Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory

Muhammed Ahmed, Xu Huang, Dharmendra Sharma, Li Shutao

Research output: A Conference proceeding or a Chapter in BookConference contribution

11 Citations (Scopus)

Abstract

Wireless sensor Network (WSN) is known to be vulnerable to variety of attacks due to the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or insider attacker has gained prominence and poses the most challenging attacks to WSN. Many works has been done to secure WSN from internal attacker but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure WSN need to find the internal attacker. Normally, internal attacker node behavioral pattern is different from the other neighbor good nodes in the system, but neighbor node can be attacked as well. In this paper, we use Dempster-Shafer theory (DST) of combined multiple evidence to identify the malicious or internal attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. Moreover, it gives a numerical procedure for fusing together multiple pieces of evidence from unreliable neighbor with higher degree of conflict reliability.
Original languageEnglish
Title of host publicationInternational Conference on Algorithms and Architectures for Parallel Processing
Subtitle of host publicationICA3PP 2012
EditorsYang Xiang, Ivan Stojmenovic, Bernady O Apduhan, Guojun Wang, Koji Nakano, Albert Zomaya
Place of PublicationJapan
PublisherSpringer
Pages255-263
Number of pages9
ISBN (Electronic)9783642330650
ISBN (Print)9783642330643
DOIs
Publication statusPublished - 2012
Event12th International Conference on Algorithms and Architectures for Parallel Processing ICA3PP 2012: ICA3PP 2012 - Fukuoka, Fukuoka, Japan
Duration: 4 Sep 20127 Sep 2012
http://nsclab.org/ica3pp12/

Publication series

NameLecture Notes in Computer Science - LNCS
PublisherSpringer
Volume7440
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Algorithms and Architectures for Parallel Processing ICA3PP 2012
Abbreviated titleICA3PP 2012
CountryJapan
CityFukuoka
Period4/09/127/09/12
OtherICA3PP 2012 is the 12th in this series of conferences started in 1995 that are devoted to algorithms and architectures for parallel processing. ICA3PP is now recognized as the main regular event of the world that is covering the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems. As applications of computing systems have permeated in every aspects of daily life, the power of computing system has become increasingly critical. This conference provides a forum for countries around the world to exchange ideas for improving the computation power of computing systems.
Following the traditions of the previous successful ICA3PP conferences held in Hangzhou, Brisbane, Singapore, Melbourne, Hong Kong, Beijing, Cyprus, Taipei, Busan, and Melbourne, ICA3PP 2012 will be held in Fukuoka, Japan. The objective of ICA3PP 2012 is to bring together researchers and practitioners from academia, industry and governments to advance the theories and technologies in parallel and distributed computing. ICA3PP 2012 will focus on two broad areas of parallel and distributed computing, i.e., architectures, algorithms and networks, and systems and applications. The conference of ICA3PP 2012 will be organized by Kyushu Sangyo University, Japan
Internet address

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Wireless sensor networks
Uncertainty

Cite this

Ahmed, M., Huang, X., Sharma, D., & Shutao, L. (2012). Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory. In Y. Xiang, I. Stojmenovic, B. O. Apduhan, G. Wang, K. Nakano, & A. Zomaya (Eds.), International Conference on Algorithms and Architectures for Parallel Processing: ICA3PP 2012 (pp. 255-263). (Lecture Notes in Computer Science - LNCS; Vol. 7440). Japan: Springer. https://doi.org/10.1007/978-3-642-33065-0_27
Ahmed, Muhammed ; Huang, Xu ; Sharma, Dharmendra ; Shutao, Li. / Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory. International Conference on Algorithms and Architectures for Parallel Processing: ICA3PP 2012. editor / Yang Xiang ; Ivan Stojmenovic ; Bernady O Apduhan ; Guojun Wang ; Koji Nakano ; Albert Zomaya. Japan : Springer, 2012. pp. 255-263 (Lecture Notes in Computer Science - LNCS).
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abstract = "Wireless sensor Network (WSN) is known to be vulnerable to variety of attacks due to the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or insider attacker has gained prominence and poses the most challenging attacks to WSN. Many works has been done to secure WSN from internal attacker but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure WSN need to find the internal attacker. Normally, internal attacker node behavioral pattern is different from the other neighbor good nodes in the system, but neighbor node can be attacked as well. In this paper, we use Dempster-Shafer theory (DST) of combined multiple evidence to identify the malicious or internal attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. Moreover, it gives a numerical procedure for fusing together multiple pieces of evidence from unreliable neighbor with higher degree of conflict reliability.",
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Ahmed, M, Huang, X, Sharma, D & Shutao, L 2012, Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory. in Y Xiang, I Stojmenovic, BO Apduhan, G Wang, K Nakano & A Zomaya (eds), International Conference on Algorithms and Architectures for Parallel Processing: ICA3PP 2012. Lecture Notes in Computer Science - LNCS, vol. 7440, Springer, Japan, pp. 255-263, 12th International Conference on Algorithms and Architectures for Parallel Processing ICA3PP 2012, Fukuoka, Japan, 4/09/12. https://doi.org/10.1007/978-3-642-33065-0_27

Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory. / Ahmed, Muhammed; Huang, Xu; Sharma, Dharmendra; Shutao, Li.

International Conference on Algorithms and Architectures for Parallel Processing: ICA3PP 2012. ed. / Yang Xiang; Ivan Stojmenovic; Bernady O Apduhan; Guojun Wang; Koji Nakano; Albert Zomaya. Japan : Springer, 2012. p. 255-263 (Lecture Notes in Computer Science - LNCS; Vol. 7440).

Research output: A Conference proceeding or a Chapter in BookConference contribution

TY - GEN

T1 - Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory

AU - Ahmed, Muhammed

AU - Huang, Xu

AU - Sharma, Dharmendra

AU - Shutao, Li

PY - 2012

Y1 - 2012

N2 - Wireless sensor Network (WSN) is known to be vulnerable to variety of attacks due to the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or insider attacker has gained prominence and poses the most challenging attacks to WSN. Many works has been done to secure WSN from internal attacker but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure WSN need to find the internal attacker. Normally, internal attacker node behavioral pattern is different from the other neighbor good nodes in the system, but neighbor node can be attacked as well. In this paper, we use Dempster-Shafer theory (DST) of combined multiple evidence to identify the malicious or internal attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. Moreover, it gives a numerical procedure for fusing together multiple pieces of evidence from unreliable neighbor with higher degree of conflict reliability.

AB - Wireless sensor Network (WSN) is known to be vulnerable to variety of attacks due to the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or insider attacker has gained prominence and poses the most challenging attacks to WSN. Many works has been done to secure WSN from internal attacker but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure WSN need to find the internal attacker. Normally, internal attacker node behavioral pattern is different from the other neighbor good nodes in the system, but neighbor node can be attacked as well. In this paper, we use Dempster-Shafer theory (DST) of combined multiple evidence to identify the malicious or internal attacker in WSN. This theory reflects with the uncertain event or uncertainty as well as uncertainty of the observation. Moreover, it gives a numerical procedure for fusing together multiple pieces of evidence from unreliable neighbor with higher degree of conflict reliability.

KW - Wireless Sensor Networks

U2 - 10.1007/978-3-642-33065-0_27

DO - 10.1007/978-3-642-33065-0_27

M3 - Conference contribution

SN - 9783642330643

T3 - Lecture Notes in Computer Science - LNCS

SP - 255

EP - 263

BT - International Conference on Algorithms and Architectures for Parallel Processing

A2 - Xiang, Yang

A2 - Stojmenovic, Ivan

A2 - Apduhan, Bernady O

A2 - Wang, Guojun

A2 - Nakano, Koji

A2 - Zomaya, Albert

PB - Springer

CY - Japan

ER -

Ahmed M, Huang X, Sharma D, Shutao L. Wireless Sensor Network Internal Attacker Identification with Multiple Evidence by Dempster-Shafer Theory. In Xiang Y, Stojmenovic I, Apduhan BO, Wang G, Nakano K, Zomaya A, editors, International Conference on Algorithms and Architectures for Parallel Processing: ICA3PP 2012. Japan: Springer. 2012. p. 255-263. (Lecture Notes in Computer Science - LNCS). https://doi.org/10.1007/978-3-642-33065-0_27