The recent adoption of smart cameras in surveillance, smart homes and smart city facilities has cast serious questions on the issue of data protection and privacy.The standard security measures do not usually identify advanced threats and behavioural abnormalities and, consequently, one will need to consider more innovative options.This paper will suggest a combined model that will use bioinformatics tools and artificial intelligence (AI) and use them to improve the security of smart cameras.Using bioinformatics-inspired pattern recognition techniques, profile information of user and device behaviour is created and processed to identify deviations that can signal possible cyberattacks or unauthorised access.Machine learning and deep learning models are used as AI models to classify normal and abnormal activities in real time.The framework is set to handle large scale streams of video data and biometrics features and be scalable and flexible in various environments.The experimental analysis proves that the suggested solution has a tremendous positive impact on the accuracy of detection, the decrease in false alarms, and the increased resistance of smart camera systems to the changing threats.The paper reveals the opportunities of integrating bioinformatics and AI to create intelligent self-adaptive security in IoT-based surveillance systems.
| Jurnal | ТАТУ хабарлари |
|---|---|
| Nashr sanasi | 2025-10-22 |
| DOI | 10.61663/253tuitmct4 |
DOI: 10.61663/253tuitmct4 · Maqolaning asl sahifasi · PDF
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