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dc.contributor.advisorFang, Song
dc.contributor.advisorLan, Chao
dc.contributor.advisorAnindya, Maiti
dc.contributor.authorHe, Yan
dc.date.accessioned2022-12-15T15:55:24Z
dc.date.available2022-12-15T15:55:24Z
dc.date.issued2022-12
dc.identifier.urihttps://hdl.handle.net/11244/336940
dc.description.abstractHouseholders have widely used IoT security systems with the development of smart home applications. Wireless security cameras are integral components of IoT security systems used by many private homes. These cameras commonly employ motion sensors to identify something occurring in their fields of vision before recording and notifying the property owner of the activity. In this thesis, we discover that the motion-sensing action can disclose the camera's location through a novel wireless camera localization technique we call MotionCompass. In short, a user who aims to avoid surveillance can find a hidden camera by creating motion stimuli and sniffing wireless traffic for a response to that stimuli. With the motion trajectories within the motion detection zone, the user can then compute the camera's exact location. We develop an Android app to implement MotionCompass. Our extensive experiments using the developed app and 18 popular wireless security cameras demonstrate that MotionCompass can attain a mean localization error of around 5 cm in less than 140 seconds for cameras with one motion sensor. This localization technique builds upon existing work that detects the existence of hidden cameras to pinpoint their exact location and area of surveillance.en_US
dc.languageen_USen_US
dc.subjectComputer Science.en_US
dc.subjectInformation Science.en_US
dc.subjectMathematics.en_US
dc.titleSecuring Smart Home Iot Applications Via Wireless Traffic Analysisen_US
dc.date.manuscript2022-12
dc.thesis.degreeMaster of Scienceen_US
ou.groupGallogly College of Engineering::School of Computer Scienceen_US
shareok.orcid0000-0002-8311-7030en_US


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