Cross domain identity trust management for grid computing

International Journal of Security, Privacy and Trust Management (IJSPTM) Vol 3, No 2, April 2014
DOI : 10.5121/ijsptm.2014.3202 11
CROSS-DOMAIN IDENTITY TRUST MANAGEMENT
FOR GRID COMPUTING
Amr Farouk, Mohamed M. Fouad and Ahmed A. Abdelhafez
Department of Computer Engineering, Military Technical College, Cairo, Egypt
ABSTRACT
The grid computing coordinates resource sharing between different administrative domains in large scale,
dynamic, and heterogeneous environment. Efficient and secure certificateless public key cryptography (CL-
PKC) based authentication protocol for multi-domain grid environment is widely acknowledged as a
challenging issue. Trust relationships management across domains is the main objective of authentication
protocols in real grid computing environments. In this paper, we discuss the grid pairing-free certificate-
less two-party authenticated key agreement (GPC-AKA) protocol. Then, we provide a cross domain trust
model for GPC-AKA protocol in grid computing environment. Moreover, we analysis the GPC-AKA
protocol in multiple trust domains simulated environment using GridSim toolkit.
KEYWORDS
Certificate-less authenticated key agreement, cross-domain identity trust, grid computing.
1. INTRODUCTION
For fully secure and efficient grid entities authentication, it is required to build a provable secure
authenticated key agreement (AKA) protocol. Moreover, it should meet with the requirements of
large scale distributed, heterogeneous and dynamic grid virtual organizations (VO), that usually
spans multiple trust domains [1]. Hence, trust in grid computing is the firm belief between grid
entities to enable grid systems to work normally in the context of the fundamental grid functions
[2]. Trust relationship in grid computing environments is classified based on trust domain
boundaries into three categories [3]: i) intra-domain trust refers to the trust relationship between
members and the power institutions of the domain. ii) interdomain recommendation trust is a kind
of trust relationship which is set up by the power institutions in the grid levels. iii) cross-domain
trust means the trust relationship among members of different domains. As well, based on trust
approaches, trust relationship is classified into the following categories [2]: i) identity trust (i.e.,
objective trust) is associated with verifying the authenticity of an entity and focuses on the
objective credentials. ii) behavioral trust (i.e., subjective trust) deals with a wider notion of an
entity’s “trustworthiness”, which depends on certain contexts. The relationship can take many
directions. First, in resource allocation process, the resource provider want to know the trust level
(i.e., acceptable code and not harmful) of the grid user requested job. Second, the resource
provider guarantees to the grid user, the process execution without interruption and the user's
privacy protection [2].
Grid computing as a VO for resources collaboration and coordination, has become so prevalent
that grid trust relationship become an intensive topic. In the trust research area, the numerous
literatures proposed the different trust models. These have provided the valuable thoughts for

12
trust research in the grid environment. As different management domains take different security
policies to mange intra-domain security in the grid, it’s difficult to form an overall management
strategy among different domains [3]. In order to build trust relations between entities and
different trust domains, we give the ring framework of objective trust model. Ring topology has
no root KGC, so no single point of trust. This approach construct a global trust infrastructure
composed of group of trust authorities (i.e., KGCs) without the hierarchy level limitation, so it
has a scalability advantage. A objective trust modeling method suitable in grid environment is
proposed based on the characteristics of grid computing and the features of objective trust.
This paper addresses trust management issues in grid computing and analyses some relevant
cross-domain scenarios. Then it derives main requirements in terms of cross authentication. We
discuss the efficient GPC-AKA protocol based on GDH complexity problem. As well, we
propose a cross-domain grid trust model based on GPC-AKA protocol. In addition, we design and
implement a simulation of the proposed grid trust model based on a world wide grid testbed. The
testbed is composed of multiple organizations, each have its own KGC, and concerned to build a
trust relationships with the others. Furthermore, we analyses the performance of cross-domain
GPC-AKA protocol in complex simulated scenarios.
The rest of this paper is organized as follows. Trust in grid computing is described in Section II.
The grid pairing-free CLAKA protocol is presented in Section III. Section IV shows the proposed
Grid trust management model based on GPC-AKA protocol. Simulation experiment of cross-
domain GPC-AKA using GridSim is introduced in Section V. Finally, Section VII provides our
research conclusions.
2. TRUST IN GRID COMPUTING
Recently, trust has been recognized as an important factor for grid computing security. Several
interesting trust models have been proposed for integration into the Grid computing systems [4]–
[7]. However, we have found that theses trust models specialize in applying trust for enhancement
of resource allocation functions of a grid system; also the trust mechanisms are mainly based on
behavioral methods, which is not scalable nor efficient.
A grid computing environment is a virtual organization (VO) that is composed of several
autonomous domains in which different security policies are applied. The grid computing
environment features are [8]: The user population and resource pool (e.g., quantity, location) are
large and dynamic. A computation is composed of a dynamic group of processes (i.e., created and
destroyed dynamically during program execution) running on different resources and sites. The
pre-trust relationships establishment between different grid sites is impractical due to the dynamic
nature of the grid computing environment [8].
The trust management is a distinct and crucial component of grid services security. Aspects of
the trust management problem include formulating security policies and security credentials,
determining whether particular sets of credentials satisfy the relevant policies, and deferring trust
to third parties.
First, security policy, is a set of rules that define the grid users (i.e., security subjects), grid
resources (i.e., security objects) and relationships among them [8]. Resources may require
different local policies (e.g., authentication and authorization mechanisms), that apply at the
different sites, which we will have limited ability to change. Authentication is the first line of
defence in the grid security policy that provides mapping from local security policies into a global
framework [8].

