Advancing Cyber Incident Timeline Analysis Through Retrieval-Augmented Generation and Large Language Models

Abstract excerpt

Cyber timeline analysis or Forensic timeline analysis is critical in Digital Forensics and Incident Response (DFIR) investigations. It involves examining artefacts and events—particularly their timestamps and associated metadata—to detect anomalies, establish correlations, and reconstruct a detailed sequence of the incident. Traditional approaches rely on processing structured artefacts, such as logs a...

Topics

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• Algorithms
• Mutation
• Natural Language Processing
• Phenotype
• Supervised Machine Learning

Identifiers and source

Literature Corpus work

d709b5d6-a567-5486-88a0-47ce580e60ca

DOI

10.20944/preprints202412.2516.v2