Detecting blackhole attacks in Disruption-Tolerant Networks through packet exchange recording

Authors:
Yanzhi Ren;Mooi Choo Chuah;Jie Yang;Yingying Chen
Affiliations:
Dept. of ECE, Stevens Institute of Technology Castle Point on Hudson, Hoboken, NJ 07030;Dept. of CSE, Lehigh University Castle Point on Hudson, Hoboken, NJ 07030 Bethlehem, PA 18015;Dept. of ECE, Stevens Institute of Technology Castle Point on Hudson, Hoboken, NJ 07030;Dept. of ECE, Stevens Institute of Technology Castle Point on Hudson, Hoboken, NJ 07030
Venue:
WOWMOM '10 Proceedings of the 2010 IEEE International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)
Year:
2010

Citing 0
Cited 5

Towards a reputation-based routing protocol to contrast blackholes in a delay tolerant network

Ad Hoc Networks
Reference based approach to mitigate blackhole attacks in delay tolerant networks

Proceedings of the 8h ACM symposium on QoS and security for wireless and mobile networks
CRISP: collusion-resistant incentive-compatible routing and forwarding in opportunistic networks

Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
A trust-based framework for data forwarding in opportunistic networks

Ad Hoc Networks
Secure Multi-copy Routing in Compromised Delay Tolerant Networks

Wireless Personal Communications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Disruption Tolerant Networks (DTNs) are especially useful in providing mission critical services such as in emergency networks or battlefield scenarios. However, DTNs are vulnerable to insider attacks, in which the legitimate nodes are compromised and the adversary nodes launch blackhole attacks by dropping packets in the networks. The traditional approaches of securing routing protocols can not address such insider attacks in DTNs. In this paper, we propose a method to secure the history records of packet delivery information at each contact so that other nodes can detect insider attacks by analyzing these packet delivery records. We evaluated our approach through extensive simulations using both Random Way Point and Zebranet mobility models. Our results show that our method can detect insider attacks efficiently with high detection rate and low false positive rate.