A METHOD FOR ENDPOINT AWARE INSPECTION IN A NETWORK SECURITY SOLUTION

Approved

1. Introduction and Relevance: The paper addresses the heightened importance of network security, particularly in the context of increased remote work due to the COVID-19 pandemic. This sets a clear and relevant foundation for the research, making the focus on improving audit decision accuracy highly pertinent.
2. Proposed Solution: The method proposed for enhancing assessment decision accuracy by using endpoint inspection within a network security plan is well-introduced. The approach of utilizing hash fingerprints from network traffic to gather endpoint awareness is innovative and practical, especially in the current cybersecurity landscape.
3. Methodology: The explanation of how the method operates at the application layer and its adaptability for different network security implementations (e.g., NGFWs, IPSs, SaaS, and SASE solutions) is detailed and demonstrates a thorough understanding of network security frameworks. The flexibility of the approach to work with lower-layer information adds value to the methodology.
4. Proof-of-Concept: The proof-of-concept case study is a strong addition, showcasing the practical application of the proposed method. The claim of achieving 100% recognition of relevant network connections when the operating system and endpoint application were present is impressive and substantiates the method's effectiveness.
5. Areas for Improvement: While the proposed method and results are compelling, the paper could benefit from further discussion on potential limitations or challenges in real-world implementation. Additionally, comparisons with existing network security methods could provide a better context for understanding the advancements made.

Overall, the paper presents a valuable contribution to network security by offering a novel method for improving audit decision accuracy, supported by a solid proof-of-concept.