Advancing Ransomware Defense Mechanisms with AI-Based Real-Time File Integrity Monitoring Systems
Keywords:
Ransomware, File Integrity Monitoring, CybersecurityAbstract
Ransomware attacks continue to be one of the most pressing cybersecurity threats, targeting both individuals and organizations worldwide. These attacks often encrypt critical files, demanding a ransom for their release, while also potentially causing significant operational and financial damage. Traditional defense mechanisms, including signature-based antivirus and heuristic methods, often fail to identify new or sophisticated variants of ransomware. To address these challenges, AI-based real-time file integrity monitoring systems offer a promising approach to enhance ransomware defense. By leveraging machine learning and deep learning algorithms, these systems can monitor file behavior, detect anomalous changes, and identify potential ransomware activities in real-time. This paper explores the application of AI in file integrity monitoring systems, focusing on its ability to detect, prevent, and mitigate ransomware attacks. It discusses various AI techniques, implementation challenges, and case studies where such systems have been successfully deployed. Furthermore, it highlights the future directions of AI-based file integrity monitoring for ransomware defense and emphasizes the need for continuous adaptation to evolving ransomware tactics.
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References
Federal Bureau of Investigation. (2020). 2020 Internet crime report. https://www.ic3.gov
Zhang, L., & Liu, D. (2021). Ransomware detection with machine learning: A comparative study. Journal of Cybersecurity, 19(4), 113-125.
S. Kumari, “Kanban-Driven Digital Transformation for Cloud-Based Platforms: Leveraging AI to Optimize Resource Allocation, Task Prioritization, and Workflow Automation”, J. of Artificial Int. Research and App., vol. 1, no. 1, pp. 568–586, Jan. 2021
Singu, Santosh Kumar. "Designing scalable data engineering pipelines using Azure and Databricks." ESP Journal of Engineering & Technology Advancements 1.2 (2021): 176-187.
Madupati, Bhanuprakash. "Blockchain in Day-to-Day Life: Transformative Applications and Implementation." Available at SSRN 5118207 (2021).
S. Kumari, “Digital Transformation Frameworks for Legacy Enterprises: Integrating AI and Cloud Computing to Revolutionize Business Models and Operational Efficiency ”, Journal of AI-Assisted Scientific Discovery, vol. 1, no. 1, pp. 186–204, Jan. 2021
Singu, Santosh Kumar. "Real-Time Data Integration: Tools, Techniques, and Best Practices." ESP Journal of Engineering & Technology Advancements 1.1 (2021): 158-172.
S. Kumari, “Kanban and AI for Efficient Digital Transformation: Optimizing Process Automation, Task Management, and Cross-Departmental Collaboration in Agile Enterprises”, Blockchain Tech. & Distributed Sys., vol. 1, no. 1, pp. 39–56, Mar. 2021
Madupati, Bhanuprakash. "Kubernetes: Advanced Deployment Strategies-* Technical Perspective." (2021).
Kumar, S., & Singh, R. (2020). The challenges of implementing AI for ransomware defense in file integrity monitoring. Journal of Information Security, 32(3), 92-105.
Wang, J., & Li, Q. (2021). Adversarial attacks and defenses in machine learning models for ransomware detection. Artificial Intelligence Review, 34(6), 137-150.
Ali, H., & Khan, M. (2020). AI-powered file integrity monitoring for ransomware defense in healthcare. Journal of Cyber Protection, 27(5), 63-72.
Zhang, H., & Liu, X. (2021). Case study: Financial institution ransomware prevention using AI-based file integrity monitoring. Journal of Financial Cybersecurity, 8(2), 115-127.
Yadav, V., & Mehta, R. (2021). Machine learning-based ransomware detection: A survey and future directions. International Journal of Artificial Intelligence, 29(4), 134-145.
Henderson, J., & Smith, L. (2022). Integrating AI with cybersecurity for ransomware detection. Journal of AI Security, 7(3), 111-124.
White, D., & Taylor, E. (2020). Developing AI systems for ransomware defense. Journal of Cyber Threat Analysis, 13(2), 45-59.
Brown, M., & Singh, A. (2020). File integrity monitoring and AI for ransomware defense: A comprehensive approach. Journal of Digital Forensics, 25(2), 50-62.
