Virtual closed networks : A secure approach to autonomous mobile ad hoc networks. / Hurley-Smith, Darren; Wetherall, Jodie; Adekunle, Andrew.

2015 10th International Conference for Internet Technology and Secured Transactions (ICITST). IEEE, 2015. p. 391-398.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

The increasing autonomy of Mobile Ad Hoc Networks (MANETs) has enabled a great many large-scale unguided missions, such as agricultural planning, conservation and similar surveying tasks. Commercial and military institutions have expressed great interest in such ventures; raising the question of security as the application of such systems in potentially hostile environments becomes a desired function of such networks. Preventing theft, disruption or destruction of such MANETs through cyber-attacks has become a focus for many researchers as a result. Virtual Private Networks (VPNs) have been shown to enhance the security of Mobile Ad hoc Networks (MANETs), at a high cost in network resources during the setup of secure tunnels. VPNs do not normally support broadcast communication, reducing their effectiveness in high-traffic MANETs, which have many broadcast communication requirements. To support routing, broadcast updates and efficient MANET communication, a Virtual Closed Network (VCN) architecture is proposed. By supporting private, secure communication in unicast, multicast and broadcast modes, VCNs provide an efficient alternative to VPNs when securing MANETs. Comparative analysis of the set-up overheads of VCN and VPN approaches is provided between OpenVPN, IPsec, Virtual Private LAN Service (VPLS), and the proposed VCN solution: Security Using Pre-Existing Routing for MANETs (SUPERMAN).
Original languageEnglish
Title of host publication2015 10th International Conference for Internet Technology and Secured Transactions (ICITST)
PublisherIEEE
Pages391-398
Number of pages8
ISBN (Electronic)978-1-9083-2052-0
DOIs
Publication statusPublished - Dec 2015
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 34868572