An Analysis of Location Independent Key Predistribution Schemes for Wireless Sensor Network

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 04 Issue: 07 | July -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 1958
An Analysis of Location Independent Key Pre distribution Schemes for
Wireless Sensor Network
Monjul Saikia1 and Md. A Hussain2
North Eastern Regional Institute of Science and Technology
Nirjuli-791109, Arunachal Pradesh, India
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Security in wireless sensor network can be
achieve by symmetric key encryption with minimum cost.
The symmetric key encryption technique requires agreeing
on one common secret key among two parties. Therefore it
is essential to have a common key among sensor nodes. The
key predistribution solves the purpose by assigning secret
keys among sensor nodes. Due to high chance of physical
capture of sensor nodes and lack of prior information of
configuration after deployment makes key predistribution
more challenging. Several key predistribution schemes
have been proposed. In this paper we try to discuss the
basics of key predistribution scheme and analyze different
schemes proposed by researchers, along with some
experimental results. Also we have discussed the
properties need to be fulfilled for an efficient scheme.
Keywords: Sensor Network; KPS; Security; Connectivity;
Resilience.
1. INTRODUCTION
The main objective of a WSN is to collect sensitive
information from the physical world where human cannot
survive. These networks of tiny devices can operate in any
locations where wired network is possible. The wireless
sensor networks are deployed to sense, process and
distribute information of some target physical
environments. Deployment strategy may dependent to the
location of each sensor node or may be independent of the
location. The deployment environment can be a controlled
one or an uncontrolled. Security of sensor nodes is highly
important when deployed in an uncontrolled environment
as there may be high chance of node compromise by
adversary.
2. KEY DISTRIBUTION SCHEMES FOUNDATIONS
The fundamental model for security for sensor network
with Key Predistribution Schemes can be devided into four
phases, namely
i) Key Predistribution phase
ii) Sensor Deployment phase
iii) Shared Key Discovery phase
iv) Pairwise Key Establishment phase
i) Key Predistribution phase: A centralized server is
responsible for determining the keys to be preloaded into
the sensor nodes. It first generates a large set of keys called
key pool. From this set, keys are loaded to the sensor nodes
based on some algorithm such that with minimum number
of keys high connectivity can be achieved. With the set of
keys loaded into the sensor nodes forms a key chain or key
ring.
ii) Sensor Deployment phase: After keys are loaded to the
sensor nodes these nodes are ready to deploy in target
area. Number of sensors within the communication range
(n') is usually much smaller than the deployed nodes (N).
Therefore, it is obvious that storing a common key which is
not in communication range may lead to unnecessary
storage for the sensor nodes.
iii) Shared Key Discovery phase: If a sensor node wants to
communicate to other sensor node within its
communication range, then they look up into their key
chain for the preloaded common secret key. This phase is
called a shared key discovery phase.
iv) Pair-wise Key Establishment phase: After discovering a
shared key secure communication can progress with
successive symmetric key encryption process. On the other
hand if a node does have a pair-wise key with a destination
node, the sensor node has to find a key path to setup their
pair-wise key for secure communication with some routing
mechanism.
3. EXISTING KEY DISTRIBUTION SCHEMES
Here we will discuss in details the various key
predistribution schemes. Starting with a random key
predistribution scheme proposed by Eschenauer and Gligor
in 2002 a numerous number of schemes have been
invented there after. Some of the location independent KPS
is listed in the table-1. The schemes are said to be location
independent in the sense that no prior information is available
regarding location/coordinates of the sensor nodes prior to
deployment.