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Second, security credential can be defined as a piece of information that is used to prove the
identity of a subject [8]. Federation of identities when grid entities have different identities and/
or credentials in different security domains. Identity federation is a set of organizations that
establish trust relationships with respect to the federated identity information. Identity federation
technology (e.g., Shibboleth) enables that no need for direct trust relationship between users and
accessed domains. However, the identity server store the individual credentials securely, the main
challenge is to protect the user's privacy.
Third, trust domain can be defined as a logical, administrative structure that holds a single,
consistent local security policy [8]. In this study, we will focus on the third point which is grid
trust relationships using grid authentication protocol.
We can solve grid trust management problems using grid authentication protocols based on
identity that distinguishes a distinct user, process or resource within the context of a specific
namespace. Identity Authentication: proving as association between an entity and an identifier.
Attribute Authentication: proving as association between an entity and an attribute.
We will use the proposed GPC-AKA protocol based on the general grid security architecture of
Foster et. al. [8]. Our approach to trust management is based on the following general principles:
unified mechanism, flexibility, locality of control and separation of mechanism from policy.
3. EFFICIENT AND SECURE GRID PAIRING-FREE CL-AKA
Wang et. al. [9] present the first grid certificate-less authentication based on certificate-less public
key cryptography (CL-PKC), that is a kind of cryptography between certificate based and
identity-based PKC. The bilinear pairing is then considered as an expensive cryptography
primitive. Therefore, a number of pairing-free CL-AKA protocols, have been proposed to
improve efficiency. These protocols, either have a security issues or are not efficient to be
practical implemented in real environments.
We focus on the more recent efficient pairing-free CL-AKA protocol, as formal prove the
protocol security to be suitable for practical grids. Recently, Amr et. al. [10] proposed an efficient
and provable secure grid pairing-free certificate-less two-party authenticated key agreement
(GPC-AKA) protocol. The GPC-AKA protocol uses a user proxy (UP) and resource proxy (RP)
to support the grid single sign on (SSO) and frequent mutual authentication requests [8].
GPC-AKA protocol requires 3 elliptic curve point multiplications, 5 elliptic curve point additions,
2 hashing functions, and 2 message exchanges. The proposed Pairing-free certificate-less two
party authenticated key agreement for grid (GPC-AKA) is introduced into two phases, as
illustrated in Fig. 1 and Fig. 2, respectively.

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Figure 1. Proposed GPC-AKA key generation setup scheme (Phase 1).
Figure 2. Proposed key agreement scheme GPC-AKA (Phase 2).
4. CROSS-DOMAIN GRID TRUST MANAGEMENT
Grid computing environments include different resources through cross-organizational
boundaries on a large scale basis. This heterogeneous environment consists of multiple
disconnected trust domains, applying its own policies and mechanisms for authentication.
Consequently, an important challenge for the GPC-AKA is to provide a cross-domain
authentication service. It should be pointed out that existing identity trust models suffer from a

