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Efficient signature based malware detection on mobile devices

机译:在移动设备上基于签名的高效恶意软件检测

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摘要

The threat of malware on mobile devices is gaining attention recently. It is important to provide security solutions to these devices before these threats cause widespread damage. However, mobile devices have severe resource constraints in terms of memory and power. Hence, even though there are well developed techniques for malware detection on the PC domain, it requires considerable effort to adapt these techniques for mobile devices. In this paper, we outline the considerations for malware detection on mobile devices and propose a signature based malware detection method. Specifically, we detail a signature matching algorithm that is well suited for use in mobile device scanning due to its low memory requirements. Additionally, the matching algorithm is shown to have high scanning speed which makes it unobtrusive to users. Our evaluation and comparison study with the well known Clam-AV scanner shows that our solution consumes less than 50% of the memory used by Clam-AV while maintaining a fast scanning rate.
机译:移动设备上恶意软件的威胁最近受到关注。在这些威胁引起广泛破坏之前,为这些设备提供安全解决方案很重要。然而,移动设备在存储器和功率方面具有严格的资源约束。因此,即使在PC域上已经有完善的恶意软件检测技术,也需要付出大量努力才能使这些技术适用于移动设备。在本文中,我们概述了在移动设备上进行恶意软件检测的注意事项,并提出了一种基于签名的恶意软件检测方法。具体来说,我们将详细介绍一种签名匹配算法,由于其内存需求低,因此非常适合在移动设备扫描中使用。此外,该匹配算法具有很高的扫描速度,这对用户而言并不引人注目。我们对著名的Clam-AV扫描仪的评估和比较研究表明,我们的解决方案在保持快速扫描速度的同时,消耗的内存不到Clam-AV所用内存的50%。

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