Detecting Mobile Malware Associated With Global Pandemics

IF 1.6 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Pervasive Computing Pub Date : 2023-01-01 DOI:10.1109/mprv.2023.3321218

Alfredo J. Perez, Sherali Zeadally, David Kingsley Tan

引用次数: 0

Abstract

More than 6 billion smartphones available worldwide can enable governments and public health organizations to develop apps to manage global pandemics. However, hackers can take advantage of this opportunity to target the public in nefarious ways through malware disguised as pandemics-related apps. A recent analysis conducted during the COVID-19 pandemic showed that several variants of COVID-19 related malware were installed by the public from nontrusted sources. We propose the use of app permissions and an extra feature (the total number of permissions) to develop a static detector using machine learning (ML) models to enable the fast-detection of pandemics-related Android malware at installation time. Using a dataset of more than 2000 COVID-19 related apps and by evaluating ML models created using decision trees and Naive Bayes, our results show that pandemics-related malware apps can be detected with an accuracy above 90% using decision tree models with app permissions and the proposed feature.

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检测与全球流行病相关的移动恶意软件

全球现有的60多亿部智能手机可以使政府和公共卫生组织开发应用程序来管理全球流行病。然而，黑客可以利用这个机会，通过伪装成流行病相关应用程序的恶意软件，以邪恶的方式瞄准公众。最近在COVID-19大流行期间进行的一项分析表明，公众从不受信任的来源安装了几种与COVID-19相关的恶意软件变体。我们建议使用应用程序权限和额外的功能(权限总数)来开发一个使用机器学习(ML)模型的静态检测器，以便在安装时快速检测与流行病相关的Android恶意软件。使用超过2000个与COVID-19相关的应用程序的数据集，并通过评估使用决策树和朴素贝叶斯创建的ML模型，我们的研究结果表明，使用具有应用程序权限和提议功能的决策树模型，可以以超过90%的准确率检测到与流行病相关的恶意软件应用程序。

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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来源期刊

IEEE Pervasive Computing 工程技术-电信学

CiteScore

4.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： IEEE Pervasive Computing explores the role of computing in the physical world–as characterized by visions such as the Internet of Things and Ubiquitous Computing. Designed for researchers, practitioners, and educators, this publication acts as a catalyst for realizing the ideas described by Mark Weiser in 1988. The essence of this vision is the creation of environments saturated with sensing, computing, and wireless communication that gracefully support the needs of individuals and society. Many key building blocks for this vision are now viable commercial technologies: wearable and handheld computers, wireless networking, location sensing, Internet of Things platforms, and so on. However, the vision continues to present deep challenges for experts in areas such as hardware design, sensor networks, mobile systems, human-computer interaction, industrial design, machine learning, data science, and societal issues including privacy and ethics. Through special issues, the magazine explores applications in areas such as assisted living, automotive systems, cognitive assistance, hardware innovations, ICT4D, manufacturing, retail, smart cities, and sustainability. In addition, the magazine accepts peer-reviewed papers of wide interest under a general call, and also features regular columns on hot topics and interviews with luminaries in the field.