15
restricted and static vision of trust (i.e., strict hierarchies where trust flows from the root to the
leaves).
We propose a novel trust model reflecting the required dynamic nature of trust for grid entities,
through cross organizational boundaries, with little administrative overhead. Based on cross-
domain grid computing GPC-AKA authentication protocol, a Grid Trust Management (GTM)
model has been designed to establish trust relations between grid entities. Cross-domain GPC-
AKA trust model is shown in Fig. 3.
Figure 3. Grid Trust Model.
We adopt some common approaches for scalability and flexibility in our design. To our
knowledge, the following discussion represents the first such grid trust management model that
has been defined to this level of detail. Our proposed GTM design model answers the following
questions:
1) How to add new KGC? According to the grid virtual organization concept, we can add a new
KGC to the virtual organization KGCs group in ring topology avoiding the hierarchal problems,
by sharing the same system parameters. Since, in the real grid, most trust domains are
autonomous, using different system parameters. So in our GTM model, all the system parameters
of PKG are the same, except the system public key and master key.
2) How to do key revocation? key expiration in GTM is straightforward, used for key revocation.
Short-term key revocation using fine-grained identifier (e.g., extend the user’s identifier to
include another field that specifies a validation period). The validation period inversely
proportional to the KGC server load.
3) How to do key renew? In a grid environment, it is normal practice to renew the user’s long-
term keys on a monthly or yearly basis. This can be done through the KGC issuing a new private
key directly to the user through a secure channel. Short-term keys are used for various security
service such as mutual authentication, single sign-on and delegation.
4) How to build trust between KGCs? Trust relationships between KGCs can be established as
follows, system parameters of the KGCs are then assumed to be trusted by all users and
recognized by the grid system, as shown in Table I.
5) How to build cross-domain trust between entities? Cross-domain GPC-AKA protocol
consistency is proved as follow.

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Table 1. Cross-Domain GPC-AKA.
Parameters
D1 D2
U1 KGC1 KGC2 R2
Public Pu1 P01,Params P02,Params Pr2
Secret Xu1,tu1 S1,Du1 S2,Dr2 Xr2,tr2
Where Params = {Fp,E/Fp,G, g,H1,H2} are the same in both KGCs (i.e., KGC1,KGC2) and grid
entities (i.e., U1,R2).
Cross-domain GPC-AKA protocol consistency is proved:
KU1R2 = (tU1 + DU1 + xU1)(TR2 + PR2 + RR2 + H1(ID R2,R R2, P R2)P0)
= (tU1 + DU1 + xU1)((t R2.P) + (x R2.P) + (r R2.P) + (Q R2.sP))
= (tU1 + DU1 + xU1)(t R2 + x R2 + r R2 + Q R2.s)P
= (tU1 + DU1 + xU1)(t R2 + x R2 + D R2)P = K R2U1
where IDR2= IDKGC2||IDR2.
5. CROSS-DOMAIN GPC-AKA SIMULATION EXPERIMENT
In this section, we present the simulation experiment of cross-domain GPC-AKA protocol in grid
computing environment. Grid network topology is explained in Section V-A. Furthermore, a
GPC-AKA simulation using GridSim toolkit is provided in Section V-B.
The only feasible way to analyze repeatable experiments and studies that are not possible in real
dynamic grid environment is the using of grid simulator. We choose the Java-based simulation
platform GridSim Toolkit [11] with network extension package to simulate the message exchange
of the proposed multiple trust domains GPC-AKA protocol. As well, GridSim is based on
SimJava which is a discrete event simulation tool based on Java and simulates various entities by
multiple thread. This aligns well with randomness of grid computing entity action.
5.1. Grid Network Topology
In this section, we provide a scenario of the cross-domain authentication using GPC-AKA
protocol. We have created an experiment based on the World Wide Grid testbed [12], as shown in
Fig. 4.

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Figure 4. Cross-Domain Grid Network Topology.
A Grid resource contains one or more Machines. Similarly, a machine contains one or more
processing elements (PEs) or CPUs. For this experiment, we are simulating five VO domains and
each resource belongs to one of them, with three Machines that contains one or more PEs. The
VO mapping is done by taking into account a geographical dissemination among the resources.
Table II summarizes the characteristics of simulated resources, which were obtained from a real
World Wide Grid testbed.
Table 2. Grid Topology and Resources Characteristics.
Domain
Resource
Name
Resource Characteristics Host name & Location
No.
CPU
Time
Zone
D1 N1 UltraAX-i2, SunOS, Sparc grid1.fmridc.org, USA, Hanover 16 -4
D2 N2 Sun HPC 3500, GridEngine, Solaris,
Sparc
sunresearch.qub.ac.uk, UK, Belfast 6 +1
D3 N3 SGI Origin 3800, IRIX 6.5.17m, Irix,
MIPS
calvin.nuigalway.ie, Ireland,
Galway
40 +1
D4 N4 SGI Onyx 3000, IRIX64, Irix, MIPS onyx3.zib.de, Germany, Berlin 20 +2
D5 N5
IBM eServer, Linux, IA-32
belle.physics.usyd.edu.au, Australia,
Sydney
4 +11

