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TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON DATA MINING

S.No IEEE TITLE ABSTRACT IEEE
. YEAR
1. A Framework Due to a wide range of potential applications, research 2012
for Personal on mobile commerce has received a lot of interests from
Mobile both of the industry and academia. Among them, one of
Commerce the active topic areas is the mining and prediction of
Pattern Mining users’ mobile commerce behaviors such as their
and Prediction movements and purchase transactions. In this paper, we
propose a novel framework, called Mobile Commerce
Explorer (MCE), for mining and prediction of mobile
users’ movements and purchase transactions under the
context of mobile commerce. The MCE framework
consists of three major components: 1) Similarity
Inference Model ðSIMÞ for measuring
the similarities among stores and items, which are two
basic mobile commerce entities considered in this paper;
2) Personal Mobile Commerce Pattern Mine (PMCP-
Mine) algorithm for efficient discovery of mobile users’
Personal Mobile Commerce Patterns (PMCPs); and 3)
Mobile Commerce Behavior Predictor ðMCBPÞ for
prediction of possible mobile user behaviors. To our
best knowledge, this is the first work that facilitates
mining and prediction of mobile users’ commerce
behaviors in
order to recommend stores and items previously
unknown to a user. We perform an extensive
experimental evaluation by simulation and show that our
proposals produce excellent results.
2. Efficient Extended Boolean retrieval (EBR) models were 2012
Extended proposed nearly three decades ago, but have had little
Boolean practical impact, despite their significant advantages
Retrieval compared to either ranked keyword or pure Boolean
retrieval. In particular, EBR models produce meaningful
rankings; their query model allows the representation of
complex concepts in an and-or format; and they are
scrutable, in that the score assigned to a document
depends solely on the content of that document,
unaffected by any collection statistics or other external
factors. These characteristics make EBR models
attractive in domains typified by medical and legal
searching, where the emphasis is on iterative
development of reproducible complex queries of dozens
or even hundreds of terms. However, EBR is much more

computationally expensive than the alternatives. We
consider the implementation of the p-norm approach to
EBR, and demonstrate that ideas used in the max-score
and wand exact optimization techniques for ranked
keyword retrieval can be adapted to allow selective
bypass of documents via a low-cost screening process
for this and similar retrieval models. We also propose
term independent bounds that are able to further reduce
the number of score calculations for short, simple
queries under the extended Boolean retrieval model.
Together, these methods yield an overall saving from 50
to 80 percent of the evaluation cost on test queries
drawn from biomedical search.
3. Improving Recommender systems are becoming increasingly 2012
Aggregate important to individual users and businesses for
Recommendati providing personalized
on Diversity recommendations. However, while the majority of
Using Ranking- algorithms proposed in recommender systems literature
Based have focused on
Techniques improving recommendation accuracy (as exemplified by
the recent Netflix Prize competition), other important
aspects of
recommendation quality, such as the diversity of
recommendations, have often been overlooked. In this
paper, we introduce and explore a number of item
ranking techniques that can generate substantially more
diverse recommendations across all users while
maintaining comparable levels of recommendation
accuracy. Comprehensive empirical evaluation
consistently shows
the diversity gains of the proposed techniques using
several real-world rating data sets and different rating
prediction
algorithms.
4. Effective Many data mining techniques have been proposed for 2012
Pattern mining useful patterns in text documents. However, how
Discovery for to effectively use and update discovered patterns is still
Text Mining an open research issue, especially in the domain of text
mining. Since most existing text mining methods
adopted term-based approaches, they all suffer from the
problems of polysemy and synonymy. Over the years,
people have often held the hypothesis that pattern (or
phrase)-based approaches should perform better than the
term-based ones, but many experiments do not support
this hypothesis. This paper presents an innovative and
effective pattern discovery technique which includes the

processes of pattern deploying and pattern evolving, to
improve the effectiveness of using and updating
discovered patterns for finding relevant and interesting
information. Substantial experiments on RCV1 data
collection and TREC topics demonstrate that the
proposed solution achieves encouraging performance.
5. Incremental Information extraction systems are traditionally 2012
Information implemented as a pipeline of special-purpose processing
Extraction modules targeting
Using the extraction of a particular kind of information. A
Relational major drawback of such an approach is that whenever a
Databases new extraction goal emerges or a module is improved,
extraction has to be reapplied from scratch to the entire
text corpus even though only a small part of the corpus
might be affected. In this paper, we describe a novel
approach for information extraction in which extraction
needs are expressed in the form of database queries,
which are evaluated and optimized by database systems.
Using database queries for information extraction
enables generic extraction and minimizes reprocessing
of data by performing incremental extraction to identify
which part of the data is affected by the change of
components or goals. Furthermore, our approach
provides automated query generation components so
that casual users do not have to learn the query language
in order to perform extraction. To demonstrate the
feasibility of our incremental extraction approach, we
performed experiments to highlight two important
aspects of an information extraction system: efficiency
and quality of extraction results. Our experiments show
that in the event of deployment of a new module, our
incremental extraction approach reduces the processing
time by 89.64 percent as compared to a traditional
pipeline approach. By applying our methods to a corpus
of 17 million biomedical abstracts, our experiments
show that the query performance is efficient for real-
time applications. Our experiments also revealed that
our approach achieves high quality extraction results.
6. A Framework XML has become the universal data format for a wide 2012
for Learning variety of information systems. The large number of
Comprehensibl XML documents existing on the web and in other
e Theories in information storage systems makes classification an
XML important task. As a typical type of semi structured data,
Document XML documents have both structures and contents.
Classification Traditional text learning techniques are not very suitable
for XML document classification as structures are not

