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The evolution of android malware and android analysis techniques
With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …
amounts of sensitive information. Sophisticated mobile malware, particularly Android …
Review of android malware detection based on deep learning
Z Wang, Q Liu, Y Chi - Ieee Access, 2020 - ieeexplore.ieee.org
At present, smartphones running the Android operating system have occupied the leading
market share. However, due to the Android operating system's open-source nature, Android …
market share. However, due to the Android operating system's open-source nature, Android …
Deep ground truth analysis of current android malware
To build effective malware analysis techniques and to evaluate new detection tools, up-to-
date datasets reflecting the current Android malware landscape are essential. For such …
date datasets reflecting the current Android malware landscape are essential. For such …
Amandroid: A precise and general inter-component data flow analysis framework for security vetting of android apps
We present a new approach to static analysis for security vetting of Android apps and a
general framework called Amandroid. Amandroid determines points-to information for all …
general framework called Amandroid. Amandroid determines points-to information for all …
[PDF][PDF] ContexloT: Towards providing contextual integrity to appified IoT platforms.
The Internet-of-Things (IoT) has quickly evolved to a new appified era where third-party
developers can write apps for IoT platforms using programming frameworks. Like other …
developers can write apps for IoT platforms using programming frameworks. Like other …
Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach
The evolution of mobile malware poses a serious threat to smartphone security. Today,
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …
A performance-sensitive malware detection system using deep learning on mobile devices
Currently, Android malware detection is mostly performed on server side against the
increasing number of malware. Powerful computing resource provides more exhaustive …
increasing number of malware. Powerful computing resource provides more exhaustive …
Lightweight, obfuscation-resilient detection and family identification of android malware
The number of malicious Android apps is increasing rapidly. Android malware can damage
or alter other files or settings, install additional applications, and so on. To determine such …
or alter other files or settings, install additional applications, and so on. To determine such …
End-to-end malware detection for android IoT devices using deep learning
Z Ren, H Wu, Q Ning, I Hussain, B Chen - Ad Hoc Networks, 2020 - Elsevier
Abstract The Internet of Things (IoT) has grown rapidly in recent years and has become one
of the most active areas in the global market. As an open source platform with a large …
of the most active areas in the global market. As an open source platform with a large …
CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs
Various studies have empirically shown that the majority of Java and Android applications
misuse cryptographic libraries, causing devastating breaches of data security. It is crucial to …
misuse cryptographic libraries, causing devastating breaches of data security. It is crucial to …