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dc.contributor.authorWang, Juan
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date.accessioned2019-03-07T19:46:51Z
dc.date.available2019-03-07T19:46:51Z
dc.identifier.urihttp://hdl.handle.net/1974/26029
dc.description.abstractProximity identification has been widely used in access control systems. These systems, in particular Passive Keyless Entry and Start systems (PKES) for high-end automobiles, allow drivers to unlock their vehicles by standing within one meter of the vehicle while carrying a legitimate key fob in their pockets. The PKES systems re¬quire zero interaction from a user since the vehicle is able to detect the presence of the key fob and verify its proximity, thereby allowing the user to have further access to the vehicle. However, due to the restricted processing capacity of the key fobs and the vulnerabilities of RFID technology, these systems may be prone to relay attacks. Some security videos show that thieves executed relay attacks to steal a luxury car in less than one minute. Previous literature findings also demonstrate that conventional PKES systems are vulnerable to attacks that exploit cryptographic techniques such as rolling code scheme and challenge-response scheme. In this thesis, we propose a Context-based Secure Keyless Entry System (CSKES) that adopts Bluetooth Low Energy (Bluetooth 4.0) wireless communication technology and utilizes a wide range of contextual information including round-trip time, RSSI (Receiving Signal Strength Indicator), GPS (Global Positioning System) coordinates, and Jaccard similarity of WiFi APs (Access Points) in order to precisely identify the close proximity of a car to its corresponding key. This multi-feature proximity identification system is highly efficient to mitigate classic relay attacks. We first evaluate each security feature individually to demonstrate their reliability, stability, and rigidity in identifying the characteristics of the environment. Then we implement the proposed system in two parts: an app on iPhone and a simulation application on the laptop. We evaluate the system performance based on three classification models with a dataset collected from normal and abnormal use cases. The results show that the proposed Context-based Secure Keyless Entry System demonstrates great efficiency in identifying physical proximity and preventing classic relay attacks.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectBluetooth Low Energyen_US
dc.subjectKeyless Entryen_US
dc.subjectproximity verificationen_US
dc.subjectvehicle securityen_US
dc.subjectrelay attacksen_US
dc.titleA Secure Keyless Entry System Based on Contextual Informationen_US
dc.typethesisen
dc.description.degreeMaster of Applied Scienceen_US
dc.contributor.supervisorZulkernine, Mohammad
dc.contributor.departmentElectrical and Computer Engineeringen_US


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