considered. This paper presents a novel complete
framework for XML document classification. We first
present a knowledge representation method for XML
documents which is based on a typed higher order logic
formalism. With this representation method, an XML
document is represented as a higher order logic term
where both its contents and structures are captured. We
then present a decision-tree learning algorithm driven by
precision/recall breakeven point (PRDT) for the XML
classification problem which can produce
comprehensible
theories. Finally, a semi-supervised learning algorithm is
given which is based on the PRDT algorithm and the
cotraining framework. Experimental results demonstrate
that our framework is able to achieve good performance
in both supervised and semi-supervised learning with
the bonus of producing comprehensible learning
theories.
7. A Link-Based Although attempts have been made to solve the problem 2012
Cluster of clustering categorical data via cluster ensembles, with
Ensemble the results being competitive to conventional algorithms,
Approach for it is observed that these techniques unfortunately
Categorical generate a final data partition based on incomplete
Data Clustering information. The underlying ensemble-information
matrix presents only cluster-data point relations, with
many entries being left unknown. The paper presents an
analysis that suggests this problem degrades the quality
of the clustering result, and it presents a new link-based
approach, which improves the conventional matrix by
discovering unknown entries through similarity between
clusters in an ensemble. In particular, an efficient link-
based algorithm is proposed for the underlying
similarity assessment. Afterward, to obtain the final
clustering result, a graph partitioning technique is
applied to a weighted bipartite graph that is formulated
from the refined matrix. Experimental results on
multiple real data sets suggest that the proposed link-
based method almost always outperforms both
conventional clustering algorithms for categorical data
and well-known cluster ensemble techniques.
8. Evaluating Path The recent advances in the infrastructure of Geographic 2012
Queries over Information Systems (GIS), and the proliferation of GPS
Frequently technology, have resulted in the abundance of geodata in
Updated Route the form of sequences of points of interest (POIs),
Collections waypoints, etc. We refer to sets of such sequences as
route collections. In this work, we consider path queries

on frequently updated route
collections: given a route collection and two points ns
and nt, a path query returns a path, i.e., a sequence of
points, that connects ns to nt. We introduce two path
query evaluation paradigms that enjoy the benefits of
search algorithms (i.e., fast index maintenance) while
utilizing transitivity information to terminate the search
sooner. Efficient indexing
schemes and appropriate updating procedures are
introduced. An extensive experimental evaluation
verifies the advantages
of our methods compared to conventional graph-based
search.
9. Optimizing Peer-to-Peer multi keyword searching requires 2012
Bloom Filter distributed intersection/union operations across wide
Settings in area networks,
Peer-to-Peer raising a large amount of traffic cost. Existing schemes
Multi keyword commonly utilize Bloom Filters (BFs) encoding to
Searching effectively
reduce the traffic cost during the intersection/union
operations. In this paper, we address the problem of
optimizing the settings of a BF. We show, through
mathematical proof, that the optimal setting of BF in
terms of traffic cost is determined by the statistical
information of the involved inverted lists, not the
minimized false positive rate as claimed by previous
studies. Through numerical analysis, we demonstrate
how to obtain optimal settings. To better evaluate the
performance of this design, we conduct comprehensive
simulations on TREC WT10G test collection and query
logs of a major commercial web search engine. Results
show that our design significantly reduces the search
traffic and latency of the existing approaches.
10. Privacy Privacy preservation is important for machine learning 2012
Preserving and data mining, but measures designed to protect
Decision Tree private information often result in a trade-off: reduced
Learning Using utility of the training samples. This paper introduces a
Unrealized privacy preserving approach that can be applied to
Data Sets decision tree learning, without concomitant loss of
accuracy. It describes an approach to the preservation of
the privacy of collected data samples in cases where
information from the sample database has been partially
lost. This approach converts the original sample data
sets into a group of unreal data sets, from which the
original samples cannot be reconstructed without the
entire group of unreal data sets. Meanwhile, an accurate

decision tree can be built directly from those unreal data
sets. This novel approach can be applied directly to the
data storage as soon as the first sample is collected. The
approach is compatible with other privacy preserving
approaches, such as cryptography, for extra protection.

TECHNOLOGY : DOTNET

DOMAIN : IEEE TRANSACTIONS ON DATA MINING

S.No. IEEE TITLE ABSTRACT IEEE
YEAR
1. A Databases enable users to precisely express their 2012
Probabilistic informational needs using structured queries. However,
Scheme for database query construction is a laborious and error-
Keyword- prone process, which cannot be performed well by most
Based end users. Keyword search alleviates the usability
Incremental problem at the price of query expressiveness. As
Query keyword search algorithms do not differentiate between
Construction the possible informational needs represented by a
keyword query, users may not receive adequate results.
This paper presents IQP—a novel approach to bridge the
gap between usability of keyword search and
expressiveness of database queries. IQP enables a user to
start with an arbitrary keyword query and incrementally
refine it into a structured query through an interactive
interface. The enabling techniques of IQP include: 1) a
probabilistic framework for incremental query
construction; 2) a probabilistic model to assess the
possible informational needs represented by a keyword
query; 3) an algorithm to obtain the optimal query
construction process. This paper presents the detailed
design of IQP, and demonstrates its effectiveness and
scalability through experiments over real-world data and
a user study.
2. Anomaly This survey attempts to provide a comprehensive and 2012
Detection for structured overview of the existing research for the
Discrete problem of detecting anomalies in discrete/symbolic
Sequences: A sequences. The objective is to provide a global
Survey understanding of the sequence anomaly detection
problem and how existing techniques relate to each other.
The key contribution of this survey is the classification of
the existing research into three distinct categories, based
on the problem formulation that they are trying to solve.

These problem formulations are: 1) identifying
anomalous sequences with respect to a database of
normal sequences; 2) identifying an anomalous
subsequence within a long sequence; and 3) identifying a
pattern in a sequence whose frequency of occurrence is
anomalous. We show how each of these problem
formulations is characteristically distinct from each other
and discuss their relevance in various application
domains. We review techniques from many disparate and
disconnected application domains that address each of
these formulations. Within each problem formulation, we
group techniques into categories based on the nature of
the underlying algorithm. For each category, we provide
a basic anomaly detection technique, and show how the
existing techniques are variants of the basic technique.
This approach shows how different techniques within a
category are related or different from each other. Our
categorization reveals new variants and combinations
that have not been investigated before for anomaly
detection. We also provide a discussion of relative
strengths and weaknesses of different techniques. We
show how techniques developed for one problem
formulation can be adapted to solve a different
formulation, thereby providing several novel adaptations
to solve the different problem formulations. We also
highlight the applicability of the techniques that handle
discrete sequences to other related areas such as online
anomaly detection and time series anomaly detection.
3. Combining Web databases generate query result pages based on a 2012
Tag and user’s query. Automatically extracting the data from
Value these query result pages is very important for many
Similarity for applications, such as data integration, which need to
Data cooperate with multiple web databases. We present a
Extraction novel data extraction and alignment method called CTVS
and that combines both tag and value similarity. CTVS
Alignment automatically extracts data from query result pages by
first identifying and segmenting the query result records
(QRRs) in the query result pages and then aligning the
segmented QRRs into a table, in which the data values
from the same attribute are put into the same column.
Specifically, we propose new techniques to handle the
case when the QRRs are not contiguous, which may be
due to the presence of auxiliary information, such as a
comment, recommendation or advertisement, and for
handling any nested structure that may exist in the QRRs.
We also design a new record alignment algorithm that

