CMNTS: Catching malicious nodes with trust support in wireless sensor networks

U. Prathap, P. D. Shenoy, K. Venugopal
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引用次数: 17

Abstract

Security in wireless sensor networks is critical due to its way of open communication. In this paper we have considered suite of attacks - packet modification, packet dropping, sybil attack, packet misrouting, and bad mouthing attack, and provided a solution to detect attacks. In literature, many schemes have been proposed to mitigate such attacks but very few detect the malicious nodes effectively and also no single solution detects all attacks. In the proposed approach, each node chooses the parent node for forwarding the packet towards sink. Each node adds its identity and trust on parent as a routing path marker and encrypts only the bytes added by node in packet before forwarding to parent. Sink can identify the malicious node based on trust value and node identities marked in packet. Child node observes the parent and decides the trust on parent based on successful and unsuccessful transactions. Data transmission is divided into multiple rounds of equal time duration. Each node chooses the parent node at the beginning of a round based on its own observation on parent. Simulated the algorithm in NS-3 and performance analysis is discussed by comparing the results with other two recently proposed approaches. With the combination of trust factor and fixed path routing to detect malicious activity, simulation results show that proposed method detect malicious nodes efficiently and early, and also with low percentage of false detection.
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CMNTS:在无线传感器网络中捕捉具有信任支持的恶意节点
由于无线传感器网络采用开放的通信方式,其安全性至关重要。本文研究了数据包修改攻击、丢包攻击、sybil攻击、数据包错路由攻击和恶意攻击,并给出了一种检测攻击的解决方案。在文献中,已经提出了许多方案来减轻这种攻击,但很少能有效地检测到恶意节点,也没有单一的解决方案可以检测到所有攻击。在提出的方法中,每个节点选择父节点向sink转发数据包。每个节点在父节点上添加自己的身份和信任作为路由路径标记,并且在转发给父节点之前只对数据包中节点添加的字节进行加密。Sink可以根据信任值和报文中标记的节点身份来识别恶意节点。子节点观察父节点,根据成功和不成功的交易决定对父节点的信任。数据传输分为多轮,每轮的传输时间相等。每个节点在一轮开始时根据自己对父节点的观察选择父节点。在NS-3中对该算法进行了仿真,并与最近提出的两种算法进行了性能分析。仿真结果表明,该方法结合信任因子和固定路径路由来检测恶意活动,能够高效、早期地检测出恶意节点,且检测误报率低。
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