Advancing cyber incident timeline analysis through retrieval-augmented generation and large language models
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 deta...
Main Authors: | Loumachi, Fatma Yasmine, Ghanem, Mohamed Chahine, Ferrag, Mohamed Amine |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI
2025
|
Subjects: | |
Online Access: | https://repository.londonmet.ac.uk/10080/7/computers-14-00067.pdf |
Similar Items
-
CyberASAP 2024: CyDRA: Risk assessment in transactions under security threats
by: Ghanem, Mohamed Chahine, et al.
Published: (2024) -
Advancing IoT and Cloud Security through LLMs, Federated Learning, and Reinforcement Learning
by: Ghanem, Mohamed Chahine
Published: (2024) -
Automation of digital crime investigation using Reinforcement Learning (RL)
by: Ghanem, Mohamed Chahine
Published: (2023) -
Keynote ALIZZ BANK cyber security by design in banking: a critical need
by: Ghanem, Mohamed Chahine
Published: (2024) -
Reinforcement learning for an efficient and effective malware investigation during cyber Incident response
by: Dunsin, Dipo, et al.
Published: (2025)