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

作     者：N’golo Konate Tenan Yeo N’golo Konate;Tenan Yeo

作者机构：UFR Mathematiques et Informatiques Universit Felix-Houphouet Boigny Abidjan Cote dIvoire 

出 版 物：《Journal of Information Security》 (信息安全（英文）)

年 卷 期：2024年第15卷第4期

页      面：419-432页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Cloud Computing Information Security Multi-Agent System IaaS Malware Propagation 

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.