A novel two-stage Multi-crieteria evaluation for internal attack in WSN

Muhammad R. Ahmed, Xu Huang, Hongyan Cui, N. K. Srinath
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Abstract

Wireless sensor networks (WSNs) are an emerging technology for collecting data about the natural or built environment. They consist of low-cost and multifunctional resources and autonomous nodes comprising the appropriate sensors along with computational devices that transmit and receive data wirelessly. The nodes work independently to function on environmental conditions. Normally each node cooperates with its neighbours to wirelessly transmit their readings via a deployed network. A wireless sensor network can be used for many different applications range from a military implementation in the battlefield, an environmental monitoring, playing an function in health sector as well as emergency response of surveillance. With its nature and application scenario WSN had drawn a great attention to the increasing applications. In order to ensure its functionality especially in malicious environments, security mechanisms become essential. Internal attacks have gained prominence and pose most challenging threats to all WSNs. Althougḩ a number of works has been done to secure a WSN but internal attacks have gained little attention. The conventional cryptographic technique does not give the appropriate security to save the network from internal attack that cause by abnormally behaved legitimate nodes. In this paper, we have proposed a new approach for detecting internal attack in two stages with multi-criteria evaluation. A prior to the stage of implementation we have checked whether the targeted node is in transmission range or not then in the current stage, we will make a misbehavior judgment with Abnormal Behavior Identification Mechanism (ABIM) by using cosine similarity for abnormality. Secondly, we combined the multiple pieces of evidences made by the internal attacker or the abnormally behaved nodes evidenced by information sources and then using the Dempester-Shafer Theory (DST) to make final decision. The advantage of this method is that it does not need the knowledge about the normal or malicious node in advance.
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一种新的两阶段多准则无线传感器网络内部攻击评估方法
无线传感器网络(WSNs)是一种用于收集自然或建筑环境数据的新兴技术。它们由低成本和多功能资源和自主节点组成,这些节点包括适当的传感器以及无线传输和接收数据的计算设备。这些节点根据环境条件独立工作。通常情况下,每个节点与相邻节点合作,通过部署的网络无线传输它们的读数。无线传感器网络可用于许多不同的应用,从战场上的军事实施,环境监测,在卫生部门发挥作用以及监测的应急响应。无线传感器网络以其自身的特性和应用场景引起了越来越多的关注。为了确保其功能,特别是在恶意环境中,安全机制变得至关重要。内部攻击日益突出,对所有无线传感器网络构成最具挑战性的威胁。虽然已经做了许多工作来保护WSN,但内部攻击很少受到关注。传统的加密技术不能提供适当的安全性来保护网络免受合法节点异常行为引起的内部攻击。本文提出了一种基于多准则评估的两阶段内部攻击检测方法。在实施阶段之前,我们已经检查了目标节点是否在传输范围内,那么在当前阶段,我们将使用异常行为识别机制(ABIM)对异常使用余弦相似度进行错误行为判断。其次,我们将内部攻击者提供的多条证据或信息源证明的异常节点结合起来,然后使用Dempester-Shafer理论(DST)进行最终决策。该方法的优点是不需要事先了解正常节点或恶意节点。
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