Continuous Exposure Management Using AI and Threat Intelligence
Keywords:
Continuous Exposure Management, Artificial Intelligence (AI), Threat Intelligence, Cybersecurity, Vulnerability ManagementAbstract
Continuous Exposure Management (CEM) is a recent development that has become an essential part of modern cybersecurity processes, as cybercrime threats are increasingly sophisticated and severe. The world is going digital, and organizations are becoming increasingly vulnerable to security risks such as malware, ransomware, and advanced threats. CEM provides an active approach that involves continuous identification, assessment, and response to vulnerabilities across a company's IT infrastructure, rather than conventional, reactive security approaches. The deployment of Artificial Intelligence (AI) and Threat Intelligence (TI) into managed CEM is a critical concept that will result in more effective, faster vulnerability management through faster threat acquisition, better vulnerability prioritization, and faster response times. The rapidity and multiplicity of analysis patterns, along with the large amounts of data, imply that AI can help identify abnormalities and generate threat intelligence, constantly updating organizations on evolving cyber threats and giving them the power to make better decisions. This study will review AI methods in CEM, particularly their practical utility, using a case study and research results. Important findings show that AI-based solutions are highly effective at improving detection rates and, by extension, accelerating response time and, consequently, the vulnerability window, as well as lessening harm. At the end of the article, there are recommendations for prioritizing integration into cybersecurity programs to make them more resilient against cyber threats.
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