes are initially unsynchronized, and
join the network at any stage of the operation. The framework consists of a zero-sum game
between all protocols and adversarial strategies, in which the protocol is announced before the
adversarial strategy. Each choice of protocol and adversarial strategy results in a payoff. The
design imperative is to choose the protocol that achieves the optimal payoff. We propose an
―edge-tally supervised‖ merge protocol that is theoretically significant in three ways. First, the
protocol achieves the max-min payoff; the highest possible payoff since the adversarial strategy
always knows the protocol a priori. Second, the protocol actually does better and achieves the
minmax payoff; it is a Nash equilibrium in the space of protocols and adversarial strategies. The
adversarial nodes gain no advantage from knowing the protocol a priori. Third, the adversarial
nodes are effectively limited to either jamming or conforming to the protocol; more complicated
behaviors yield no strategic benefit.
IEEE Transactions on Control of Network Systems (May 2016)

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IEEE Networking 2016 Title and Abstract

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IEEE Networking 2016 Title and Abstract