The Open UniversitySkip to content

A Packet Traversal Time per Hop based Adaptive Wormhole Detection Algorithm for MANETs

Karlsson, Jonny; Dooley, Laurence S. and Pulkkis, Goran (2016). A Packet Traversal Time per Hop based Adaptive Wormhole Detection Algorithm for MANETs. In: International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2016), 22-24 Sep 2016, Split, Croatia.

Full text available as:
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (978kB) | Preview
Google Scholar: Look up in Google Scholar


Routing security challenges significantly impact the wide-scale adoption of mobile ad hoc networks (MANET), with wormholes constituting an especially severe threat. Wormhole detection algorithms like traversal time and hop count analysis (TTHCA) and modified transmission time-based mechanism (M-TTM) combine effective detection with low traffic overheads. TTHCA measures packet traversal time (PTT) per route hop count (HC), while M-TTM compares an expected round trip time (RTT) with a measured RTT. However, using only fixed thresholds for the permissible PTT/HC and measured RTT deviations respectively, both algorithms are compromised so participation mode (PM), out-of-band (O-B) wormholes are inadequately detected in MANETs with large radio range fluctuations. This paper presents an extended variant of the TTHCA algorithm called traversal time per hop analysis (TTpHA) that dynamically adapts the PTT per hop threshold to prevailing MANET conditions and nodes’ radio coverage. Experimental results confirm TTpHA provides superior PM O-B detection performance compared to TTHCA and M-TTM, with commensurately low false positive rates and traffic overheads.

Item Type: Conference or Workshop Item
Copyright Holders: IEEE
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 46872
Depositing User: Laurence Dooley
Date Deposited: 15 Aug 2016 11:16
Last Modified: 25 May 2019 20:12
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU