基于系统发育的iOS手机恶意软件分类:概念验证

M. A. Husainiamer, M. Saudi, Azuan Ahmad
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引用次数: 1

摘要

在全球范围内,FinSpy和Exodus等利用iOS用户的移动恶意软件能够窃取用户的凭证信息,并影响受害者的生产力损失的案例不断增加。然而,能够遭遇iOS恶意软件攻击的解决方案并不多。因此,本文提出了一种基于系统发育概念的基于移动行为、漏洞利用的iOS移动恶意软件分类方法。实验采用杂交分析方法进行。进行了概念验证(POC),并基于POC证明了该分类方法对检测恶意软件攻击具有重要意义。未来,这一分类将成为iOS手机恶意软件检测的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification for iOS Mobile Malware Inspired by Phylogenetic: Proof of Concept
There are raising cases of mobile malwares exploiting iOS users across the world such as FinSpy and Exodus that were able to steal credential information from the victims and affect loss of victims’ productivity. Yet, not many solutions were able to encounter iOS malware attacks. Hence, this paper presents a new iOS mobile malware classification based on mobile behaviour, vulnerability exploitation inspired by phylogenetic concept. The experiment was conducted by using hybrid analysis. Proof of concept (POC) was conducted and based on the POC it indicated that this proposed classification is significant to detect the malware attacks. In future, this proposed classification will be the input for iOS mobile malware detection.
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