Unmasking non-simultaneous sybils in mobile opportunistic networks

Abstract

Mobile opportunistic networks allow nodes to freely join and leave the network; hence they are highly susceptible to security threats. The paper proposes a method for detection and avoidance of a non-simultaneous Sybil attack in mobile opportunistic networks. In this attack, a malicious node assumes multiple, fake identities (i.e. Sybils) over a period of time to remain active in the network even after it has been detected as malicious. These Sybils may deplete the network resources or bias recommendation and voting systems. The proposed Sybil detection and avoidance methodology has been simulated using the opportunistic network simulator, ONE. The simulation results show that the proposed technique achieves a higher probability of packet delivery and reduces the average latency, overhead and the number of aborted message transmissions in networks with varying number of malicious nodes as compared to the case when no Sybil detection method is used.