SATIG: AI-Enhanced Threat Detection in Drone

SATIG: AI-Enhanced Threat Detection in Drone

Yamini G1, Suhani Sharma2, Sushmitha K3, Umme Asma4, Zainab Tabha5

1Yamini G , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

2Suhani Sharma , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

3Sushmitha K , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

4Umme Asma , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

5Zainab Tabha , Computer Science & Engineering, Dayananda Sagar Academy of Technology & Management

Abstract - The SATIG (Self-Adaptive Threat Intelligence Grid) project addresses the growing concern of drone-based threats in military and defense operations. With the increasing use of autonomous drones, there is a rising risk of cyberattacks, spoofing, jamming, and coordinated intrusions that current security systems struggle to manage. The system combines computer vision, anomaly detection, and threat grading. SATIG aims to improve response speed, reduce false positives, and enhance adaptability to unknown threats. The project demonstrates how AI and cooperative decision-making can offer a scalable and intelligent approach to modern drone security.

Key Words: Drone security, real-time detection, multi-agent systems, reinforcement learning, anomaly detection, SATIG