"A Sybil attack is one where an adversary assumes multiple identities with the purpose of defeating an existing reputation system. When Sybil attacks are launched in vehicular networks, an added challenge in detecting malicious nodes is mobility that makes it increasingly difficult to tie a node to the location of attacks. In this thesis, we present an innovative protocol for Sybil detection in vehicular networks. Considering that vehicular networks are cyber-physical systems integrating cyber and physical components, our technique exploits well grounded results in the physical (i.e., transportation) domain to tackle the Sybil problem in the cyber domain. Compared to existing works that rely on additional cyber hardware support, or complex cryptographic primitives for Sybil detection, the key innovation in our protocol is leverage the theory of platoon dispersion that models the physics of naturally occurring dispersion in roads. Specifically, our technique employs a certain number of roadside units that periodically collect reports from vehicles regarding their physical neighborhood as they move in roads. Leveraging from existing models of platoon dispersion, we design a protocol to detect anomalously close neighborhoods that are reflective of Sybil attacks. To the best of our knowledge, this is the first work integrating a well established theory in transportation engineering for detecting cyber space attacks in vehicular networks. The resulting protocol is naturally simple, efficient and performs very well"--Abstract, page iii.
M.S. in Computer Science
King Saud University
Missouri University of Science and Technology
vi, 22 pages
© 2013 Muhammad Ibrahim Almutaz, All rights reserved.
Thesis - Restricted Access
Vehicular ad hoc networks (Computer networks) -- Security measures
Traffic engineering -- Computer simulation
Location-based services -- Security measures
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Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu:80/record=b10158065~S5
Almutaz, Muhammad Ibrahim, "Sybil detection in vehicular networks" (2013). Masters Theses. 4480.
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