A Survey on Detection Techniques for Cryptographic Ransomware <s> D. LOST FILES <s> Preventive and reactive security measures can only partially mitigate the damage caused by modern ransomware attacks. Indeed, the remarkable amount of illicit profit and the cyber-criminals' increasing interest in ransomware schemes suggest that a fair number of users are actually paying the ransoms. Unfortunately, pure-detection approaches (e.g., based on analysis sandboxes or pipelines) are not sufficient nowadays, because often we do not have the luxury of being able to isolate a sample to analyze, and when this happens it is already too late for several users! We believe that a forward-looking solution is to equip modern operating systems with practical self-healing capabilities against this serious threat. Towards such a vision, we propose ShieldFS, an add-on driver that makes the Windows native filesystem immune to ransomware attacks. For each running process, ShieldFS dynamically toggles a protection layer that acts as a copy-on-write mechanism, according to the outcome of its detection component. Internally, ShieldFS monitors the low-level filesystem activity to update a set of adaptive models that profile the system activity over time. Whenever one or more processes violate these models, their operations are deemed malicious and the side effects on the filesystem are transparently rolled back. We designed ShieldFS after an analysis of billions of low-level, I/O filesystem requests generated by thousands of benign applications, which we collected from clean machines in use by real users for about one month. This is the first measurement on the filesystem activity of a large set of benign applications in real working conditions. We evaluated ShieldFS in real-world working conditions on real, personal machines, against samples from state of the art ransomware families. ShieldFS was able to detect the malicious activity at runtime and transparently recover all the original files. Although the models can be tuned to fit various filesystem usage profiles, our results show that our initial tuning yields high accuracy even on unseen samples and variants. <s> BIB001 </s> A Survey on Detection Techniques for Cryptographic Ransomware <s> D. LOST FILES <s> Ransomware is a form of extortion-based attack that locks the victim’s digital resources and requests money to release them. The recent resurgence of high-profile ransomware attacks, particularly in critical sectors such as the health care industry, has highlighted the pressing need for effective defenses. While users are always advised to have a reliable backup strategy, the growing number of paying victims in recent years suggests that an endpoint defense that is able to stop and recover from ransomware’s destructive behavior is needed. <s> BIB002 </s> A Survey on Detection Techniques for Cryptographic Ransomware <s> D. LOST FILES <s> Ransomware has recently (re)emerged as a popular malware that targets a wide range of victims - from individual users to corporate ones for monetary gain. Our key observation on the existing ransomware detection mechanisms is that they fail to provide an early warning in real-time which results in irreversible encryption of a significant number of files while the post-encryption techniques (e.g., key extraction, file restoration) suffer from several limitations. Also, the existing detection mechanisms result in high false positives being unable to determine the original intent of file changes, i.e., they fail to distinguish whether a significant change in a file is due to a ransomware encryption or due to a file operation by the user herself (e.g., benign encryption or compression). To address these challenges, in this paper, we introduce a ransomware detection mechanism, RWGuard, which is able to detect crypto-ransomware in real-time on a user’s machine by (1) deploying decoy techniques, (2) carefully monitoring both the running processes and the file system for malicious activities, and (3) omitting benign file changes from being flagged through the learning of users’ encryption behavior. We evaluate our system against samples from 14 most prevalent ransomware families to date. Our experiments show that RWGuard is effective in real-time detection of ransomware with zero false negative and negligible false positive (\(\sim \)0.1%) rates while incurring an overhead of only \(\sim \)1.9%. <s> BIB003
Finally, some proposals detected and stopped ransomware action before it encrypted files, while other detectors required monitoring ransomware action (the encryption phase) to label it as dangerous. The result was a time window when some files could be lost before the ransomware was detected. The column ''lost files'' shows the data offered by the authors on this topic. Studies with a ''0'' in this column lost no files. In some cases, this was the result of detection prior to the encryption phase. In other cases, the monitoring software performed file backups BIB002 ,  ,  , BIB001 , BIB003 or intercepted the disk access system calls from any unclassified software. Once intercepted, the system calls could be redirected to a copy of the original file.