Taxonomy of malware analysis in the IoT

Silvia Wahballa Soliman, Mohammed A. Sobh, Ayman M. Bahaa-Eldin
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引用次数: 19

Abstract

Internet of Things (IoT) totally transformed our world on many levels and in many fields either industry, health, economy, energy saving, etc. According to Cisco by 2020 there will about 50 billion IoT connected devices and this causes many issues specially security problems. IoT devices are widely used everywhere and leads to user privacy, big data as well as in data and server management problems but malware is from the biggest challenges facing IoT devices where there are different types of malware like viruses, Trojan horses, worms, spy-ware and viruses, which can access and manipulate confidential information or cause a running problem in the system. As there are many types of malware but at the same time there are different approaches for malware analysis. Therefore there are many approaches to handle malware analysis and each approach has its pros and cons. In this paper we will discuss security issues in IoT devices and different approaches for malware analysis and build a taxonomy for malware analysis tools and methodologies from different points of view as well as the advantages and disadvantages of each approach.
物联网中恶意软件分析的分类
物联网(IoT)在工业、健康、经济、节能等多个层面和领域彻底改变了我们的世界。根据思科的数据,到2020年,将有大约500亿个物联网连接设备,这将导致许多问题,特别是安全问题。物联网设备广泛应用于任何地方,导致用户隐私,大数据以及数据和服务器管理问题,但恶意软件来自物联网设备面临的最大挑战,其中存在不同类型的恶意软件,如病毒,特洛伊木马,蠕虫,间谍软件和病毒,可以访问和操纵机密信息或导致系统运行问题。由于恶意软件的类型很多,但同时也有不同的恶意软件分析方法。因此,有许多方法来处理恶意软件分析,每种方法都有其优点和缺点。在本文中,我们将讨论物联网设备中的安全问题和恶意软件分析的不同方法,并从不同的角度构建恶意软件分析工具和方法的分类,以及每种方法的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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