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We created five scenarios, each time we increased the total grid users {5,10,15,20,25} to simulate
the concurrent requests and uniformly distributed them among the five trust domains, each
domain has {1,2,3,4,5} user(s). In our simulation setup, some parameters are set identical for all
network elements, such as the maximum transfer unit (MTU) of links is set to 1,500 bytes and the
latency is set to 10 milliseconds. We can conclude the simulation experiment parameters in Table
III.
Table 3. Simulation Parameters.
Parameter Value
number of grid users {5,10,15,20,25}
number of grid resource 5
number of gridlets 1
baud rate 1000 bits/sec
propagation delay 10 msec
max. transmission unit (MTU) 1500 byte
5.2. Simulation using GridSim Toolkit
Object-oriented GridSim toolkit allows modeling of heterogeneous types of resources, located in
any time zone. As well, multiple user can simultaneously submit tasks for execution in the same
resource, that may be timeshared or space-shared. In addition, statistics of operations can be
recorded and they can be analyzed using GridSim statistics analysis methods.
GridSim Toolkit V5.2 is run, on a 2 GHz Intel core 2 duo with 6 GB RAM. This simulation
scenario shows how to create user and resource entities connected via a network topology, using
link and router. In addition, background traffic functionality is explained in this scenario. Fig. 5
shows GPC-AKA simulation steps using GridSim.
Figure 5. Main GPC-AKA Simulation Steps using GridSim.
Independent tasks are heterogeneous in terms of processing time and input files size. In GridSim,
such tasks can be created and their requirements can be defined through gridlet objects [13]. We
simulate GPC-AKA message exchange using the gridlet concept in GridSim. One gridlet for
mutual GPC-AKA instance for each pair of grid entities.

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6. DISCUSSION AND ANALYSIS
In the first experiment, we simulate the cross-domain GPCAKA message exchange without
background traffic, as shown in Fig. 6. We simulate 5 trust domains and increase the number of
users per each domain {1,2,3,4,5} who send concurrent requests to check GPC-AKA scalability
and get the minimum, maximum, and the average of the response time. For 1 user per domain,
with 5 total grid users, the minimum response time 126.30 seconds, maximum response time
140.52 seconds, and average response time 136.72 seconds. For 2 users per domain, with 10 total
grid users, the minimum response time 169.30 seconds, maximum response time 214.14 seconds,
and average response time 191.96 seconds with 71% increased. For 3 users per domain, with 15
total grid users, the minimum response time 197.30 seconds, maximum response time 290.15
seconds, and average response time 246.20 seconds with 78% increased. For 4 users per domain,
366.13 seconds, and average response time 301.94 seconds with82% increased. For 5 users per
domain, with 25 total grid users. the minimum response time 269.30 seconds, maximum response
time 440.92 seconds, and average response time 357.54 seconds with 84% increased.
Figure 6. Concurrent Requests versus Time without Background Traffic.
In the real grid environment there is a background traffic. So, the second experiment, simulates
the GPC-AKA message exchange with background traffic, as shown in Fig. 7. For 1 user per
domain, with 5 total grid users, the minimum response time 139.64 seconds, maximum response
time 172.02 seconds, and average response time 151.14 seconds. For 2 users per domain, with 10
total grid users, the minimum response time 172.92 seconds, maximum response time 229.65
seconds, and average response time 202.42 seconds with 75% increased. For 3 users per domain,
352.02 seconds, and average response time 278.84 seconds with73% increased. For 4 users per
domain, with 20 total grid users, per minimum response time 233.30 seconds, maximum response
time 420.43 seconds, and average response time 321.41 seconds with 87% increased. For 5 users
per domain, with 25 total grid users, the minimum response time 269.30 seconds, maximum
response time 580.02 seconds, and average response time 417.20 seconds with 77% increased.

