论文标题
基于AI的恶意软件检测技术的最先进：评论
The State-of-the-Art in AI-Based Malware Detection Techniques: A Review
论文作者
论文摘要
近年来，人工智能技术迅速发展，彻底改变了与网络犯罪分子作斗争的方法。但是，随着网络安全领域的发展，恶意软件开发也是如此，这使得加强企业防御能力的恶意软件攻击能力是经济上的必要性。这篇综述旨在概述恶意软件检测和预防中使用的最新AI技术，从而对该领域的最新研究进行了深入的分析。研究的算法包括浅层学习，深度学习和生物启发的计算，这些计算应用于PC，Cloud，Android和IoT等各种平台。这项调查还涉及网络犯罪分子迅速采用AI，以此作为创建更先进的恶意软件并利用旨在防御它们的AI算法的一种手段。
Artificial Intelligence techniques have evolved rapidly in recent years, revolutionising the approaches used to fight against cybercriminals. But as the cyber security field has progressed, so has malware development, making it an economic imperative to strengthen businesses' defensive capability against malware attacks. This review aims to outline the state-of-the-art AI techniques used in malware detection and prevention, providing an in-depth analysis of the latest studies in this field. The algorithms investigated consist of Shallow Learning, Deep Learning and Bio-Inspired Computing, applied to a variety of platforms, such as PC, cloud, Android and IoT. This survey also touches on the rapid adoption of AI by cybercriminals as a means to create ever more advanced malware and exploit the AI algorithms designed to defend against them.
