Mobile malware attacks: Review, taxonomy & future directions
A pervasive increase in the adoption rate of smartphones with Android OS is noted in recent
years. Android's popular and attractive environment not only captured the attention of users …
years. Android's popular and attractive environment not only captured the attention of users …
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 …
[HTML][HTML] DL-Droid: Deep learning based android malware detection using real devices
The Android operating system has been the most popular for smartphones and tablets since
2012. This popularity has led to a rapid raise of Android malware in recent years. The …
2012. This popularity has led to a rapid raise of Android malware in recent years. The …
Effective and efficient hybrid android malware classification using pseudo-label stacked auto-encoder
Android has become the target of attackers because of its popularity. The detection of
Android mobile malware has become increasingly important due to its significant threat …
Android mobile malware has become increasingly important due to its significant threat …
Dynamic android malware category classification using semi-supervised deep learning
Due to the significant threat of Android mobile malware, its detection has become
increasingly important. Despite the academic and industrial attempts, devising a robust and …
increasingly important. Despite the academic and industrial attempts, devising a robust and …
MLDroid—framework for Android malware detection using machine learning techniques
A Mahindru, AL Sangal - Neural Computing and Applications, 2021 - Springer
This research paper presents MLDroid—a web-based framework—which helps to detect
malware from Android devices. Due to increase in the popularity of Android devices …
malware from Android devices. Due to increase in the popularity of Android devices …
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 …
[PDF][PDF] Iotguard: Dynamic enforcement of security and safety policy in commodity IoT.
Broadly defined as the Internet of Things (IoT), the growth of commodity devices that
integrate physical processes with digital connectivity has changed the way we live, play, and …
integrate physical processes with digital connectivity has changed the way we live, play, and …
Droidcat: Effective android malware detection and categorization via app-level profiling
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …
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 …