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2020-05-26
Fu, Yulong, Li, Guoquan, Mohammed, Atiquzzaman, Yan, Zheng, Cao, Jin, Li, Hui.  2019.  A Study and Enhancement to the Security of MANET AODV Protocol Against Black Hole Attacks. 2019 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). :1431–1436.
Mobile AdHoc Networks (MANET) can be fast implemented, and it is very popular in many specific network requirements, such as UAV (Unmanned Aerial Unit), Disaster Recovery and IoT (Internet of Things) etc. However, MANET is also vulnerable. AODV (Ad hoc On-Demand Distance Vector Routing) protocol is one type of MANET routing protocol and many attacks can be implemented to break the connections on AODV based AdHoc networks. In this article, aim of protecting the MANET security, we modeled the AODV protocol with one type of Automata and analyzed the security vulnerabilities of it; then based on the analyzing results, we proposed an enhancement to AODV protocol to against the Black Hole Attacks. We also implemented the proposed enhancement in NS3 simulator and verified the correctness, usability and efficiency.
2019-06-10
As'adi, H., Keshavarz-Haddad, A., Jamshidi, A..  2018.  A New Statistical Method for Wormhole Attack Detection in MANETs. 2018 15th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC). :1–6.

Mobile ad hoc networks (MANETs) are a set of mobile wireless nodes that can communicate without the need for an infrastructure. Features of MANETs have made them vulnerable to many security attacks including wormhole attack. In the past few years, different methods have been introduced for detecting, mitigating, and preventing wormhole attacks in MANETs. In this paper, we introduce a new decentralized scheme based on statistical metrics for detecting wormholes that employs “number of new neighbors” along with “number of neighbors” for each node as its parameters. The proposed scheme has considerably low detection delay and does not create any traffic overhead for routing protocols which include neighbor discovery mechanism. Also, it possesses reasonable processing power and memory usage. Our simulation results using NS3 simulator show that the proposed scheme performs well in terms of detection accuracy, false positive rate and mean detection delay.