In the world of digital age people used digital electronic which is widely use in the world, people use digital lock system for their security and share their digital information everywhere. People also use their biological identity for credential or access permission, but most of the time, they share their photos and videos on social media, for which privacy get compromised. People share their detail in application verification and sometimes the application isn’t verifiable, so it is also lack of security. By using Intrusion Detection System (IDS), it will overcome this problem with the help of this if any intrusion occurred using deepfake, it will detect and alarm notification system. The proposed system implementation will be an automated AI-powered Intrusion Detection System (IDS) with integrated deepfake detection (Pang et al. in IEEE Trans Circuits Syst Video Technol 33:3663–3676, Aug. 2023). The system aims to monitor biometric authentication for suspicious or abnormal activities and to enhance the security of biometric authentication systems. It will be developed with a Python-based GUI and AI model to monitor biometric authentication processes for any abnormal activities. Also, the objective is to determine a range of security challenges, including replay adversarial incidents on facial recognition, and deepfake attempts. By utilizing machine learning algorithms, it will analyze biometric data in real time, automatically detecting anomalies and responding by blocking unauthorized access (S. Kumar and K. Kolhe, “Implementation of QOS in SDN and Distributed Networks for mitigation of DDOS based attacks using Machine Learning,” 2024 IEEE International Conference on Blockchain and Distributed Systems Security (ICBDS), Pune, India, 2024, pp. 1–6, https://doi.org/10.1109/ICBDS61829.2024.10837482 .). This proactive approach is expected to significantly improve the overall security and integrity of the authentication process.