Abstract
Vulnerability assessment is a critical process in identifying and mitigating potential security risks in various systems. With the increasing complexity and diversity of modern technologies, traditional vulnerability assessment methods may not be sufficient to address emerging threats effectively. In recent years, new approaches have emerged that leverage advanced techniques, including machine learning and artificial intelligence, to enhance the accuracy and efficiency of vulnerability assessment. In this review paper, we explore the latest developments in vulnerability assessment and provide a comprehensive analysis of various new approaches. We discuss the advantages and limitations of these approaches and provide insights into their practical applications.
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