Abstract
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.
Original language | English |
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Pages (from-to) | 170-177 |
Number of pages | 8 |
Journal | International Conference on Agents and Artificial Intelligence |
Volume | 3 |
DOIs | |
Publication status | Published - 2024 |
Event | 16th International Conference on Agents and Artificial Intelligence, ICAART 2024 - Rome, Italy Duration: 24 Feb 2024 → 26 Feb 2024 |
Keywords
- Anonymization
- Network Intrusion Detection
- Review
- Trust
- Zero Trust
ASJC Scopus subject areas
- Artificial Intelligence