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A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
Unblind your apps: Predicting natural-language labels for mobile gui components by deep learning
According to the World Health Organization (WHO), it is estimated that approximately 1.3
billion people live with some forms of vision impairment globally, of whom 36 million are …
billion people live with some forms of vision impairment globally, of whom 36 million are …
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 …
A survey of deep learning on mobile devices: Applications, optimizations, challenges, and research opportunities
Deep learning (DL) has demonstrated great performance in various applications on
powerful computers and servers. Recently, with the advancement of more powerful mobile …
powerful computers and servers. Recently, with the advancement of more powerful mobile …
[HTML][HTML] DL-AMDet: Deep learning-based malware detector for android
The Android operating system, with its market share leadership and open-source nature in
smartphones, has become the primary target of malware. However, detecting malicious …
smartphones, has become the primary target of malware. However, detecting malicious …
Why an android app is classified as malware: Toward malware classification interpretation
Machine learning–(ML) based approach is considered as one of the most promising
techniques for Android malware detection and has achieved high accuracy by leveraging …
techniques for Android malware detection and has achieved high accuracy by leveraging …
Core: Automating review recommendation for code changes
Code review is a common process that is used by developers, in which a reviewer provides
useful comments or points out defects in the submitted source code changes via pull …
useful comments or points out defects in the submitted source code changes via pull …
IntDroid: Android malware detection based on API intimacy analysis
Android, the most popular mobile operating system, has attracted millions of users around
the world. Meanwhile, the number of new Android malware instances has grown …
the world. Meanwhile, the number of new Android malware instances has grown …
An empirical assessment of security risks of global android banking apps
Mobile banking apps, belonging to the most security-critical app category, render massive
and dynamic transactions susceptible to security risks. Given huge potential financial loss …
and dynamic transactions susceptible to security risks. Given huge potential financial loss …