Visible to the public Intrusion detection systems in MANETs using hybrid techniques

TitleIntrusion detection systems in MANETs using hybrid techniques
Publication TypeConference Paper
Year of Publication2017
AuthorsJoshi, V. B., Goudar, R. H.
Conference Name2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon)
Date Publishedaug
KeywordsAES, AES algorithm, AODV, AODV routing protocol, base station, compositionality, cryptographic protocols, cryptography, data authentication, EAACK, enhanced adaptive acknowledgement, hybrid cryptographic technique, IDS technique, Intrusion detection, intrusion detection system technique, MANET, Metrics, mobile ad hoc networks, pubcrawl, public key cryptography, resilience, Resiliency, Routing, Routing protocols, RSA, RSA algorithm, security, security of data, self organized wireless technologies, SHA 256 hashing technique, telecommunication security, ZRP, ZRP routing protocol
Abstract

The use of self organized wireless technologies called as Mobile Ad Hoc Networks (MANETs) has increased and these wireless devices can be deployed anywhere without any infrastructural support or without any base station, hence securing these networks and preventing from Intrusions is necessary. This paper describes a method for securing the MANETs using Hybrid cryptographic technique which uses RSA and AES algorithm along with SHA 256 Hashing technique. This hybrid cryptographic technique provides authentication to the data. To check whether there is any malicious node present, an Intrusion Detection system (IDS) technique called Enhanced Adaptive Acknowledgement (EAACK) is used, which checks for the acknowledgement packets to detect any malicious node present in the system. The routing of packets is done through two protocols AODV and ZRP and both the results are compared. The ZRP protocol when used for routing provides better performance as compared to AODV.

URLhttps://ieeexplore.ieee.org/document/8358429/
DOI10.1109/SmartTechCon.2017.8358429
Citation Keyjoshi_intrusion_2017