Abstract
Cybersecurity assessments are critical. Automation of a cyber risk assessment fosters real-time identification and assessment of risks, enabling rapid responses to potential threats. This paper deals with assessing cyber intelligence, learning, and automation capabilities. Specifically, several topics are introduced or discussed. They include human factors in cybersecurity and the relevance of cyber intelligent systems, machine learning (ML), and automation; the performance of ML and data preprocessing; the assessment of ML (bias, advantages, disadvantages, and metrics); and ML-based stealing attacks, intrusion detection systems, cyber threat intelligence, and cybersecurity automation. This paper presents cybersecurity assessment in healthcare (Internet of Medical Things, internal/external threats, and human factors) as a case study. Cyberthreat intelligence (CTI) represents actionable threat information that is useful for threat detection and remediation. Cybersecurity automation helps to enhance the management of vulnerabilities, security incidents, and risks. Cybersecurity assessment in healthcare helps mitigate internal and external threats. Creating a cybersecurity culture in the medical and healthcare environment is essential to robust cybersecurity.
Keywords: Artificial intelligence (AI), Automation, Cybersecurity, Cyber intelligence, Healthcare, Information, Internet of Medical Things (IoMT), Machine learning (ML).
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