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12 April 2021 Securing smart cities using artificial intelligence: intrusion and abnormal behavior detection system
Wissam Kaddah, Ehsan Sedgh Gooya, Marwa Elbouz, Ayman Alfalou
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Proceedings Volume 11735, Pattern Recognition and Tracking XXXII; 117350J (2021) https://doi.org/10.1117/12.2586774
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
Abstract
Cities development accelerates with galloping urbanization on the surface on the world [1,2]. They must face significant threats linked to risks of human origin, like terrorism. In this paper, we present our approach for intrusion detection composed of 3 phases. The first one consists in selecting, via a GUI interface, zones supposed to be prohibited zones in an image. The second one, based on a Neural Network method, is applied for the person detection. The third one verifies if the detected person is present in one of the prohibited zones or not. If so, an alarm goes off automatically. Real tests were performed to secure an elementary school in the city of Nice in France. The obtained results showed the efficiency of our method in terms of good detection. Other work is in progress with the aim of deeply analyzing the intrusion to detect the abnormal behavior.
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Wissam Kaddah, Ehsan Sedgh Gooya, Marwa Elbouz, and Ayman Alfalou "Securing smart cities using artificial intelligence: intrusion and abnormal behavior detection system", Proc. SPIE 11735, Pattern Recognition and Tracking XXXII, 117350J (12 April 2021); https://doi.org/10.1117/12.2586774
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KEYWORDS
Artificial intelligence
Computer networks
Computer intrusion detection
Neural networks
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