海报:MUSTARD -用于勒索软件检测的自适应行为分析

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security Pub Date : 2022-11-07 DOI:10.1145/3548606.3563529

D. Sanvito, G. Siracusano, Roberto González, R. Bifulco

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引用次数: 0

摘要

基于文件系统操作的行为分析是检测勒索软件最有前途的方法之一。尽管如此，跟踪所有进程的所有文件上的所有操作可能会给被监视的系统带来很大的开销。我们提出了MUSTARD，一种基于每个进程的行为动态调整监控程度的解决方案，以减少良性进程的监控资源。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Poster: MUSTARD - Adaptive Behavioral Analysis for Ransomware Detection

Behavioural analysis based on filesystem operations is one of the most promising approaches for the detection of ransomware. Nonetheless, tracking all the operations on all the files for all the processes can introduce a significant overhead on the monitored system. We present MUSTARD, a solution to dynamically adapt the degree of monitoring for each process based on their behaviour to achieve a reduction of monitoring resources for the benign processes.

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Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security

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