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An Artificial intelligence technique for prevent black hole attacks in MANET - 2014

An Artificial intelligence technique for prevent black hole attacks in MANET

Research Paper on An Artificial intelligence technique for prevent black hole attacks in MANET

Research Area:  Mobile Ad Hoc Networks

Abstract:

Mobile ad hoc networks (MANETs) can be operated in the difficult environments or emergency situations. In this type of networks, the nodes work of forwarding packets together. Routing protocols are worked based on multi-hop to discover a path from source to destination node when the direct path between them does not exist. One of the standard MANET protocols is Ad hoc on-demand distance vector protocol (AODV). AODV is attacked by many types of attacks such as black hole attack due its routing mechanism. Black hole provides highest destination sequence number and lowest hop count number to attract sourcenode and drop the packets. Most previous works were used trusted neighbor nodes for preventing black hole attack and making AODV more secure. However, these solutions suffer from high routing overhead and missing specific mechanism for providing a shortest secure path. In this paper, we propose an intelligent preventing technique for AODV to prevent black hole attacks, which is called Shortest Secure Path for AODV (SSP-AODV). This intelligent technique is integrated A* and Floyd-Warshall’s algorithms. The simulation is conducted in Network Simulator 2. The results indicate that the proposed intelligent technique outperform standard AODV in two terms; packet loss delivery and average End-to-End delay. The performance of proposed technique can significantly reduce the effect of black hole attacks.

Keywords:  
Mobile Ad hoc Networks (MANETs)
Black Hole attack
Heuristic Search
A* algorithm
Floyd-Warshall-s
Malicious node
Secure Routing

Author(s) Name:  Khalil I. Ghathwan & Abdul Razak B. Yaakub

Journal name:  

Conferrence name:  Recent Advances on Soft Computing and Data Mining

Publisher name:  Springer

DOI:  DOI: 10.1007/978-3-319-07692-8_12

Volume Information: