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Titlebook: Android Malware Detection using Machine Learning; Data-Driven Fingerpr ElMouatez Billah Karbab,Mourad Debbabi,Djedjiga Mo Book 2021 The Edi

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楼主: HAND
发表于 2025-3-26 21:35:40 | 显示全部楼层
Introduction,s become the dominant platform not only for mobile phones and tablets but also for Internet of Things (IoT) devices. In this context, Google has launched Android Things, an Android OS for IoT devices, where developers benefit from the mature Android stack to develop IoT apps for thin devices. In con
发表于 2025-3-27 04:03:25 | 显示全部楼层
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Fingerprinting Android Malware Packages,ng fingerprints such as MD5 and SHA1. Still, the fuzzy fingerprint change is virtually linear to the change in the binary content. In other words, smaller changes in the static content of the malware will cause a minor change in the computed fuzzy fingerprint. In the context of cybersecurity, this i
发表于 2025-3-27 11:59:58 | 显示全部楼层
Robust Android Malicious Community Fingerprinting,ection until signature generation by anti-malware vendors. The larger the window is, the more time the malicious apps are given to spread over the users’ devices. Current state-of-the-art techniques have a large analysis window due to the significant number of Android malware appearing daily. Beside
发表于 2025-3-27 17:11:13 | 显示全部楼层
Android Malware Fingerprinting Using Dynamic Analysis,ses. The state-of-the-art solutions, such as Chen et al., (Stormdroid: A streaminglized machine learning-based system for detecting android malware, in . (2016), pp. 377–388), Kharraz et al. (UNVEIL: A large-scale, automated approach to detecting ransomware, in . (2016), pp. 757–772) and Sgandurra e
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Portable Supervised Malware Fingerprinting Using Deep Learning,focuses on portable malware detection based on applying supervised machine learning on static analysis features in contrast to ., presented in Chap. ., in which we propose an unsupervised system based on static analysis features. While . provides a framework for malware clustering, aimed at market l
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Conclusion,running on smart devices are nowadays ubiquitous due to their convenience. For instance, users can presently use apps as Google Pay service to purchase products online and to make payments in retail stores. However, the growth of the mobile market apps has increased the concerns about the security o
发表于 2025-3-28 13:08:41 | 显示全部楼层
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