基于深度学习的恶意软件检测方法研究

P. Kavitha, B. Muruganantham
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引用次数: 2

摘要

作为对技术的一种倾向,互联网有了巨大的发展,这导致了对数据存储的需求。在上传或下载过程中对数据进行操纵时,数据受到不同类型恶意软件的严重感染。在即将到来的异构技术中,技术的使用将变得复杂。根据技术的有效使用,存在各种机器学习机制。在本调查中,我们对深度学习算法在感染检测中的应用进行了调查。首先,对相关内容进行了基础研究。然后,对深度学习算法和感染类别进行了概述。本调查提供了关于深度学习方法和恶意软件检测的简要报告。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study on deep learning approaches over Malware detection
As an inclination to technology there is a tremendous growth in internet which leads to a need in storage of data. While manipulating data during uploading or downloading, the data is greatly infected with different types of malware.The usage of technology will become complex in the upcoming heterogeneous technologies. In accordance with the effective usage of the technologies, various machine learning mechanisms exist. In this survey, we provide a survey on deep learning algorithms applied on detection of infection. First, the basic study of the related content is discussed. Then, an overview of deep learning algorithms and categories of infections are conferred. This survey presents a brief report on Deep learning methodologies and malware detection.
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