A novel reinforcement learning model for post-incident malware investigations
This Research proposes a Novel Reinforcement Learning (RL) model to optimise malware forensics investigation during cyber incident response. It aims to improve forensic investigation efficiency by reducing false negatives and adapting current practices to evolving malware signatures. The proposed RL...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://repository.londonmet.ac.uk/9761/1/SNAMS%202024%20RL%20for%20Malware%20Investigation%20FINAL.pdf |