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An Agent Based Model for Ransomware Detection and Mitigation in a Cloud System

An Agent Based Model for Ransomware Detection and Mitigation in a Cloud System
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摘要 The increasing trend toward dematerialization and digitalization has prompted a surge in the adoption of IT service providers, offering cost-effective alternatives to traditional local services. Consequently, cloud services have become prevalent across various industries. While these services offer undeniable benefits, they face significant threats, particularly concerning the sensitivity of the data they handle. Many existing mathematical models struggle to accurately depict the complex scenarios of cloud systems. In response to this challenge, this paper proposes a behavioral model for ransomware propagation within such environments. In this model, each component of the environment is defined as an agent responsible for monitoring the propagation of malware. Given the distinct characteristics and criticality of these agents, the impact of malware can vary significantly. Scenario attacks are constructed based on real-world vulnerabilities documented in the Common Vulnerabilities and Exposures (CVEs) through the National Vulnerability Database. Defender actions are guided by an Intrusion Detection System (IDS) guideline. This research aims to provide a comprehensive framework for understanding and addressing ransomware threats in cloud systems. By leveraging an agent- based approach and real-world vulnerability data, our model offers valuable insights into detection and mitigation strategies for safeguarding sensitive cloud-based assets. The increasing trend toward dematerialization and digitalization has prompted a surge in the adoption of IT service providers, offering cost-effective alternatives to traditional local services. Consequently, cloud services have become prevalent across various industries. While these services offer undeniable benefits, they face significant threats, particularly concerning the sensitivity of the data they handle. Many existing mathematical models struggle to accurately depict the complex scenarios of cloud systems. In response to this challenge, this paper proposes a behavioral model for ransomware propagation within such environments. In this model, each component of the environment is defined as an agent responsible for monitoring the propagation of malware. Given the distinct characteristics and criticality of these agents, the impact of malware can vary significantly. Scenario attacks are constructed based on real-world vulnerabilities documented in the Common Vulnerabilities and Exposures (CVEs) through the National Vulnerability Database. Defender actions are guided by an Intrusion Detection System (IDS) guideline. This research aims to provide a comprehensive framework for understanding and addressing ransomware threats in cloud systems. By leveraging an agent- based approach and real-world vulnerability data, our model offers valuable insights into detection and mitigation strategies for safeguarding sensitive cloud-based assets.
作者 N’golo Konate Tenan Yeo N’golo Konate;Tenan Yeo(UFR Mathematiques et Informatiques, Universit Felix-Houphouet Boigny, Abidjan, Cote dIvoire)
出处 《Journal of Information Security》 2024年第4期419-432,共14页 信息安全(英文)
关键词 Cloud Computing Information Security Multi-Agent System IAAS Malware Propagation Cloud Computing Information Security Multi-Agent System IaaS Malware Propagation
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