|
|
The Inhibition and Clearup of the Mobile Worm in Wireless Sensor Networks |
WANG Tian① WU Qun① WEN Sheng② CAI Yiqiao① TIAN Hui① CHEN Yonghong① |
①(College of Computer Science & Technology, Huaqiao University, Xiamen 361021, China)
②(Institute of Information Technology, Deakin University, Melbourne VIC3125, Australia) |
|
|
Abstract The network performance of WSNs (Wireless Sensor Networks) can be improved significantly by injecting mobile elements. However, the infection process of worm will be greatly accelerated once the mobile element has been captured and become the new infection source. To cope with this new threat, this paper first proposes the infection model for the networks with the mobile worm and designs a heuristic algorithm to identify the boundary of infected area. High risk nodes near the boundary can be found and switched to sleeping states to block the further spreading of the worm. Second, an algorithm with directed-diffusion based anti-worm is designed to repair those infected sensors. Theoretical analysis and experimental results show that the proposed methods can achieve better worm cleaning effect with low cost, which can be applied to energy-limited wireless sensor networks.
|
Received: 25 November 2015
Published: 12 June 2016
|
|
Fund: The National Natural Science Foundation of China (61572206, 61202468, 61305085, 61370007, U1536115), The Project Supported by The Natural Science Foundation of Fujian Province, China (2014J01240), The Project Supported by Graduate Student Research and Innovation Ability Cultivation Plan Funded Projects of Huaqiao University (1400214020) |
Corresponding Authors:
WANG Tian
E-mail: cs_tianwang@163.com
|
|
|
|
[1] |
MISHRA B K and KESHRI N. Mathematical model on the transmission of worms in wireless sensor networks[J]. Applied Mathematical Modeling, 2013, 37(6): 4103-4111. doi: 10.1016/j.apm.2012.09.025.
|
[2] |
BUTUN I, MORGERA S D, and SANKAR R. A survey of intrusion detection systems in wireless sensor networks[J]. Communications Surveys & Tutorials, 2014, 16(1): 266-282. doi: 10.1109/SURV.2013.050113.00191.
|
[3] |
MISHRA B K and TYAGI I. Defending against malicious threats in wireless Sensor network: A mathematical model[J]. International Journal of Information Technology and Computer Science, 2014, 6(3): 12-19. doi: 10.5815/ijitcs. 2014.03.02.
|
[4] |
WANG T, PENG Z, CHEN Y, et al. Continuous tracking for mobile targets with mobility nodes in WSNs[C]. 2014 International Conference on Smart Computing (SMARTCOMP), Hong Kong, 2014: 261-268. doi: 10.1109/ SMARTCOMP.2014.7043867.
|
[5] |
DI FRANCESCO M, DAS S K, and ANASTASI G. Data collection in wireless sensor networks with mobile elements: A survey[J]. ACM Transactions on Sensor Networks, 2011, 8(1): 7-38. doi: 10.1145/1993042.1993049.
|
[6] |
PENG Z, WANG T, BHUIYAN M Z A, et al. Dependable cascading target tracking in heterogeneous mobile camera sensor networks[C]. Algorithms and Architectures for Parallel Processing, Springer International Publishing, Zhangjiajie, 2015: 531-540. doi: 10.1007/978-3-319-27161-3_48.
|
[7] |
WANG T, PENG Z, LIANG J, et al. Detecting targets based on a realistic detection and decision model in wireless sensor networks[C]. Wireless Algorithms, Systems, and Applications, Springer International Publishing, Qufu, China, 2015: 836-844. doi: 10.1007/978-3-319-21837-3_82.
|
[8] |
WEN S, ZHOU W, ZHANG J, et al. Modeling propagation dynamics of social network worms[J]. IEEE Transactions on Parallel and Distributed Systems, 2013, 24(8): 1633-1643. doi: 10.1109/TPDS.2012.250.
|
[9] |
ZHOU H Y, LUO D Y, GAO Y, et al. Modeling of node energy consumption for wireless sensor networks[J]. Wireless Sensor Network, 2011, 3(1): 18-23. doi: 10.4236/wsn. 2011.31003.
|
[10] |
SHEN S, LI H, HAN R, et al. Differential game-based strategies for preventing malware propagation in wireless sensor networks[J]. IEEE Transactions on Information Forensics and Security, 2014, 9(11): 1962-1973. doi: 10.1109/TIFS.2014.2359333.
|
[11] |
ZHAO T, ZHANG G, and ZHANG L. An overview of mobile devices security issues and countermeasures[C]. 2014 International Conference on Wireless Communication and Sensor Network (WCSN), Wuhan, 2014: 439-443. doi: 10.1109/wcsn.2014.95.
|
[12] |
CASTANEDA F, SEZER E C, and XU J. Worm vs. worm: preliminary study of an active counter-attack mechanism[C]. Proceedings of the 2004 ACM workshop on Rapid malcode, New York, USA, 2004: 83-93. doi: 10.1145/1029618.1029631.
|
[13] |
YANG Y, ZHU S, and CAO G. Improving sensor network immunity under worm attacks: a software diversity approach[C]. Proceedings of the 9th ACM International Symposium on Mobile Ad Hoc Networking and Computing, New York, USA, 2008: 149-158. doi: 10.1145/1374618. 1374640.
|
|
|
|