恶意软件检测问题:挑战与新方法

Marcus Botacin, P. De Geus, A. Grégio
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引用次数: 0

摘要

随着时间的推移,已经提出了许多检测恶意软件的解决方案,但有效和高效的恶意软件检测仍然是一个开放的问题。在这项工作中,我将介绍一些恶意软件检测的挑战和陷阱,以帮助提高系统的恶意软件检测能力。我提出了一种新的方法,以一种实用但仍然科学的方式来解决恶意软件的研究,并利用这种方法来调查四个问题:(I)需要理解上下文,以便正确检测局部威胁;(ii)开发更好的反病毒(AV)评估指标的需求;(iii)利用硬件软件协作高效实施自动驾驶的可行性,以及(iv)预测未来威胁的需求,以便更快地响应事件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Malware Detection Problem: Challenges & Novel Approaches
Many solutions to detect malware have been proposed over time, but effective and efficient malware detection still remains an open problem. In this work, I take a look at some malware detection challenges and pitfalls to contribute towards increasing system’s malware detection capabilities. I propose a new approach to tackle malware research in a practical but still scientific manner and leverage this approach to investigate four issues: (i) the need for understanding context to allow proper detection of localized threats; (ii) the need for developing better metrics for AntiVirus (AV) evaluation; (iii) the feasibility of leveraging hardware-software collaboration for efficient AV implementation, and (iv) the need for predicting future threats to allow faster incident responses.
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