aligns the attributes in a record, first pairwise and then
holistically, by combining the tag and data value
similarity information. Experimental results show that
CTVS achieves high precision and outperforms existing
state-of-the-art data extraction methods.
4. Creating Knowledge about computer users is very beneficial for 2012
Evolving assisting them, predicting their future actions or detecting
User masqueraders. In this paper, a new approach for creating
Behavior and recognizing automatically the behavior profile of a
Profiles computer user is presented. In this case, a computer user
Automatically behavior is represented as the sequence of the commands
she/he types during her/his work. This sequence is
transformed into a distribution of relevant subsequences
of commands in order to find out a profile that defines its
behavior. Also, because a user profile is not necessarily
fixed but rather it evolves/changes, we propose an
evolving method to keep up to date the created profiles
using an Evolving Systems approach. In this paper, we
combine the evolving classifier with a trie-based user
profiling to obtain a powerful self-learning online
scheme. We also develop further the recursive formula of
the potential of a data point to become a cluster center
using cosine distance, which is provided in the Appendix.
The novel approach proposed in this paper can be
applicable to any problem of dynamic/evolving user
behavior modeling where it can be represented as a
sequence of actions or events. It has been evaluated on
several real data streams.
5. Horizontal Preparing a data set for analysis is generally the most 2012
Aggregations time consuming task in a data mining project, requiring
in SQL to many complex SQL queries, joining tables, and
Prepare Data aggregating columns. Existing SQL aggregations have
Sets for Data limitations to prepare data sets because they return one
Mining column per aggregated group. In general, a significant
Analysis manual effort is required to build data sets, where a
horizontal layout is required. We propose simple, yet
powerful, methods to generate SQL code to return
aggregated columns in a horizontal tabular layout,
returning a set of numbers instead of one number per
row. This new class of functions is called horizontal
aggregations. Horizontal aggregations build data sets
with a horizontal denormalized layout (e.g., point-
dimension, observation variable, instance-feature), which
is the standard layout required by most data mining
algorithms. We propose three fundamental methods to
evaluate horizontal aggregations: CASE: Exploiting the

programming CASE construct; SPJ: Based on standard
relational algebra operators (SPJ queries); PIVOT: Using
the PIVOT operator, which is offered by some DBMSs.
Experiments with large tables compare the proposed
query evaluation methods. Our CASE method has similar
speed to the PIVOT operator and it is much faster than
the SPJ method. In general, the CASE and PIVOT
methods exhibit linear scalability, whereas the SPJ
method does not.
6. Slicing: A Several anonymization techniques, such as generalization 2012
New and bucketization, have been designed for privacy
Approach for preserving micro data publishing. Recent work has
Privacy shown that generalization loses considerable amount of
Preserving information, especially for high dimensional data.
Data Bucketization, on the other hand, does not prevent
Publishing membership disclosure and does not apply for data that
do not have a clear separation between quasi-identifying
attributes and sensitive attributes. In this paper, we
present a novel technique called slicing, which partitions
the data both horizontally and vertically. We show that
slicing preserves better data utility than generalization
and can be used for membership disclosure protection.
Another important advantage of slicing is that it can
handle high-dimensional data. We show how slicing can
be used for attribute disclosure protection and develop an
efficient algorithm for computing the sliced data that
obey the ‘-diversity requirement. Our workload
experiments confirm that slicing preserves better utility
than generalization and is more effective than
bucketization in workloads involving the sensitive
attribute. Our experiments also demonstrate that slicing
can be used to prevent membership disclosure.
7. Tree-Based Discovering semantic knowledge is significant for 2012
Mining for understanding and interpreting how people interact in a
Discovering meeting discussion. In this paper, we propose a mining
Patterns of method to extract frequent patterns of human interaction
Human based on the captured content of face-to-face meetings.
Interaction in Human interactions, such as proposing an idea, giving
Meetings comments, and expressing a positive opinion, indicate
user intention toward a topic or role in a discussion.
Human interaction flow in a discussion session is
represented as a tree. Tree based interaction mining
algorithms are designed to analyze the structures of the
trees and to extract interaction flow patterns. The
experimental results show that we can successfully
extract several interesting patterns that are useful for the

interpretation of human behavior in meeting discussions,
such as determining frequent interactions, typical
interaction flows, and relationships between different
types of interactions.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON NETWORKING

