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无线传感器与执行器网络中移动传感器蠕虫的传播建模与防御

Propagation Modeling and Defending of a Mobile Sensor Worm in Wireless Sensor and Actuator Networks.

作者信息

Wang Tian, Wu Qun, Wen Sheng, Cai Yiqiao, Tian Hui, Chen Yonghong, Wang Baowei

机构信息

School of Computer Science and Technology, Huaqiao University, Xiamen 361021, China.

College of Information Technology, Deakin University, Melbourne, VIC 3125, Australia.

出版信息

Sensors (Basel). 2017 Jan 13;17(1):139. doi: 10.3390/s17010139.

DOI:10.3390/s17010139
PMID:28098748
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5298712/
Abstract

WSANs (Wireless Sensor and Actuator Networks) are derived from traditional wireless sensor networks by introducing mobile actuator elements. Previous studies indicated that mobile actuators can improve network performance in terms of data collection, energy supplementation, etc. However, according to our experimental simulations, the actuator's mobility also causes the sensor worm to spread faster if an attacker launches worm attacks on an actuator and compromises it successfully. Traditional worm propagation models and defense strategies did not consider the diffusion with a mobile worm carrier. To address this new problem, we first propose a microscopic mathematical model to describe the propagation dynamics of the sensor worm. Then, a two-step local defending strategy (LDS) with a mobile patcher (a mobile element which can distribute patches) is designed to recover the network. In LDS, all recovering operations are only taken in a restricted region to minimize the cost. Extensive experimental results demonstrate that our model estimations are rather accurate and consistent with the actual spreading scenario of the mobile sensor worm. Moreover, on average, the LDS outperforms other algorithms by approximately 50% in terms of the cost.

摘要

无线传感器与执行器网络(WSANs)是在传统无线传感器网络的基础上引入移动执行器元件而形成的。先前的研究表明,移动执行器在数据收集、能量补充等方面能够提升网络性能。然而,根据我们的实验模拟,如果攻击者对执行器发动蠕虫攻击并成功攻陷它,执行器的移动性也会导致传感器蠕虫传播得更快。传统的蠕虫传播模型和防御策略并未考虑移动蠕虫载体的扩散情况。为了解决这个新问题,我们首先提出一个微观数学模型来描述传感器蠕虫的传播动态。然后,设计了一种带有移动补丁分发器(一种可分发补丁的移动元件)的两步局部防御策略(LDS)来恢复网络。在LDS中,所有恢复操作仅在一个受限区域内进行,以尽量降低成本。大量实验结果表明,我们的模型估计相当准确,与移动传感器蠕虫的实际传播情况相符。此外,平均而言,LDS在成本方面比其他算法的表现高出约50%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/19dee431b727/sensors-17-00139-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/0f52d33fb82f/sensors-17-00139-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/1cce95de106b/sensors-17-00139-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/126ab6b9a9aa/sensors-17-00139-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/a00a5bf12bcf/sensors-17-00139-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/561009493253/sensors-17-00139-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/6be78bb0d0d9/sensors-17-00139-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/bd849c49805b/sensors-17-00139-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/ae584c6bab60/sensors-17-00139-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/be06fd15046f/sensors-17-00139-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/19dee431b727/sensors-17-00139-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/0f52d33fb82f/sensors-17-00139-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/1cce95de106b/sensors-17-00139-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/126ab6b9a9aa/sensors-17-00139-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/a00a5bf12bcf/sensors-17-00139-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/561009493253/sensors-17-00139-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/6be78bb0d0d9/sensors-17-00139-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/bd849c49805b/sensors-17-00139-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/ae584c6bab60/sensors-17-00139-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/be06fd15046f/sensors-17-00139-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d500/5298712/19dee431b727/sensors-17-00139-g010.jpg

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