Detection and Response Strategies for Advanced Persistent Threats (APTs)
Chris Gilbert, Mercy Abiola Gilbert, Maxwell Dorgbefu · International Journal of Scientific Research and Modern Technology. · 2025
This study investigates Advanced Persistent Threats (APTs), a class of cyber-attacks distinguished by their sophisticated, state-sponsored nature and long-term, stealthy operations. Unlike typical cybercriminals focused on immediate gains, APT groups meticulously plan and execute multi-stage attacks to infiltrate networks and exfiltrate sensitive data over extended periods. To address the shortcomings of conventional security measures, we developed a comprehensive framework for detecting and responding to APTs. Our approach combines a systematic literature review, integration of established frameworks (such as the Cyber Kill Chain and MITRE ATT&CK), empirical simulations, and extensive expert consultations—including valuable peer feedback—to validate our methodology. The findings reveal that APTs follow a defined, multi-step process and exploit gaps in traditional defenses, thereby underscoring the effectiveness of advanced anomaly detection, behavioral analytics, and threat intelligence integration. Based on these insights, we propose a robust incident response framework that emphasizes rapid containment and recovery. The study concludes with actionable recommendations for adopting emerging technologies like artificial intelligence, Zero Trust architectures, and enhanced cloud security solutions to fortify organizational defenses against evolving cyber threats, while also outlining directions for future research to further refine these strategies.