Digital Forensics and Incident Response (DFIR) Automation: Leveraging AI to Accelerate Breach Investigation, Evidence Collection, and Cyberattack Mitigation

Abstract

The rapid escalation of cyber threats in both frequency and sophistication has outpaced the capacity of traditional Digital Forensics and Incident Response (DFIR) practices. Conventional manual investigation methods such as log examination, evidence extraction, and threat correlation are often too time-consuming and labor-intensive to meet the demands of real-time incident management. Consequently, organizations are increasingly turning to artificial intelligence (AI) and automation to enhance the speed, accuracy, and scalability of DFIR operations. This paper explores how AI-driven models and automation frameworks can transform digital forensics and incident response, enabling faster detection, investigation, and containment of cyberattacks. It examines the integration of machine learning, natural language processing (NLP), and robotic process automation (RPA) into DFIR workflows to automate evidence collection, pattern recognition, and anomaly detection. Moreover, the study discusses how AI-enabled SOAR (Security Orchestration, Automation, and Response) platforms streamline the decision-making process by automatically correlating multi-source data and executing predefined containment actions.
The paper also highlights practical applications across enterprise and national defense contexts, showcasing how predictive forensics and adaptive response mechanisms reduce investigation time and operational fatigue. Despite these advancements, several challenges persist, including AI model bias, data imbalance, interpretability issues, and legal admissibility of AI-generated evidence. To address these concerns, the study emphasizes the need for explainable AI frameworks, standardized forensic data models, and cross-disciplinary training for DFIR professionals. Ultimately, AI and automation do not aim to replace human expertise but to augment it enhancing investigative precision, improving incident readiness, and fostering a new generation of intelligent, resilient cyber defense systems.