The DAEMON-AI project, titled "Detection and Active Elimination of Malicious anomalies through Ongoing Network, sensor, and behavioral analysis with AI," aims to revolutionize mobile cybersecurity by developing a behavior-based anomaly detection system. This system employs unsupervised machine learning to identify unknown cyber threats in real time, offering an innovative solution to the limitations of traditional signature-based approaches. The project focuses on safeguarding users from threats such as spyware, unauthorized data transmission, and encrypted traffic anomalies by leveraging lightweight, on-device machine learning models for enhanced security and privacy.

The DAEMON-AI solution will be integrated into Malloc's existing application to produce an enhanved prototype at TRL6. The project builds on this foundation to introduce advanced anomaly detection capabilities, enhancing the app's ability to identify unknown threats and provide real-time protection against spyware attacks. The objectives of DAEMON-AI include developing an energy-efficient anomaly detection system for encrypted traffic, enhancing real-time malware detection, and reducing reliance on cloud infrastructure. The proposed solutions focus on on-device functionality, ensuring low latency, high accuracy, and robust user data protection. Through iterative prototyping, rigorous testing, and dissemination activities, DAEMON-AI seeks to deliver an integrated security solution that will further strengthen Malloc’s application, addressing emerging cyber threats effectively and sustainably while setting new standards for mobile cybersecurity.