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Figure 7. Concurrent Requests versus Time without Background Traffic.
7. CONCLUSIONS
According to the trust relationships between different security domains, an authentication
protocol suitable for multiple security (i.e., trust) domains in grid computing is proposed in this
paper. We present an efficient and secure pairing-free two party certificate-less authenticated key
agreement protocol for grid computing (GPC-AKA) based on GHD complexity problem. Based
on GPC-AKA, a grid trust management (GTM) model is proposed. At last, the authentication
protocol is analyzed with simulated grid environment using GridSim. So, we can infer that GPC-
AKA is a cross-domain authentication protocol suitable for large scale and dynamic grid
computing environments.
REFERENCES
[1] A. Farouk, A. A. Abdelhafez, and M. M. Fouad, “Authentication mechanisms in grid computing
environment: Comparative study,” in IEEE International Conferencce on Engineering and
Technology, Oct. 2012, pp. 1–6.
[2] J. Luo, X. Ni, and J. Yong, “A trust degree based access control in grid environments,” Information
Sciences, vol. 179, no. 15, pp. 2618–2628, 2009.
[3] H. Hai-sheng and W. Ru-chuan, “A new subjective trust model in grid computing,” in Computer
Application and System Modeling (ICCASM), 2010 International Conference on, vol. 9. IEEE, 2010,
pp. V9–360.
[4] Z. Yongqiang, L. Qiang, and T. Haibo, “A hybrid system for authentication service,” in 5th
International Conference on Intelligent Networking and Collaborative Systems, 2013, pp. 821–826.
[5] L. Guoyuan, B. Yuyu, and L. Min, “Trust based access control policy in multi-domain of cloud
computing,” Journal of Computers, vol. 8, no. 5, pp. 1357–1365, may 2013.
[6] T. Liye and J. Wei, “A multi trust chain scheme in trusted crossdomain interaction,” in International
Conference on Industrial Control and Electronics Engineering, 2012, pp. 550–553.
[7] Z. Shaomin, Z. Yue, and W. Baoyi, “A novel grid trust model based on fuzzy theory,” in Third
International Conference on Network and System Security, 2009, pp. 203–207.
[8] I. Foster, C. Kesselman, G. Tsudik, and S. Tuecke, “A security architecture for computational grids,”
in Proceedings of the 5th ACM conference on Computer and communications security. ACM, 1998,
pp. 83–92.
[9] W. Shengbao, C. Zhenfu, and B. Haiyong, “Efficient certificateless authentication and key agreement
(CL-AK) for grid computing,” in International Journal of Network Security, vol. 7, no. 3, Nov. 2008,
pp. 342–347.

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[10] A. Farouk, M. M. Fouad, and A. A. Abdelhafez, “Analysis and improvement of pairing-free
certificate-less two-party authenticated key agreement protocol for grid computing,” International
Journal of Security, Privacy and Trust Management (IJSPTM), vol. 3, no. 1, 2014.
[11] S. Anthony, P. Gokul, B. Rajkumar, and T. Chen-Khong, “Constructing a grid simulation with
differentiated network service using gridsim,” in IEEE, 2004.
[12] A. Barmouta, “Authorisation and accounting services for the world wide grid,” Master of Science,
School of Computer Science and Software Engineering, University of Western Australia, jun 2004.
[13] B. Rajkumar and M. Manzur, “Gridsim: a toolkit for the modeling and simulation of distributed
resource management and scheduling for grid computing,” in Concurrency and Computation:
Practice and Experience, vol. 14. John Wiley & Sons, Ltd, Feb 2002, pp. 1175–1220.
Authors
Amr Farouk received the Bachelor engineering from the Military Technical College
(MTC), Cairo, Egypt, in 1997, and the Masters' engineering degrees from Engineering
faculty, Mansoura university, Mansoura, Egypt in 2009. He is currently a PhD arguing
from Computer engineering, MTC, Cairo, Egypt. His research interests include network
security, authentication protocols, certificate-less authenticated key agreement.
M. M. Fouad received the Bachelor engineering (honors, with great distinction) and
Masters' engineering degrees from the Military Technical College (MTC), Cairo, Egypt, in
1996 and 2001, respectively. As well, he received the Ph.D. degree in Electrical and
Computer engineering from Carleton University, Ottawa, Ontario, Canada, in 2010. He is
currently a faculty member with the Department of Computer Engineering, MTC. His
research interests are in online handwritten recognition, image registration, image
reconstruction, super-resolution, video compression and multiview video coding.
Ahmed A. AbdelHafez; received the B.S. and M.Sc. in Electrical Engineering from
Military Technical College (MTC) in 1990, 1997 respectively, and his Ph.D from School
of Information Technology and Engineering (SITE), University of Ottawa, Ottawa,
Canada in 2003. Dr. Abdel-Hafez is the head of the Cryptography Research Center
(CRC), Egypt where he is leading many applied researches in communication security
field. He is a visiting lecturer in Communication Dept. MTC, and other universities in
Egypt. Dr. Abdel-hafez published more than 40 papers in specialized conferences and
periodicals. His research interests include wireless networks and data security, mathematical cryptography
and provable security.

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