CLOUDOSCOPE: Detecting Anti-Forensic Malware using Public Cloud Environments

被引:0
|
作者
Guri, Mordechai [1 ]
机构
[1] Ben Gurion Univ Negev, Beer Sheva, Israel
来源
PROCEEDINGS OF THE 2023 EUROPEAN INTERDISCIPLINARY CYBERSECURITY CONFERENCE, EICC 2023 | 2023年
关键词
Anti-forensic; evasion; anti-VM; anti-debug; anti-sandbox; malware; APT; public cloud; detection; VIRTUALIZATION;
D O I
10.1145/3590777.3590793
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Many modern malware employs runtime anti-forensic techniques in order to evade detection. Anti-forensic tactics can be categorized as anti-virtualization (anti-VM), anti-debugging, anti-sandbox, and anti forensic-tools. The detection of such malware is challenging since they do not reveal their malicious behavior and are therefore considered benign. We present CLOUDOSCOPE, a novel architecture for detecting anti-forensic malware using the power of public cloud environments. The method we use involves running samples on bare metal machines, then running and monitoring them in multiple forensic environments deployed in the cloud. That includes virtual machines, debugging, sandboxes, and forensic environments. We identify anti-forensic behavior by comparing results in forensic and non-forensic environments. Anti-forensic malware would expose a difference between bare-metal, non-forensic, and virtualized forensic executions. Furthermore, our method enables the identification of the specific anti-forensic technique(s) used by the malware. We provide background on anti-forensic malware, present the architecture, design and implementation of CLOUDOSCOPE, and the evaluation of our system. Public cloud environments can be used to identify and detect stealthy, anti-forensic malware, as shown in our evaluation.
引用
收藏
页码:100 / 107
页数:8
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