Hybrid Multi-Level Detection and Mitigation of Clone Attacks in Mobile Wireless Sensor Network (MWSN).

Wireless sensor networks (WSNs) are often deployed in hostile environments, where an adversary can physically capture some of the sensor nodes. The adversary collects all the nodes' important credentials and subsequently replicate the nodes, which may expose the network to a number of other security attacks, and eventually compromise the entire network. This harmful attack where a single or more nodes illegitimately claims an identity as replicas is known as the node replication attack. The problem of node replication attack can be further aggravated due to the mobile nature in WSN. In this paper, we propose an extended version of multi-level replica detection technique built on Danger Theory (DT), which utilizes a hybrid approach (centralized and distributed) to shield the mobile wireless sensor networks (MWSNs) from clone attacks. The danger theory concept depends on a multi-level of detections; first stage (highlights the danger zone (DZ) by checking the abnormal behavior of mobile nodes), second stage (battery check and random number) and third stage (inform about replica to other networks). The DT method performance is highlighted through security parameters such as false negative, energy, detection time, communication overhead and delay in detection. The proposed approach also demonstrates that the hybrid DT method is capable and successful in detecting and mitigating any malicious activities initiated by the replica. Nowadays, crimes are vastly increasing and it is crucial to modify the systems accordingly. Indeed, it is understood that the communication needs to be secured by keen observation at each level of detection. The simulation results show that the proposed approach overcomes the weaknesses of the previous and existing centralized and distributed approaches and enhances the performance of MWSN in terms of communication and memory overhead

Implementation of Fuzzy Based Simulation for Clone Detection in Wireless Sensor Networks

Wireless sensor networks are usually left unattended and serve hostile environment, therefore can easily be compromised. With compromised nodes an attacker can conduct several inside and outside attacks. Node replication attack is one of them which can cause severe damage to wireless sensor network if left undetected. This paper presents fuzzy based simulation framework for detection and revocation of compromised nodes in wireless sensor network. Our proposed scheme uses PDR statistics and neighbor reports to determine the probability of a cluster being compromised. Nodes in compromised cluster are then revoked and software attestation is performed.Simulation is carried out on MATLAB 2010a and performance of proposed scheme is compared with conventional algorithms on the basis of communication and storage overhead. Simulation results show that proposed scheme require less communication and storage overhead than conventional algorithms