Android平台基于虚拟机的恶意软件安全防护

Anthony Avella, Syed Rizvi, Andrew Gibson, Marcus Ryan, Ryan P. Strimple, Ian Menovich
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引用次数: 0

摘要

本文着眼于Android手机被Android恶意软件攻击的不同方式,以及恶意软件防护和检测的不同发展。与手机恶意软件的斗争是一项重要的工作,因为今天大多数人都拥有手机,并在手机上存储有价值的个人信息。手机被恶意软件攻击的方式有很多,因此有很多不同的方法来检测和防御这些攻击。一些专家建议采用分散的数据方法,而另一些专家则认为反恶意软件硬件是解决方案。有许多不同的反恶意软件硬件设备,它们都以不同的方式工作,并在不同的级别检测恶意软件。然而,目前还没有完全可靠的恶意软件检测方案。令人担忧的是,没有通用的解决方案来防止恶意软件,也没有办法每次都完全检测到恶意软件。在这项研究中,我们主要关注Android恶意软件,特别是在b谷歌Play Store应用程序中发现的恶意软件。解决这个问题的方法之一是使用虚拟机并在其上编译恶意软件检测程序。为了支持我们基于VM的恶意软件检测方案,我们开发了一种算法来提供实现级细节。通过多个案例研究表明了我们提出的方案的实用性。
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VM based Malware Security Protection on Android Platform
This paper looks at the different ways in which Android phones can be attacked by android malware, and the different developments in malware protection and detection. The fight against mobile malware is an important one as most people today own cell phones and store valuable personal information on their phones. There are many ways in which a phone can be attacked by malware, and therefore there are many different methods to detect and defend against these attacks. Some experts suggest a decentralized data approach, while others suggest anti-malware hardware is the solution. There are many different Anti-malware hardware devices that all work in different ways and detect malware at different levels. However, there are no full-proof malware detection schemes. It is alarming that there is no common solution to protecting against malware and no way to completely detect malware every time. In this research, we focus on Android malware, specifically malware found on apps from the Google Play Store. One of the ways one would solve this problem is by using virtual machines and compiling malware detection programs on them. To support our VM based malware detection scheme, we develop an algorithm to provide implementation-level details. The practicality of our proposed scheme is shown using multiple case studies.
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