FlashGuard: Leveraging Intrinsic Flash Properties to Defend Against Encryption Ransomware
Jian Huang, Jun Xu, Xinyu Xing, Peng Liu, Moinuddin K. Qureshi
摘要
Encryption ransomware is a malicious software that stealthily encrypts user files and demands a ransom to provide access to these files. Several prior studies have developed systems to detect ransomware by monitoring the activities that typically occur during a ransomware attack. Unfortunately, by the time the ransomware is detected, some files already undergo encryption and the user is still required to pay a ransom to access those files. Furthermore, ransomware variants can obtain kernel privilege, which allows them to terminate software-based defense systems, such as anti-virus. While periodic backups have been explored as a means to mitigate ransomware, such backups incur storage overheads and are still vulnerable as ransomware can obtain kernel privilege to stop or destroy backups. Ideally, we would like to defend against ransomware without relying on software-based solutions and without incurring the storage overheads of backups. To that end, this paper proposes FlashGuard, a ransomware tolerant Solid State Drive (SSD) which has a firmware-level recovery system that allows quick and effective recovery from encryption ransomware without relying on explicit backups. FlashGuard leverages the observation that the existing SSD already performs out-of-place writes in order to mitigate the long erase latency of flash memories. Therefore, when a page is updated or deleted, the older copy of that page is anyway present in the SSD. FlashGuard slightly modifies the garbage collection mechanism of the SSD to retain the copies of the data encrypted by ransomware and ensure effective data recovery. Our experiments with 1,447 manually labeled ransomware samples show that FlashGuard can efficiently restore files encrypted by ransomware. In addition, we demonstrate that FlashGuard has a negligible impact on the performance and lifetime of the SSD.
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引用它的顶会 Paper9
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它引用的顶会 Paper2
- Cryptographic Function Detection in Obfuscated Binaries via Bit-Precise Symbolic Loop MappingDongpeng Xu, Jiang Ming, Dinghao WuS&P 2017 · 被引用 83 次
- UNVEIL: A Large-Scale, Automated Approach to Detecting RansomwareAmin Kharraz, Sajjad Arshad, Collin Mulliner, William K. Robertson 等USENIX Security 2016
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