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Filters: Author is Qin, Panke  [Clear All Filters]
2020-04-17
Chen, Guangxuan, Wu, Di, Chen, Guangxiao, Qin, Panke, Zhang, Lei, Liu, Qiang.  2019.  Research on Digital Forensics Framework for Malicious Behavior in Cloud. 2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). 1:1375—1379.

The difficult of detecting, response, tracing the malicious behavior in cloud has brought great challenges to the law enforcement in combating cybercrimes. This paper presents a malicious behavior oriented framework of detection, emergency response, traceability, and digital forensics in cloud environment. A cloud-based malicious behavior detection mechanism based on SDN is constructed, which implements full-traffic flow detection technology and malicious virtual machine detection based on memory analysis. The emergency response and traceability module can clarify the types of the malicious behavior and the impacts of the events, and locate the source of the event. The key nodes and paths of the infection topology or propagation path of the malicious behavior will be located security measure will be dispatched timely. The proposed IaaS service based forensics module realized the virtualization facility memory evidence extraction and analysis techniques, which can solve volatile data loss problems that often happened in traditional forensic methods.