Hybrid Acknowledgment Punishment Scheme Based on Dempster-Shafer Theory for MANET

Abstract : In this paper, we cope with malicious nodes dropping packets to disrupt the well-functioning of mobiles ad hoc networks tasks. We propose a new hybrid acknowledgment punishment scheme based on Dempster Shafer theory, called HAPS. The proposed scheme incorporates three interactive modules. The monitor module monitors the behaviour of one-hop nodes in the data forwarding process. The reputation module assesses the direct and the indirect reputation of nodes using Dempster Shafer theory, which is a mathematical method, that can aggregate multiple recommendations shared by independent sources, while some of these recommendations might be unreliable. Since recommendations exchange between nodes consumes resources, a novel recommendation algorithm has been incorporated to deal with false dissemination attack and to minimize the recommendation traffic. The exclusion module punishes nodes regarded as malicious. The simulation results show that HAPS improves the throughput and reduces the malicious dropping ratio in comparison to existing acknowledgment scheme.
Document type :
Conference papers
Complete list of metadatas

Cited literature [24 references]  Display  Hide  Download

Contributor : Hal Ifip <>
Submitted on : Tuesday, November 6, 2018 - 5:11:20 PM
Last modification on : Thursday, November 8, 2018 - 1:46:14 PM
Long-term archiving on : Thursday, February 7, 2019 - 4:14:48 PM


 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : 2021-01-01

Please log in to resquest access to the document


Distributed under a Creative Commons Attribution 4.0 International License



Mahdi Bounouni, Louiza Bouallouche-Medjkoune. Hybrid Acknowledgment Punishment Scheme Based on Dempster-Shafer Theory for MANET. 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA), May 2018, Oran, Algeria. pp.436-447, ⟨10.1007/978-3-319-89743-1_38⟩. ⟨hal-01913881⟩



Record views