AB  - Organizations today are facing increasing cybersecurity challenges by moving more services to the cloud and outsourcing Intrusion Detection System (IDS) network monitoring tasks to third-party analysts. Zero Trust models may mitigate these challenges by employing the philosophy of ?Never Trust, Always Verify.? However, specific anonymization approaches are required to ensure information integrity while preserving privacy. This paper reviews the existing approaches identified in the literature, compares them, and assesses the privacy-accuracy trade-offs. Plus, we have discussed future research directions and knowledge gaps.
AU  - Alalmaie, AZ
AU  - Waheed, N
AU  - Alalyan, M
AU  - Nanda, P
AU  - Jia, W
AU  - He, X
DA  - 2024/01/01
DO  - 10.5220/0012312300003636
EP  - 177
JO  - Proceedings of the 16th International Conference on Agents and Artificial Intelligence
PB  - INSTICC
PY  - 2024/01/01
SP  - 170
TI  - Zero Trust for Intrusion Detection System: A Systematic Literature Review
VL  - 3
Y1  - 2024/01/01
Y2  - 2026/05/07
ER  -