S.No. IEEE ABSTRACT IEEE
TITLE YEAR
1. Adaptive A distributed adaptive opportunistic routing scheme for 2012
Opportunistic multi-hop wireless ad hoc networks is proposed. The
Routing for proposed scheme utilizes a reinforcement learning
Wireless Ad framework to opportunistically route the packets even in
Hoc the absence of reliable knowledge about channel statistics
Networks and network model. This scheme is shown to be optimal
with respect to an expected average per-packet reward
criterion. The proposed routing scheme jointly addresses
the issues of learning and routing in an opportunistic
context, where the network structure is characterized by
the transmission success probabilities. In particular, this
learning framework leads to a stochastic routing scheme
that optimally “explores” and “exploits” the opportunities
in the network.
2. Efficient Motivated by recent emerging systems that can leverage 2012
Error partially correct packets in wireless networks; this paper
Estimating proposes the novel concept of error estimating coding
Coding: (EEC). Without correcting the errors in the packet, EEC
Feasibility enables the receiver of the packet to estimate the
and packet’s bit error rate, which is perhaps the most
Applications important meta-information of a partially correct packet.
Our EEC design provides provable estimation quality
with rather low redundancy and computational overhead.
To demonstrate the utility of EEC, we exploit and
implement EEC in two wireless network applications,
Wi-Fi rate adaptation and real-time video streaming. Our
real-world experiments show that these applications can
significantly benefit from EEC.
3. Exploiting Excess capacity (EC) is the unused capacity in a network. 2012
Excess We propose EC management techniques to improve
Capacity to network performance. Our techniques exploit the EC in
Improve two ways. First, a connection pre provisioning algorithm
Robustness is used to reduce the connection setup time. Second,

of WDM whenever possible, we use protection schemes that have
Mesh higher availability and shorter protection switching time.
Networks Specifically, depending on the amount of EC available in
the network, our proposed EC management techniques
dynamically migrate connections between high-
availability, high-backup-capacity protection schemes and
low-availability, low-backup-capacity protection
schemes. Thus, multiple protection schemes can coexist
in the network. The four EC management techniques
studied in this paper differ in two respects: when the
connections are migrated from one protection scheme to
another, and which connections are migrated.
Specifically, Lazy techniques migrate connections only
when necessary, whereas Proactive techniques migrate
connections to free up capacity in advance. Partial
Backup Reprovisioning (PBR) techniques try to migrate a
minimal set of connections, whereas Global Backup
Reprovisioning (GBR) techniques migrate all
connections. We develop integer linear program (ILP)
formulations and heuristic algorithms for the EC
management techniques. We then present numerical
examples to illustrate how the EC
management techniques improve network performance
by exploiting the EC in wavelength-division-multiplexing
(WDM) mesh
networks.
4. Improving This paper deals with a novel forwarding scheme for 2012
Energy wireless sensor networks aimed at combining low
Saving and computational complexity and high performance in terms
Reliability in of energy efficiency and reliability. The proposed
Wireless approach relies on a packet-splitting algorithm based on
Sensor the Chinese Remainder Theorem (CRT) and is
Networks characterized by a simple modular division between
Using a integers. An analytical model for estimating the energy
Simple CRT- efficiency of the scheme is presented, and several
Based practical issues such as the effect of unreliable channels,
Packet- topology changes, and MACoverhead are discussed. The
Forwarding results obtained show that the proposed algorithm
Solution outperforms traditional approaches in terms of power
saving, simplicity, and fair distribution of energy
consumption among all nodes in the network.
5. Independent In order to achieve resilient multipath routing, we 2012
Directed introduce the concept of independent directed acyclic
Acyclic graphs (IDAGs) in this paper. Link-independent (node-
Graphs for independent) DAGs satisfy the property that any path
Resilient from a source to the root on one DAG is link-disjoint

Multipath (node-disjoint) with any path from the source to the root
Routing on the other DAG. Given a network, we develop
polynomial- time algorithms to compute link-independent
and node-independent DAGs. The algorithm developed in
this paper: 1) provides multipath routing; 2) utilizes all
possible edges; 3) guarantees recovery from single link
failure; and 4) achieves all these with at most one bit per
packet as overhead when routing is based on destination
address and incoming edge. We show the effectiveness of
the proposed IDAGs approach by comparing key
performance indices to that of the independent trees and
multiple pairs of independent trees techniques through
extensive simulations.
6. Latency Multiparty interactive network applications such as 2012
Equalization teleconferencing, network gaming, and online trading are
as a New gaining popularity. In addition to end-to-end latency
Network bounds, these applications require that the delay
Service difference among multiple clients of the service is
Primitive minimized for a good interactive experience. We propose
a Latency EQualization (LEQ) service, which equalizes
the perceived latency for all clients participating in an
interactive network application. To effectively implement
the proposed LEQ service, network support is essential.
The LEQ architecture uses a few routers in the network as
hubs to redirect packets of interactive applications along
paths with similar end-to-end delay. We first formulate
the hub selection problem, prove its NP-hardness, and
provide a greedy algorithm to solve it. Through extensive
simulations, we show that our LEQ architecture
significantly reduces delay difference under different
optimization criteria that allow or do not allow
compromising the per-user end-to-end delay. Our LEQ
service is incrementally deployable in today’s networks,
requiring just software modifications to edge routers.
7. Opportunistic The inherent measurement support in routers (SNMP 2012
Flow-Level counters or NetFlow) is not sufficient to diagnose
Latency performance problems in IP networks, especially for
Estimation flow-specific problems where the aggregate behavior
Using within a router appears normal. Tomographic approaches
Consistent to detect the location of such problems are not feasible in
NetFlow such cases as active probes can only catch aggregate
characteristics. To address this problem, in this paper, we
propose a Consistent NetFlow (CNF) architecture for
measuring per-flow delay measurements within routers.
CNF utilizes the existing NetFlow architecture that
already reports the first

and last timestamps per flow, and it proposes hash-based
sampling to ensure that two adjacent routers record the
same flows. We devise a novel Multiflow estimator that
approximates the intermediate delay samples from other
background flows to significantly improve the per-flow
latency estimates compared to the naïve estimator that
only uses actual flow samples. In our experiments using
real backbone traces and realistic delay models, we show
that the Multiflow estimator is accurate with a median
relative error of less than 20% for flows of size greater
than 100 packets. We also show that Multiflow estimator
performs two to three times better than a prior approach
based on trajectory sampling at an equivalent packet
sampling rate.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON MOBILE COMPUTING