Table 1: Location Independent KPS
Sl Schemes Year Authors
1 Single key scheme - -
2 Fully pairwise key scheme - -
3 Blom’s method 1984 R Blom
4 Method by Blundo et al. 1993
C. Blundo et.
al.
5 Eschenauer and Gligor’s method 2002
L Eschenauer
et. al.
6 q‐Composite scheme 2003 H Chan et. al.
7
Multiple space key pre‐distribution
scheme
2003 Du W et. al.
8
Polynomial pool‐based key pre‐
distribution scheme
2003 Liu D et. al.
9
Pseudo‐random function‐based key pre‐
distribution scheme
2004
Pietro RD et.
al.
10
Combinatorial design‐based key pre‐
distribution scheme (BIBD‐based method)
2004 S. A. Camtepe
11
PIKE: Peer Intermediaries for Key
Establishment
2005 H Chan et. al.
12
Expander graph‐based key pre‐
distribution scheme
2006
S. A. Camtepe
et. al.
13
Combinatorial design‐based key pre‐
distribution scheme (hybrid design‐based
method)
2007
S. A. Camtepe
et. al.
14
Random assignment set selection key pre‐
distribution scheme
2007 Tague P et. al.
15 BABEL key pre‐distribution scheme 2007 Deng J et. al.
16
Random perturbation‐based key
establishment scheme
2007 Zhang W et. al.
17 Non-interactive key establishment scheme 2010 Yu C‐M et. al.
4. DISCUSSIONS AND EXPERIMENTS
Here, some of these schemes have been discussed with
experimental results:
1. Single Key Predistribution Scheme [2]: It is a straight
forward method of key predistribution scheme, where a
single key is shared among all nodes. Therefore it is highly
vulnerable to attacked. One node compromise will affect
the entire network.
Fig -1: Single Key Predistribution
Figure 1 shows the comm. graph in Single Key
Predistribution Scheme. In this approach a common key K
is preloaded in all the sensor nodes. Any node can use the
key to transmit information using the same secret key K,
which can be shown using an incidence graph, as shown in
figure 2.
Fig - 2: Incidence Graph- Single Key Predistribution
Although the scheme is highly resource efficient, it has
lowest resilience and may collapsed the network on single
node capture.
2. Fully Pairwise Key Predistribution Scheme [2,11]: In fully
pairwise key predistribution scheme, for each sensor node
n-1 keys are preloaded. Each key corresponds to key share
with other nodes.
Fig - 3: Fully Pairwise Key Predistribution Scheme
Figure 3, shows key share among nodes and in figure 4 the
respective incidence graph is shown.
Fig - 4: Incidence Graph- Fully Pairwise Key Predistribution
Scheme
3. Eschenauer and Gligor’s Scheme [1, 2]: This is a type of
randomly allocate key from a large set of keys to form the
key chain.
For example, let total number of sensor nodes be N=10 and
key pool set P = {1,2,3,4,5,6,7,8,9,10} and the key chain size
is k = 3. The formation of key chain after random
distribution can be seen as given in table -2.
Table 2: Key Ring
Node Key Ring Node Key Ring
N#1 {1,7,7} N#6 {1,2,9}
N#2 {2,2,5} N#7 {9,4,9}
N#3 {2,5,5} N#8 {10,5,6}
N#4 {1,1,10} N#9 {8,5,6}
N#5 {8,8,8} N#10 {3,4,3}

Fig -5: Key graph in the with 10 nodes
Table 3: Results: a) Number of nodes (n) b) Key Ring size
(k) c) Probability d) Maximum Hop e) Average Hop f)
fail1 g) fail2
(a) (b) (c) (d) (e) (f) (g)
10 3 1.0000 1 1.000 0.300 0.510
20 3 0.7421 2 1.258 0.150 0.277
30 4 0.9211 2 1.079 0.200 0.360
40 6 0.9247 2 1.025 0.120 0.225
50 10 0.9394 2 1.001 0.100 0.190
60 10 0.9497 2 1.000 0.010 0.019
70 20 0.9954 3 1.000 0.020 0.039
4. Combinatorial design based Key Predistribution Scheme
[9]: Combinatorial design technique can be used for key
distribution for their special property of symmetricity.
For example a BIBD (7,7,3,3,1) is type of symmetric design
which indicates, elements, blocks, each block
contains elements and each elements in blocks
and each pair of blocks has common elements. This
arrangement can be used for key distribution.
Fig -6: (a) BIBD (7,3,1) Key graph
Fig -6: (b) Incidence graph
5. Expander Graph based Key Predistribution Scheme: A
Ramanujan graph is a graph with number of nodes
and the degree of the graph k , where both
s and t are prime congruent to . Figure 7 shows a
key graph with the use of Ramanujan graph where self
loops and multiple edeges are deleted.
Fig -7: Expander graph X 5, 17
5. ANALYSIS OF THE KPS
A. Connectivity:
Figure 8 shows plot of connectivity probability that is
having a common key between any two randomly chosen
nodes in various schemes discussed above using a key
chain of size 3. As the network size increases the
probability of immediate key share decreases in every
scheme.
Fig -8: Plot of Probability Pr1 or Connectivity
B. Resilience:
It is essential to minimise the number of nodes affected on
any node compromised. The fraction of the network that
can survive is called the resilience of the network and a plot
for the same is shown in figure 9. As network size increases
the probability of nodes affected decreases in case in all the
approaches and therefore resilience of the network
increases.

