Wireless cameras dominate the home surveillance market, providing an additional layer of security for homeowners. Cameras are not limited to private residences; retail stores, public bathrooms, and public beaches represent only some of the possible locations where wireless cameras may be monitoring people's movements. When cameras are deployed into an environment, one would typically expect the user to disclose the presence of the camera as well as its location, which should be outside of a private area. However, adversarial camera users may withhold information and prevent others from discovering the camera, forcing others to determine if they are being recorded on their own. To uncover hidden cameras, a wireless camera detection system must be developed that will recognize the camera's network traffic characteristics. We monitor the network traffic within the immediate area using a separately developed packet sniffer, a program that observes and collects information about network packets. We analyze and classify these packets based on how well their patterns and features match those expected of a wireless camera. We used a Support Vector Machine classifier and a secondary-level of classification to reduce false positives to design and implement a system that uncovers the presence of hidden wireless cameras within an area. / Master of Science / Wireless cameras may be found almost anywhere, whether they are used to monitor city traffic and report on travel conditions or to act as home surveillance when residents are away. Regardless of their purpose, wireless cameras may observe people wherever they are, as long as a power source and Wi-Fi connection are available. While most wireless camera users install such devices for peace of mind, there are some who take advantage of cameras to record others without their permission, sometimes in compromising positions or places. Because of this, systems are needed that may detect hidden wireless cameras. We develop a system that monitors network traffic packets, specifically based on their packet lengths and direction, and determines if the properties of the packets mimic those of a wireless camera stream. A double-layered classification technique is used to uncover hidden wireless cameras and filter out non-wireless camera devices.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/100148 |
| Date | 02 October 2020 |
| Creators | Cowan, KC Kaye |
| Contributors | Computer Science, Hicks, Matthew, Gracanin, Denis, Ahiskali, Metin Burhan |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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