YEAR
1. Acknowledgment- We propose a broadcast algorithm suitable for a wide 2012
Based Broadcast range of vehicular scenarios, which only employs
Protocol for local information acquired via periodic beacon
Reliable and messages, containing acknowledgments of the
Efficient Data circulated broadcast messages. Each vehicle decides
Dissemination in whether it belongs to a connected dominating set
Vehicular Ad Hoc (CDS). Vehicles in the CDS use a shorter waiting
Networks period before possible retransmission. At time-out
expiration, a vehicle retransmits if it is aware of at
least one neighbor in need of the message. To address
intermittent connectivity and appearance of new
neighbors, the evaluation timer can be restarted. Our
algorithm resolves propagation at road intersections
without any need to even recognize intersections. It is
inherently adaptable to different mobility regimes,
without the need to classify network or vehicle speeds.
In a thorough simulation-based performance
evaluation, our algorithm is shown to provide higher
reliability and message efficiency than existing
approaches for non safety applications.
2. FESCIM: Fair, In multihop cellular networks, the mobile nodes 2012
Efficient, and usually relay others’ packets for enhancing the
Secure network performance and deployment. However,
Cooperation selfish nodes usually do not cooperate but make use of
Incentive the cooperative nodes to relay their packets, which has

Mechanism for a negative effect on the network fairness and
Multihop Cellular performance. In this paper, we propose a fair and
Networks efficient incentive mechanism to stimulate the node
cooperation. Our mechanism applies a fair charging
policy by charging the source and destination nodes
when both of them benefit from the communication.
To implement this charging policy efficiently, hashing
operations are used in the ACK packets to reduce the
number of public-key-cryptography operations.
Moreover, reducing the overhead of the payment
checks is essential for the efficient implementation of
the incentive mechanism due to the large number of
payment transactions. Instead of generating a check
per message, a small-size check can be generated per
route, and a check submission scheme is proposed to
reduce the number of submitted checks and protect
against collusion attacks. Extensive analysis and
simulations demonstrate that our mechanism can
secure the payment and significantly reduce the
checks’ overhead, and the fair charging policy can be
implemented almost computationally free by using
hashing operations.
3. Characterizing the Cellular text messaging services are increasingly 2012
Security being relied upon to disseminate critical information
Implications of during emergencies. Accordingly, a wide range of
Third-Party organizations including colleges and universities now
Emergency Alert partner with third-party providers that promise to
Systems over improve physical security by rapidly delivering such
Cellular Text messages. Unfortunately, these products do not work
Messaging as advertised due to limitations of cellular
Services infrastructure and therefore provide a false sense of
security to their users. In this paper, we perform the
first extensive investigation and characterization of the
limitations of an Emergency Alert System (EAS)
using text messages as a security incident response
mechanism. We show emergency alert systems built
on text messaging not only can meet the 10 minute
delivery requirement mandated by the WARN Act,
but also potentially cause other voice and SMS traffic
to be blocked at rates upward of 80 percent. We then
show that our results are representative of reality by
comparing them to a number of documented but not
previously understood failures. Finally, we analyze a
targeted messaging mechanism as a means of
efficiently using currently deployed infrastructure and
third-party EAS. In so doing, we demonstrate that this

increasingly deployed security infrastructure does not
achieve its stated requirements for large populations.
4. Handling In a mobile ad hoc network, the mobility and resource 2012
Selfishness in constraints of mobile nodes may lead to network
Replica partitioning or performance degradation. Several data
Allocation over a replication techniques have been proposed to
Mobile Ad Hoc minimize performance degradation. Most of them
Network assume that all mobile nodes collaborate fully in terms
of sharing their memory space. In reality, however,
some nodes may selfishly decide only to cooperate
partially, or not at all, with other nodes. These selfish
nodes could then reduce the overall data accessibility
in the network. In this paper, we examine the impact
of selfish nodes in a mobile ad hoc network from the
perspective of replica allocation. We term this selfish
replica allocation. In particular, we develop a selfish
node detection algorithm that considers partial
selfishness and novel replica allocation techniques to
properly cope with selfish replica allocation. The
conducted simulations demonstrate the proposed
approach outperforms traditional cooperative replica
allocation techniques in terms of data accessibility,
communication cost, and average query delay.
5. Local Broadcast There are two main approaches, static and dynamic, to 2012
Algorithms in broadcast algorithms in wireless ad hoc networks. In
Wireless Ad Hoc the static approach, local algorithms determine the
Networks: status (forwarding/nonforwarding) of each node
Reducing the proactively based on local topology information and a
Number of globally known priority function. In this paper, we
Transmissions first show that local broadcast algorithms based on the
static approach cannot achieve a good approximation
factor to the optimum solution (an NP-hard problem).
However, we show that a constant approximation
factor is achievable if (relative) position information is
available. In the dynamic approach, local algorithms
determine the status of each node “on-the-fly” based
on local topology information and broadcast state
information. Using the dynamic approach, it was
recently shown that local broadcast algorithms can
achieve a constant approximation factor to the
optimum solution when (approximate) position
information is available. However, using position
information can simplify the problem. Also, in some
applications it may not be practical to have position
information. Therefore, we wish to know whether
local broadcast algorithms based on the dynamic

approach can achieve a constant approximation factor
without using position information. We answer this
question in the positive—we design a local broadcast
algorithm in which the status of each node is decided
“on-the-fly” and prove that the algorithm can achieve
both full delivery and a constant approximation to the
optimum solution.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON IMAGE PROCESSING

YEAR
1. A Primal– Loss of information in a wavelet domain can occur 2012
Dual Method during storage or transmission when the images are
for Total- formatted and stored in terms of wavelet coefficients.
Variation- This calls for image inpainting in wavelet domains. In
Based this paper, a variational approach is used to formulate the
Wavelet reconstruction problem. We propose a simple but very
Domain efficient iterative scheme to calculate an optimal solution
Inpainting and prove its convergence. Numerical results are
presented to show the performance of the proposed
algorithm.
2. A Secret- A new blind authentication method based on the secret 2012
Sharing-Based sharing technique with a data repair capability for
Method for grayscale document images via the use of the Portable
Authentication Network Graphics (PNG) image is proposed. An
of Grayscale authentication signal is generated for each block of a
Document grayscale document image, which, together with the
Images via the binarized block content, is transformed into several
Use of the shares using the Shamir secret sharing scheme. The
PNG Image involved parameters are carefully chosen so that as many
With a Data shares as possible are generated and embedded into an
Repair alpha channel plane. The alpha channel plane is then
Capability combined with the original grayscale image to form a
PNG image. During the embedding process, the
computed share values are mapped into a range of alpha
channel values near their maximum value of 255 to yield
a transparent stego-image with a disguise effect. In the
process of image authentication, an image block is
marked as tampered if the authentication signal
computed from the current block content does not match
that extracted from the shares embedded in the alpha

