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- W4366446376 abstract "Abstract The Cyber threats exposure has created worldwide pressure on organizations to comply with cyber security standards and policies for protecting their digital assets. Vulnerability assessment (VA) and Penetration Testing (PT) are widely adopted Security Compliance (SC) methods to identify security gaps and anticipate security breaches, In the computer networks context and despite the use of autonomous tools and systems, security compliance remains highly repetitive and resources consuming. In this paper, we tackled the problem of security auditing systems in networks infrastructures by designing and developing an Expert-System Automated Security Compliance Framework (ESASCF) which enables industrial and open-source VA and PT tools and systems to become efficient through extracting, storing and re-using the expertise in similar scenarios or while re-testing the same assets. The ES-led Security Compliance framework observe, learn and assist human expert to eventually take over autonomously the future repeated tasks and thus enable a prioritized and fast handling for both periodic and Ad-Hoc compliance re-assessment and re-testing. The obtained results validate the performance enhancement notably by cutting the time required for an expert to 50% in the context of reassessing and 20% in re-testing which represent a significant cost-cutting in addition to the long-term impact illustrated in the knowledge extraction, generalization and re-utilization." @default.
- W4366446376 created "2023-04-22" @default.
- W4366446376 creator A5031133190 @default.
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- W4366446376 date "2023-04-19" @default.
- W4366446376 modified "2023-09-27" @default.
- W4366446376 title "ESASCF: A Framework for Expertise Extraction, Generalization and Reply for an Optimized Automation of Network Security Compliance" @default.
- W4366446376 doi "https://doi.org/10.21203/rs.3.rs-2824119/v1" @default.
- W4366446376 hasPublicationYear "2023" @default.
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