Title: A twofold self-healing approach for MANET survivability reinforcement

Authors: Leila Mechtri; Fatiha Djemili Tolba; Salim Ghanemi; Damien Magoni

Addresses: Networks and Systems Laboratory (LRS), Computer Science Department, Badji Mokhtar University, P.O. 12, 23000 Annaba, Algeria ' Networks and Systems Laboratory (LRS), Computer Science Department, Badji Mokhtar University, P.O. 12, 23000 Annaba, Algeria ' Computer Science Department, Badji Mokhtar University, P.O. 12, 23000 Annaba, Algeria ' Computer Science Research Laboratory (LaBRI), University of Bordeaux, 351 cours de la Libération, 33405 Talence Cedex, France

Abstract: Distributed systems are by nature fault-prone systems. The situation becomes more complicated in the presence of intrusions that continue to grow in both number and severity, especially in open environments like MANET. In this paper, we present a twofold self-healing approach to reinforce MANET survivability. First, a fault-tolerant IDS is designed by replication of individual agents within MASID to ensure continuous supervision of the network. However, since not all intrusions are predictable, there might have been some serious effects on the network before being detected and completely removed. For that, even if the implications of intrusions could be minimised by the intrusion detection system MASID, still the need for the recovery of altered or deleted data is a vital step to ensure the correct functioning of the network. For that, a recovery-oriented approach for a self-healing MANET is also presented. It is based on the ability of MASID-R to assess the damage caused by the detected intrusions and aimed at enabling the supervised network to heal itself of those faults and damages. Simulations using ns-2 have been performed to study the feasibility and prove the optimality of the proposed approach.

Keywords: survivability; fault-tolerance; intrusion detection; self-healing; replication; recovery-oriented approach; MANET.

DOI: 10.1504/IJIEI.2017.087931

International Journal of Intelligent Engineering Informatics, 2017 Vol.5 No.4, pp.309 - 326

Received: 17 Feb 2016
Accepted: 08 Dec 2016
Published online: 13 Nov 2017 *

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