王珺,朱志伟,刘俊杰.一种针对无线传感网中黑洞攻击的检测与防御方法[J].计算机科学,2019,46(2):102-108
一种针对无线传感网中黑洞攻击的检测与防御方法
Detection and Defense Method for Blackhole Attacks in Wireless Sensor Networks
投稿时间:2018-01-09  修订日期:2018-05-21
DOI:
中文关键词:  无线传感器网络,路由层攻击,黑洞攻击
英文关键词:WSN,Routing layer attacks,Blackhole attack
基金项目:本文受国家自然科学基金(61401234),江苏省高校优势学科工程资助
作者单位
王珺 南京邮电大学宽带无线通信与传感网技术教育部重点实验室 南京210003
南京邮电大学通信与信息工程学院 南京210003 
朱志伟 南京邮电大学通信与信息工程学院 南京210003 
刘俊杰 南京邮电大学宽带无线通信与传感网技术教育部重点实验室 南京210003
南京邮电大学通信与信息工程学院 南京210003 
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中文摘要:
      无线传感器网络WSN(Wireless Sensor Networks)被广泛应用于军事、生产、医疗等各个方面,而当下的许多传感器网络都部署在恶劣、开放的环境中,存在各种各样的威胁。黑洞攻击是一种典型的路由攻击,在这种攻击中恶意节点声称自己是剩余能量多、能够一跳到达目的节点的节点或者声称自己就是目的节点,因此很多节点会把要发送的数据发给该恶意节点,而恶意节点吸引数据包后,并不将数据包转发而是丢弃,这就造成传输空洞。针对这种特性,文中提出了一种基于位置信息的诱捕检测算法BTCOLI(Blackhole Attack Detection Algorithm Based on Location Information),以实际不存在的目的节点为诱饵,找到黑洞节点,对其进行身份验证以及位置检测,从而剔除该恶意节点。同时,还提出了相应的防御方案:在网络中加入预共享对称密钥,并提供HMAC(Hash-based Message Authentication Code)消息验证机制,以防止恶意节点加入网络。最后通过搭建NS-2下的仿真平台,验证了该算法在检测率方面的优越性。
英文摘要:
      Wireless sensor networks(WSN) are widely used in military,production,medical and so on.Many sensor networks are deployed in hostile and open environments,so there exist a variety of threats.Blackhole attack is a typical route attack in WSNs.A malicious node claims that it has enough residual energy and it can reach the destination in one hop or claims itself to be the destination node.So the malicious node can attract other nodes to send data to it.But it will discard the packets without forwarding it which results in the “data hole”.This paper proposed a new location detection method with trapping method.A non-existent destination node is used as a bait to locate the blackhole nodes.By verifying the identity and position information of the nodes,the malicious nodes can be removed.At the same time,the algorithm adds the pre-shared symmetric key and HMAC(Hash-based message authentication code) message authentication mechanism to prevent malicious nodes from joining the network.The results of simulation based on NS2 platform show that the proposed algorithm is superior to other ones with higher detection ratio.
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