channel plane. Data repairing is then applied to each
tampered block by a reverse Shamir scheme after
collecting two shares from unmarked blocks. Measures
for protecting the security of the data hidden in the alpha
channel are also proposed. Good experimental results
prove the effectiveness of the proposed method for real
applications.
3. Image We investigate the problem of averaging values on 2012
Reduction lattices and, in particular, on discrete product lattices.
Using Means This problem arises in image processing when several
on Discrete color values given in RGB, HSL, or another coding
Product scheme need to be combined. We show how the
Lattices arithmetic mean and the median can be constructed by
minimizing appropriate penalties, and we discuss which
of them coincide with the Cartesian product of the
standard mean and the median. We apply these functions
in image processing. We present three algorithms for
color image reduction based on minimizing penalty
functions on discrete product lattices.
4. Vehicle We present an automatic vehicle detection system for 2012
Detection in aerial surveillance in this paper. In this system, we
Aerial escape from the stereotype and existing frameworks of
Surveillance vehicle detection in aerial surveillance, which are either
Using region based or sliding window based. We design a pixel
Dynamic wise classification method for vehicle detection. The
Bayesian novelty lies in the fact that, in spite of performing pixel
Networks wise classification, relations among neighboring pixels
in a region are preserved in the feature extraction
process. We consider features including vehicle colors
and local features. For vehicle color extraction, we
utilize a color transform to separate vehicle colors and
non-vehicle colors effectively. For edge detection, we
apply moment preserving to adjust the thresholds of the
Canny edge detector automatically, which increases the
adaptability and the accuracy for detection in various
aerial images. Afterward, a dynamic Bayesian network
(DBN) is constructed for the classification purpose. We
convert regional local features into quantitative
observations that can be referenced when applying pixel
wise classification via DBN. Experiments were
conducted on a wide variety of aerial videos. The results
demonstrate flexibility and good generalization abilities
of the proposed method on a challenging data set with
aerial surveillance images taken at different heights and
under different camera angles.
5. Abrupt The robust tracking of abrupt motion is a challenging 2012

Motion task in computer vision due to its large motion
Tracking Via uncertainty. While various particle filters and
Intensively conventional Markov-chain Monte Carlo (MCMC)
Adaptive methods have been proposed for visual tracking, these
Markov-Chain methods often suffer from the well-known local-trap
Monte Carlo problem or from poor convergence rate. In this paper, we
Sampling propose a novel sampling-based tracking scheme for the
abrupt motion problem in the Bayesian filtering
framework. To effectively handle the local-trap problem,
we first introduce the stochastic approximation Monte
Carlo (SAMC) sampling method into the Bayesian filter
tracking framework, in which the filtering distribution is
adaptively estimated as the sampling proceeds, and thus,
a good approximation to the target distribution is
achieved. In addition, we propose a new MCMC sampler
with intensive adaptation to further improve the
sampling efficiency, which combines a density-grid-
based predictive model with the SAMC sampling, to
give a proposal adaptation scheme. The proposed method
is effective and computationally efficient in addressing
the abrupt motion problem. We compare our approach
with several alternative tracking algorithms, and
extensive experimental results are presented to
demonstrate the effectiveness and the efficiency of the
proposed method in dealing with various types of abrupt
motions.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

YEAR
1. Automatic Dynamic loading of software components (e.g., libraries 2012
Detection of or modules) is a widely used mechanism for an
Unsafe improved system modularity and flexibility. Correct
Dynamic component resolution is critical for reliable and secure
Component software execution. However, programming mistakes
Loadings may lead to unintended or even malicious components
being resolved and loaded. In particular, dynamic
loading can be hijacked by placing an arbitrary file with
the specified name in a directory searched before

resolving the target component. Although this issue has
been known for quite some time, it was not considered
serious because exploiting it requires access to the local
file system on the vulnerable host. Recently, such
vulnerabilities have started to receive considerable
attention as their remote exploitation became realistic. It
is now important to detect and fix these vulnerabilities.
In this paper, we present the first automated technique to
detect vulnerable and unsafe dynamic component
loadings. Our analysis has two phases: 1) apply dynamic
binary instrumentation to collect runtime information on
component loading (online phase), and 2) analyze the
collected information to detect vulnerable component
loadings (offline phase). For evaluation, we
implemented our technique to detect vulnerable and
unsafe component loadings in popular software on
Microsoft Windows and Linux. Our evaluation results
show that unsafe component loading is prevalent in
software on both OS platforms, and it is more severe on
Microsoft Windows. In particular, our tool detected
more than 4,000 unsafe component loadings in our
evaluation, and some can lead to remote code execution
on Microsoft Windows.
2. Fault In recent years, there has been significant interest in 2012
Localization fault-localization techniques that are based on statistical
for Dynamic analysis of program constructs executed by passing and
Web failing executions. This paper shows how the Tarantula,
Applications Ochiai, and Jaccard fault-localization algorithms can be
enhanced to localize faults effectively in web
applications written in PHP by using an extended
domain for conditional and function-call statements and
by using a source mapping. We also propose several
novel test-generation strategies that are geared toward
producing test suites that have maximal fault-
localization effectiveness. We implemented various
fault-localization techniques and test-generation
strategies in Apollo, and evaluated them on several
open-source PHP applications. Our results indicate that a
variant of the Ochiai algorithm that includes all our
enhancements localizes 87.8 percent of all faults to
within 1 percent of all executed statements, compared to
only 37.4 percent for the unenhanced Ochiai algorithm.
We also found that all the test-generation strategies that
we considered are capable of generating test suites with
maximal fault-localization effectiveness when given an
infinite time budget for test generation. However, on

