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一种使用编码算法中和基于熵测量的勒索软件检测技术的方法。

A Method for Neutralizing Entropy Measurement-Based Ransomware Detection Technologies Using Encoding Algorithms.

作者信息

Lee Jaehyuk, Lee Kyungroul

机构信息

School of Computer Software, Daegu Catholic University, Gyeongsan 38430, Korea.

出版信息

Entropy (Basel). 2022 Feb 4;24(2):239. doi: 10.3390/e24020239.

DOI:10.3390/e24020239
PMID:35205533
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8871499/
Abstract

Ransomware consists of malicious codes that restrict users from accessing their own files while demanding a ransom payment. Since the advent of ransomware, new and variant ransomwares have caused critical damage around the world, thus prompting the study of detection and prevention technologies against ransomware. Ransomware encrypts files, and encrypted files have a characteristic of increasing entropy. Due to this characteristic, a defense technology has emerged for detecting ransomware-infected files by measuring the entropy of clean and encrypted files based on a derived entropy threshold. Accordingly, attackers have applied a method in which entropy does not increase even if the files are encrypted, such that the ransomware-infected files cannot be detected through changes in entropy. Therefore, if the attacker applies a base64 encoding algorithm to the encrypted files, files infected by ransomware will have a low entropy value. This can eventually neutralize the technology for detecting files infected from ransomware based on entropy measurement. Therefore, in this paper, we propose a method to neutralize ransomware detection technologies using a more sophisticated entropy measurement method by applying various encoding algorithms including base64 and various file formats. To this end, we analyze the limitations and problems of the existing entropy measurement-based ransomware detection technologies using the encoding algorithm, and we propose a more effective neutralization method of ransomware detection technologies based on the analysis results.

摘要

勒索软件由恶意代码组成,这些代码在要求支付赎金的同时限制用户访问自己的文件。自勒索软件出现以来,新的和变种勒索软件在全球造成了严重破坏,从而促使人们对勒索软件的检测和预防技术进行研究。勒索软件会加密文件,而加密文件具有熵增加的特征。由于这一特征,一种防御技术应运而生,即通过基于导出的熵阈值测量干净文件和加密文件的熵来检测受勒索软件感染的文件。因此,攻击者采用了一种方法,即使文件被加密,熵也不会增加,这样就无法通过熵的变化来检测受勒索软件感染的文件。因此,如果攻击者对加密文件应用Base64编码算法,受勒索软件感染的文件将具有较低的熵值。这最终可能会使基于熵测量来检测受勒索软件感染文件的技术失效。因此,在本文中,我们提出了一种方法,通过应用包括Base64在内的各种编码算法和各种文件格式,使用更复杂的熵测量方法来中和勒索软件检测技术。为此,我们分析了使用编码算法的现有基于熵测量的勒索软件检测技术的局限性和问题,并根据分析结果提出了一种更有效的勒索软件检测技术中和方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/db3f8ff4cd68/entropy-24-00239-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/750c19869a79/entropy-24-00239-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/96a5d43ba5e7/entropy-24-00239-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/4b3460e97aca/entropy-24-00239-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/976e181336c4/entropy-24-00239-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/9b287d6ca62b/entropy-24-00239-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/db3f8ff4cd68/entropy-24-00239-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/750c19869a79/entropy-24-00239-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/96a5d43ba5e7/entropy-24-00239-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/4b3460e97aca/entropy-24-00239-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/976e181336c4/entropy-24-00239-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/9b287d6ca62b/entropy-24-00239-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8a2a/8871499/db3f8ff4cd68/entropy-24-00239-g006.jpg

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