Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/138189
Title: SECURITY AND PRIVACY IN WIRELESS NETWORKING AND MOBILE CROWD SENSING
Authors: KOH JING YANG
Keywords: security and privacy, location spoofing, traffic analysis, Bayesian inference, privacy guarantees
Issue Date: 31-Jul-2017
Citation: KOH JING YANG (2017-07-31). SECURITY AND PRIVACY IN WIRELESS NETWORKING AND MOBILE CROWD SENSING. ScholarBank@NUS Repository.
Abstract: This thesis study and address: (i) the location spoofing attack in time-of-arrival (TOA)-based localization systems, (ii) the traffic analysis attack in wireless networks, and (iii) privacy-awareness in mobile crowd sensing (MCS) applications. First, we study how to detect location spoofing attacks in TOA-based localization systems and design a generalized likelihood ratio test (GLRT) to detect location spoofing anomalies in the received TOA delay measurements. Second, we study how to provide privacy for a communicating source-destination pair and design a statistical decision-making framework to select the routing path distribution that minimizes the detection probability of Bayesian maximum-a-posteriori (MAP) inference (a type of traffic analysis method). We then formulate linear programs to minimize the expected detection probability of a MAP adversary, subjected to a privacy budget constraint. We also propose the (k, e)-anonymity privacy constraint for strict privacy guarantees in wireless networks and formulate a mixed-integer linear program to minimize the expected routing cost of the (k, e)-anonymous path distribution. Finally, we study how to improve the utility (in terms of spatial coverage) of privacy-aware mobile crowd sensing applications and propose a privacy-aware Stackelberg game incentive mechanism to select the optimal set of participating mobile smartphone users.
URI: http://scholarbank.nus.edu.sg/handle/10635/138189
Appears in Collections:Ph.D Theses (Open)

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