average, a directed strategy based on path-constraint
similarity achieves this maximal effectiveness after
generating only 6.5 tests, compared to 46.8 tests for an
undirected test-generation strategy.
3. Input Domain Search-Based Test Data Generation reformulates testing 2012
Reduction goals as fitness functions so that test input generation
through can be automated by some chosen search-based
Irrelevant optimization algorithm. The optimization algorithm
Variable searches the space of potential inputs, seeking those that
Removal and are “fit for purpose,” guided by the fitness function. The
Its Effect on search space of potential inputs can be very large, even
Local, Global, for very small systems under test. Its size is, of course, a
and Hybrid key determining factor affecting the performance of any
Search- search-based approach. However, despite the large
Based volume of work on Search-Based Software Testing, the
literature contains little that concerns the performance
impact of search space reduction. This paper proposes a
static dependence analysis derived from program slicing
that can be used to support search space reduction. The
paper presents both a theoretical and empirical analysis
of the application of this approach to open source and
industrial production code. The results provide evidence
to support the claim that input domain reduction has a
significant effect on the performance of local, global,
and hybrid search, while a purely random search is
unaffected.
4. PerLa:A A declarative SQL-like language and a middleware 2012
Language and infrastructure are presented for collecting data from
Middleware different nodes of a pervasive system. Data management
Architecture is performed by hiding the complexity due to the large
for Data underlying heterogeneity of devices, which can span
Management from passive RFID(s) to ad hoc sensor boards to
and Integration portable computers. An important feature of the
presented middleware is to make the integration of new
device types in the system easy through the use of device
self-description. Two case studies are described for
PerLa usage, and a survey is made for comparing our
approach with other projects in the area.
5. Comparing Current and future information systems require a better 2012
Semi- understanding of the interactions between users and
Automated systems in order to improve system use and, ultimately,
Clustering success. The use of personas as design tools is becoming
Methods for more widespread as researchers and practitioners
Persona discover its benefits. This paper presents an empirical
Development study comparing the performance of existing qualitative
and quantitative clustering techniques for the task of

identifying personas and grouping system users into
those personas. A method based on Factor (Principal
Components) Analysis performs better than two other
methods which use Latent Semantic Analysis and
Cluster Analysis as measured by similarity to expert
manually defined clusters
6. StakeRare: Requirements elicitation is the software engineering
Using Social activity in which stakeholder needs are understood. It
Networks and involves identifying and prioritizing requirements-a
Collaborative process difficult to scale to large software projects with
Filtering for many stakeholders. This paper proposes StakeRare, a
Large-Scale novel method that uses social networks and collaborative
Requirements filtering to identify and prioritize requirements in large
Elicitation software projects. StakeRare identifies stakeholders and
asks them to recommend other stakeholders and
stakeholder roles, builds a social network with
stakeholders as nodes and their recommendations as
links, and prioritizes stakeholders using a variety of
social network measures to determine their project
influence. It then asks the stakeholders to rate an initial
list of requirements, recommends other relevant
requirements to them using collaborative filtering, and
prioritizes their requirements using their ratings
weighted by their project influence. StakeRare was
evaluated by applying it to a software project for a
30,000-user system, and a substantial empirical study of
requirements elicitation was conducted. Using the data
collected from surveying and interviewing 87
stakeholders, the study demonstrated that StakeRare
predicts stakeholder needs accurately and arrives at a
more complete and accurately prioritized list of
requirements compared to the existing method used in
the project, taking only a fraction of the time
7. QoS A major challenge of dynamic reconfiguration is Quality 2012
Assurance for of Service (QoS) assurance, which is meant to reduce
Dynamic application disruption to the minimum for the system's
Reconfiguratio transformation. However, this problem has not been well
n of studied. This paper investigates the problem for
Component- component-based software systems from three points of
Based view. First, the whole spectrum of QoS characteristics is
Software defined. Second, the logical and physical requirements
for QoS characteristics are analyzed and solutions to
achieve them are proposed. Third, prior work is
classified by QoS characteristics and then realized by
abstract reconfiguration strategies. On this basis,
quantitative evaluation of the QoS assurance abilities of

existing work and our own approach is conducted
through three steps. First, a proof-of-concept prototype
called the reconfigurable component model is
implemented to support the representation and testing of
the reconfiguration strategies. Second, a reconfiguration
benchmark is proposed to expose the whole spectrum of
QoS problems. Third, each reconfiguration strategy is
tested against the benchmark and the testing results are
evaluated. The most important conclusion from our
investigation is that the classified QoS characteristics
can be fully achieved under some acceptable constraints.

TECHNOLOGY : JAVA

DOMAIN : IEEE TRANSACTIONS ON SECURE COMPUTING

YEAR
1. Revisiting Brute force and dictionary attacks on password-only 2012
Defenses remote login services are now widespread and ever
against increasing.Enabling convenient login for legitimate users
Large-Scale while preventing such attacks is a difficult problem.
Online Automated Turing Tests (ATTs) continue to be an
Password effective, easy-to-deploy approach to identify automated
Guessing malicious login attempts with reasonable cost of
Attacks inconvenience to users. In this paper, we discuss the
inadequacy of existing and proposed login protocols
designed to address large-scale online dictionary attacks
(e.g., from a botnet of hundreds of thousands of nodes).
We propose a new Password Guessing Resistant Protocol
(PGRP), derived upon revisiting prior proposals designed
to restrict such attacks. While PGRP limits the total
number of login attempts from unknown remote hosts to
as low as a single attempt per username, legitimate users
in most cases (e.g., when attempts are made from known,
frequently-used machines) can make several failed login
attempts before being challenged with an ATT. We
analyze the performance of PGRP with two real-world
data sets and find it more promising than existing
proposals

2. Data- Malicious software typically resides stealthily on a user's 2012
Provenance computer and interacts with the user's computing
Verification resources. Our goal in this work is to improve the
For Secure trustworthiness of a host and its system data. Specifically,
Hosts we provide a new mechanism that ensures the correct
origin or provenance of critical system information and
prevents adversaries from utilizing host resources. We
define data-provenance integrity as the security property
stating that the source where a piece of data is generated
cannot be spoofed or tampered with. We describe a
cryptographic provenance verification approach for
ensuring system properties and system-data integrity at
kernel-level. Its two concrete applications are
demonstrated in the keystroke integrity verification and
malicious traffic detection. Specifically, we first design
and implement an efficient cryptographic protocol that
enforces keystroke integrity by utilizing on-chip Trusted
Computing Platform (TPM). The protocol prevents the
forgery of fake key events by malware under reasonable
assumptions. Then, we demonstrate our provenance
verification approach by realizing a lightweight
framework for restricting outbound malware traffic. This
traffic-monitoring framework helps identify network
activities of stealthy malware, and lends itself to a
powerful personal firewall for examining all outbound
traffic of a host that cannot be bypassed
3. Design and The multihop routing in wireless sensor networks 2012
Implementati (WSNs) offers little protection against identity deception
on of through replaying routing information. An adversary can
TARF:A exploit this defect to launch various harmful or even
Trust-Aware devastating attacks against the routing protocols,
Routing including sinkhole attacks, wormhole attacks, and Sybil
Framework attacks. The situation is further aggravated by mobile and
for WSNs harsh network conditions. Traditional cryptographic
techniques or efforts at developing trust-aware routing
protocols do not effectively address this severe problem.
To secure the WSNs against adversaries misdirecting the
multihop routing, we have designed and implemented
TARF, a robust trust-aware routing framework for
dynamic WSNs. Without tight time synchronization or
known geographic information, TARF provides
trustworthy and energy-efficient route. Most importantly,
TARF proves effective against those harmful attacks
developed out of identity deception; the resilience of
TARF is verified through extensive evaluation with both
simulation and empirical experiments on large-scale

WSNs under various scenarios including mobile and RF-
shielding network conditions. Further, we have
implemented a low-overhead TARF module in TinyOS;
as demonstrated, this implementation can be incorporated
into existing routing protocols with the least effort. Based
on TARF, we also demonstrated a proof-of-concept
mobile target detection application that functions well
against an antidetection mechanism.
4. On the Content distribution via network coding has received a lot 2012
Security and of attention lately. However, direct application of
Efficiency of network coding may be insecure. In particular, attackers
Content can inject "bogus” data to corrupt the content distribution
Distribution process so as to hinder the information dispersal or even
via Network deplete the network resource. Therefore, content
Coding verification is an important and practical issue when
network coding is employed. When random linear
network coding is used, it is infeasible for the source of
the content to sign all the data, and hence, the traditional
"hash-and-sign” methods are no longer applicable.
Recently, a new on-the-fly verification technique has
been proposed by Krohn et al. (IEEE S&P '04), which
employs a classical homomorphic hash function.
However, this technique is difficult to be applied to
network coding because of high computational and
communication overhead. We explore this issue further
by carefully analyzing different types of overhead, and
propose methods to help reducing both the computational
and communication cost, and provide provable security at
the same time
5. Detecting Collaborative information systems (CISs) are deployed 2012
Anomalous within a diverse array of environments that manage
Insiders in sensitive information. Current security mechanisms
Collaborative detect insider threats, but they are ill-suited to monitor
Information systems in which users function in dynamic teams. In this
Systems paper, we introduce the community anomaly detection
system (CADS), an unsupervised learning framework to
detect insider threats based on the access logs of
collaborative environments. The framework is based on
the observation that typical CIS users tend to form
community structures based on the subjects accessed
(e.g., patients' records viewed by healthcare providers).
CADS consists of two components: 1) relational pattern
extraction, which derives community structures and 2)
anomaly prediction, which leverages a statistical model to
determine when users have sufficiently deviated from
communities. We further extend CADS into MetaCADS

to account for the semantics of subjects (e.g., patients'
diagnoses). To empirically evaluate the framework, we
perform an assessment with three months of access logs
from a real electronic health record (EHR) system in a
large medical center. The results illustrate our models
exhibit significant performance gains over state-of-the-art
competitors. When the number of illicit users is low,
MetaCADS is the best model, but as the number grows,
commonly accessed semantics lead to hiding in a crowd,
such that CADS is more prudent.
6. ES-MPICH2: An increasing number of commodity clusters are
A Message connected to each other by public networks, which have
Passing become a potential threat to security sensitive parallel
Interface with applications running on the clusters. To address this
Enhanced security issue, we developed a Message Passing Interface
Security (MPI) implementation to preserve confidentiality of
messages communicated among nodes of clusters in an
unsecured network. We focus on M PI rather than other
protocols, because M PI is one of the most popular
communication protocols for parallel computing on
clusters. Our MPI implementation-called ES-MPICH2-
was built based on MPICH2 developed by the Argonne
National Laboratory. Like MPICH2, ES-MPICH2 aims at
supporting a large variety of computation and
communication platforms like commodity clusters and
high-speed networks. We integrated encryption and
decryption algorithms into the MPICH2 library with the
standard MPI interface and; thus, data confidentiality of
MPI applications can be readily preserved without a need
to change the source codes of the MPI applications. MPI-
application programmers can fully configure any
confidentiality services in MPICHI2, because a secured
configuration file in ES-MPICH2 offers the programmers
flexibility in choosing any cryptographic schemes and
keys seamlessly incorporated in ES-MPICH2. We used
the Sandia Micro Benchmark and Intel MPI Benchmark
suites to evaluate and compare the performance of ES-
MPICH2 with the original MPICH2 version. Our
experiments show that overhead incurred by the
confidentiality services in ES-MPICH2 is marginal for
small messages. The security overhead in ES-MPICH2
becomes more pronounced with larger messages. Our
results also show that security overhead can be
significantly reduced in ES-MPICH2 by high-
performance clustersRequirements elicitation is the
software engineering activity in which

7. On the In 2011, Sun et al. [CHECK END OF SENTENCE] 2012
Security of a proposed a security architecture to ensure unconditional
Ticket-Based anonymity for honest users and traceability of
Anonymity misbehaving users for network authorities in wireless
System with mesh networks (WMNs). It strives to resolve the conflicts
Traceability between the anonymity and traceability objectives. In this
Property in paper, we attacked Sun et al. scheme's traceability. Our
Wireless analysis showed that trusted authority (TA) cannot trace
Mesh the misbehavior client (CL) even if it double-time
Networks deposits the same ticket.

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