Abstract
The rapid advancement of technology has resulted in advanced camera capabilities coming to smaller form factors with improved energy efficiency. These improvements have led to more efficient and capable cameras on mobile devices like mobile phones, tablets, and even eyeglasses. Using these unobtrusive cameras, users can capture photographs and videos of almost any location where they have physical access. Unfortunately, the proliferation of highly compact cameras has threatened the privacy rights of individuals and even entire nations and governments. For example, governments may not want photographs or videos of sensitive installations or locations like airside operations of military bases or the inner areas of nuclear power plants to be captured for unapproved uses. In addition, solutions that obfuscate images in post-processing are subject to threats that could siphon unprocessed data. Our work proposes a Global Positioning System-based approach to restrict the ability of smart cameras to capture and store images of sensitive areas.
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References
Valente, J., Koneru, K., Cardenas, A.: Privacy, and security in internet-connected cameras. In: 2019 IEEE International Congress on Internet of Things (ICIOT), pp. 173–180 (2019). https://doi.org/10.1109/ICIOT.2019.00037
Xiong, Z., Cai, Z., Han, Q., Alrawais, A., Li, W.: ADGAN: protect your location privacy in camera data of auto-driving vehicles. IEEE Trans. Ind. Inform. 17, 6200–6210. https://doi.org/10.1109/TII.2020.3032352
Liranzo, J., Hayajneh, T.: Security and privacy issues affecting cloud-based IP camera. In: 2017 IEEE 8th Annual Ubiquitous Computing, Electronics, and Mobile Communication Conference (UEMCON), pp. 458–465 (2017). https://doi.org/10.1109/UEMCON.2017.8249043
Yu, J., Chen, H., Wu, K., Cai, Z., Cui, J.: A distributed storage system for robust, privacy-preserving surveillance cameras. In: 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS), pp. 1195–1196 (2020). https://doi.org/10.1109/ICDCS47774.2020.00189
Hassan, M., Sazonov, E.: Selective content removal for egocentric wearable camera in nutritional studies. IEEE Access 8, 198615–198623 (2020). https://doi.org/10.1109/ACCESS.2020.3030723
Shu, J.: Building intelligent mobile camera systems: visual privacy by design meets social interaction. Hong Kong University of Science and Technology (2019)
Peters, F., Hanvey, S., Veluru, S., Mady, A., Boubekeur, M., Nuseibeh, B.: Generating privacy zones in smart cities. In: 2018 IEEE International Smart Cities Conference (ISC2), pp. 1–8 (2018). https://doi.org/10.1109/ISC2.2018.8656830
Koufogiannis, F., Pappas, G.: Location-dependent privacy. In: 2016 IEEE 55th Conference on Decision and Control (CDC), pp. 7586–7591 (2016). https://doi.org/10.1109/CDC.2016.7799441
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Gopinath, S., Olmsted, A. (2023). Safeguarding National Security Interests Utilizing Location-Aware Camera Devices. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 2. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 560. Springer, Cham. https://doi.org/10.1007/978-3-031-18458-1_25
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DOI: https://doi.org/10.1007/978-3-031-18458-1_25
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