Fig -9: Plot of Resilience
5. Conclusion
The paper gives an overview of key predistribution scheme
and comparison of various approaches. Combinatorial
designed based KPS is found to be highly efficient
compared the other scheme when connectivity is
concerned. Single key distribution scheme is highly storage
efficient but it has lowest resilience. Storage requirement in
pair-wise KPS is very high but it gives perfect resilience to
the network. Comparison of these method were shown in
graph.
REFERENCES
[1] Eschenauer L, Gligor V. A key‐management scheme for
distributed sensor networks. In Proceedings of the
Annual ACM Computer and Communications Security
(CCS), 2002.
[2] Chi‐Yuan Chen and Han‐Chieh Chao "A survey of key
distribution in wireless sensor networks" SECURITY
AND COMMUNICATION NETWORKS Security Comm.
Networks 2014; 7:2495–2508published online 13 July
2011 in Wiley Online Library
(wileyonlinelibrary.com). DOI: 10.1002/sec.354.
[3] ShlomoHoory, Nathan Linial, and AviWigderson.
Expander graphs and their applications. In Bulletin of
the American Mathematical Society, 43(04):439{562,
August 2006.
[4] Michelle Kendall and Keith Martin "On the Role of
Expander Graphs in Key Predistribution Schemes for
Wireless Sensor Networks"Information Security
Group, Royal Holloway,University of London, Egham,
Surrey, TW20 0EX, UK.
[5] Friedrich Wilhelm Levi. Finite Geometrical Systems:
six public lectures delivered in February, 1940, at
theUniversity of Calcutta. The University of Calcutta,
1942.
[6] Coxeter, H. S. M. "Self-Dual Configurations and Regular
Graphs." Bull. Amer. Math. Soc. 56, 413-455, 1950.
[7] Godsil, C. and Royle, G. "Incidence Graphs." §5.1 in
Algebraic Graph Theory. New York: Springer-Verlag,
pp. 78-79, 2001.
[8] Fan R. K. Chung. Spectral Graph Theory. American
Mathematical Society, California State University,
Fresno, 1994.
[9] Çamtepe SA, Yener B. Combinatorial design of key
distribution mechanisms for wireless sensor
networks. IEEE/ACM Transaction on Networking
2007; 15(2): 346–358.
[10] Blom R. An optimal class of symmetric key generation
systems. In Proceedings of Annual International
Conference on the Theory and Applications of
Cryptographic Techniques (EUROCRYPT), 1984.
[11] Du W, Deng J, Han YS, Varshney P. A pairwise key pre‐
distriubtion scheme for wireless sensor networks. In
Proceedings of the Annual ACM Computer and
Communications Security (CCS), 2003.
[12] Blundo C, Santis AD, Herzberg A, Kutten S, Vaccaro U,
Yung M. Perfectly‐secure key distribution for dynamic
conferences. In Proceedings of the 29th International
Cryptology Conference (CRYPTO), 1993.
[13] Chan H, Perrig A, Song D. Random key predistribution
schemes for sensor networks. In Proceedings of IEEE
Symposium on Security and Privacy (S&P), 2003
[14] Seyit Ahmet Camtepe, Bulent Yener, and Moti Yung.
Expander Graph Based Key Distribution Mechanisms
in Wireless Sensor Networks. In ICC 06, IEEE
International Conference on Communications, pages
2262-2267, 2006.
[15] A. Lubotzky, R. Phillips, and P. Sarnak, “Ramanujan
graphs,” Combinatorica, vol. 8, no. 3.
BIOGRAPHY
Mr. Monjul Saikia has been serving
as an Assistant Professor in the
department of Computer Science and
Engineering, NERIST (North Eastern
Regional Institute of Science and
Technology) a Deemed University
under the Govt. of India, in Arunachal
Pradesh, India since July 2007. He has completed his
Masters of Technology from the Department Computer
Science and Engineering, NERIST in the year of 2011. He
did his Bachelor of Engineering from Jorhat Engineering
College, Jorhat Assam, in 2005 in Computer Science
discipline. Currently he is pursuing PhD in the Department
of Electronics and Communication Engineering, NERIST
under the guidance of Prof. Md. Anwar Hussain. His major
research interests include Information Security,
Cryptography, Image and Video Processing, VLSI etc. He is
a member of professional societies like IEEE, CSI (India),
IEI (India) and ISTE (India).

Prof. Md. Anwar Hussain, Professor
in the Department of Electronics and
Communication Engineering, North
Eastern Regional Institute of Science
and Technology. He has done Ph.D (in
Engineering) , Optical Fiber
Commun
-cation from Jadavpur University, Kolkota in 2002 (Feb.).
His area of research includes: High data rate wireless
communication & networks, Routing & scheduling in
Multi-hop wireless networks, Key distribution in Sensor
networks, Multimedia data encryption & security, Mobile
computing security, Time-series data modelling and
prediction, Low power VLSI design, Climate change &
modelling, Networks-on-Chip.

An Analysis of Location Independent Key Predistribution Schemes for Wireless Sensor Network

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