Knowledge Empowered Deep Reinforcement Learning to Prioritize Alerts Generated by Intrusion Detection Systems

Author:

Chavali Lalitha,Saxena Paresh,Mitra Barsha

Publisher

Springer Nature Switzerland

Reference19 articles.

1. Mclean, M.: Must-know cyber attack statistics and trends. Embroker (2023) https://www.embroker.com/blog/cyber-attack-statistics/#:~:text=cyber%20attacks%20have%20been%20rated,expected%20to%20double%20by%202025

2. Mandiant 2023. m-trends (2023). https://www.mandiant.com/m-trends. Accessed 10 Aug 2023

3. Liao, H.-J., Lin, C.-H.R., Lin, Y.-C., Tung, K.-Y.: Intrusion detection system: a comprehensive review. J. Netw. Comput. Appl. 36(1), 16–24 (2013)

4. Alahmadi, B.A., Axon, L., Martinovic, I.: 99% false positives: a qualitative study of $$\{$$SOC$$\}$$ analysts’ perspectives on security alarms. In: 31st USENIX Security Symposium (USENIX Security 22), pp. 2783–2800 (2022)

5. Ulevitch, D.: Cisco 2017 annual cybersecurity report: the hidden danger of uninvestigated threats (2017). https://blogs.cisco.com/security/cisco-2017-annualcybersecurity-report-the-hidden-danger-of-uninvestigated-threats. Accessed 17 Apr 2019

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