As the digital landscape continues to evolve, organizations face increasingly sophisticated cyber threats that challenge traditional cybersecurity measures. In response, this paper proposes a novel approach to bolstering cybersecurity posture by integrating dynamic vulnerability matching and threat intelligence. The proposed framework combines proactive identification of vulnerabilities within an organization's network with real-time threat intelligence feeds. Leveraging advanced analytics and machine learning algorithms, the system dynamically matches vulnerabilities to relevant threat intelligence, allowing for prioritized remediation efforts. This dynamic matching ensures that resources are allocated efficiently, focusing on mitigating the most imminent threats to the organization's security. Furthermore, the integration of threat intelligence enriches the vulnerability management process by providing contextual information about emerging threats, attack vectors, and adversary tactics. This contextual awareness enables organizations to anticipate and proactively defend against potential cyber attacks, thereby reducing the window of vulnerability and minimizing the impact of security breaches. Through empirical evaluation and case studies, we demonstrate the efficacy of the proposed framework in enhancing cybersecurity posture across diverse organizational environments. By empowering organizations to adaptively respond to evolving cyber threats, this approach enables them to stay ahead of adversaries and effectively safeguard their critical assets and data.
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J.F. John (2024) studied this question.
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