Securing AIoT Surveillance: Techniques, Challenges, and Solutions

The fusion of Artificial Intelligence (AI) and the Internet of Things (IoT) in surveillance systems, known as the Artificial Intelligence of Things (AIoT), represents a major leap in security technology, enabling advanced monitoring and real-time data processing. However, this integration also presents a new frontier of complex security challenges. This comprehensive survey examines the evolving landscape of AIoT security in surveillance, focusing on critical issues such as the integration of heterogeneous devices, vulnerabilities inherent in edge computing and distributed processing, and the increasing threat of adversarial attacks on AI algorithms. We also address regulatory and compliance challenges that arise in this domain. The survey highlights the urgent need for robust security frameworks and proposes cutting-edge solutions, including advanced encryption mechanisms, lightweight communication protocols, and specialized Intrusion Detection and Prevention Systems (IDPS). Furthermore, we emphasize the significance of ethical considerations, particularly the implementation of zero-trust architectures and the necessity for ethical oversight to maintain user trust and ensure regulatory compliance. By synthesizing the latest research and identifying future directions, this paper provides essential insights for advancing AIoT security in surveillance and offers valuable guidance for researchers and industry practitioners navigating this rapidly evolving field.