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WiFi-based indoor localization is emerging as a new positioning technology. In this work, we present our efforts to find the best recommender system based on the indoor location tracks collected from the Bow Valley shopping mall for one week. The time a user spends in a shop is considered as an implicit preference and different mapping algorithms are proposed to map the time to a more realistic rating value. A new distribution error metric is proposed to examine the mapping algorithms. Eleven different recommender systems are built and evaluated in terms of accuracy and execution time. The Slope-One recommender system with a logarithmic mapping algorithm is finally selected with a score of 1.292, distribution error of 0.178 and execution time of 0.39 seconds for ten runs.

WiFi-based indoor localization is emerging as a new positioning technology. In this work, we present our efforts to find the best recommender system based on the indoor location tracks collected from the Bow Valley shopping mall for one week. The time a user spends in a shop is considered as an implicit preference and different mapping algorithms are proposed to map the time to a more realistic rating value. A new distribution error metric is proposed to examine the mapping algorithms. Eleven different recommender systems are built and evaluated in terms of accuracy and execution time. The Slope-One recommender system with a logarithmic mapping algorithm is finally selected with a score of 1.292, distribution error of 0.178 and execution time of 0.39 seconds for ten runs.

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Vehicular ad hoc networks (VANETs) have attracted much attention over the last few years. VANETs own several significant characteristics, such as the high-rate changing topology led by velocity of vehicles, time-and-location critical safety applications, and Global Positioning System (GPS) devices. In VANETs, as vehicle movement is usually restricted in just bidirectional movements along the roads and streets, geographical location information becomes very useful. In addition, many studies show that position-based routing protocol is a more promising routing strategy for VANETs; therefore security and verification of location information are necessary to be researched. In this thesis, a location verification approach, namely the Cooperative Location Verification (CLV) protocol, is proposed, aiming to prevent position-spoofing attacks on VANETs. The CLV basically uses two vehicles, a Verifier and a Cooperator, to verify the claimed position of a vehicle (Prover), according to two challenge-response procedures. Additionally, the security analysis of the CLV is presented. In order to enhance the CLV by reduce the network overhead, a reputation management system is designed. It utilizes the verification results of the CLV application and maintain every vehicle's reliability in the network. In addition, the solution to sparse networks is briefly discussed. In the simulation, the results show that the proposed CLV performs better than another location verification algorithm, namely the Secure Location Verification (SLV). And the effectiveness of the reputation management system is also demonstrated.

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