International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Threat Modeling and Risk Assessment in Industrial Control System Environments

Author(s) Jyothsna Devi Dontha
Country United States
Abstract The increasing reliance on Industrial Control Systems (ICS) in critical infrastructure has made these systems attractive targets for cyberattacks. To ensure the security of ICS environments, it is vital to develop robust threat modeling and risk assessment strategies. This paper explores various methodologies for identifying potential threats and vulnerabilities within ICS, analyzing their risks, and applying mitigation strategies. By integrating threat modeling techniques with risk assessment frameworks, organizations can identify and prioritize security risks, implement effective countermeasures, and ensure the continued safe operation of critical infrastructure. The paper presents a comprehensive review of the latest tools and frameworks used in threat modeling and risk assessment for ICS. It also examines how these methodologies can be integrated into the operational security lifecycle, enhancing overall risk management and decision-making processes. The study highlights the importance of real-time monitoring, predictive analytics, and continuous risk assessment in mitigating cybersecurity threats. Key findings suggest that a well-executed threat modeling approach can significantly reduce vulnerabilities, improve situational awareness, and enhance response times to cyber incidents. Additionally, the research emphasizes the need for a collaborative, multi-disciplinary approach to managing ICS security risks, involving cybersecurity professionals, engineers, and decision-makers. The research also discusses emerging trends in ICS security, including the integration of AI and machine learning for proactive threat detection and response.
Keywords Industrial Control Systems, Threat Modeling, Risk Assessment, Cybersecurity, ICS Security, Vulnerability Assessment, Risk Mitigation.
Field Engineering
Published In Volume 2, Issue 6, November-December 2020
Published On 2020-11-10
DOI https://doi.org/10.36948/ijfmr.2020.v02i06.37233
Short DOI https://doi.org/
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E-ISSN 2582-2160
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