Detecting android malware leveraging text semantics of network flows

S Wang, Q Yan, Z Chen, B Yang… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
The emergence of malicious apps poses a serious threat to the Android platform. Most types
of mobile malware rely on network interface to coordinate operations, steal users' private …

A mobile malware detection method using behavior features in network traffic

S Wang, Z Chen, Q Yan, B Yang, L Peng… - Journal of Network and …, 2019 - Elsevier
Android has become the most popular mobile platform due to its openness and flexibility.
Meanwhile, it has also become the main target of massive mobile malware. This …

Droidclassifier: Efficient adaptive mining of application-layer header for classifying android malware

Z Li, L Sun, Q Yan, W Srisa-an, Z Chen - Security and Privacy in …, 2017 - Springer
A recent report has shown that there are more than 5,000 malicious applications created for
Android devices each day. This creates a need for researchers to develop effective and …

Android malware identification based on traffic analysis

R Chen, Y Li, W Fang - … conference on artificial intelligence and security, 2019 - Springer
As numerous new techniques for Android malware attacks have growingly emerged and
evolved, Android malware identification is extremely crucial to prevent mobile applications …

Android malware detection and classification based on network traffic using deep learning

M Gohari, S Hashemi, L Abdi - 2021 7th International …, 2021 - ieeexplore.ieee.org
Users of smartphones in the world has grown significantly, and attacks against these
devices have increased. Many protection techniques for android malware detection have …

An efficient Android malware detection system based on method-level behavioral semantic analysis

H Zhang, S Luo, Y Zhang, L Pan - IEEE Access, 2019 - ieeexplore.ieee.org
According to the recent report, 12 000 new Android malware samples will be generated
every day. Efficient identification of evolving malware is an urgent challenge. Traditional …

TFDroid: Android malware detection by topics and sensitive data flows using machine learning techniques

S Lou, S Cheng, J Huang… - 2019 IEEE 2Nd …, 2019 - ieeexplore.ieee.org
With explosive growth of Android malware and due to the severity of its damages to smart
phone users, efficient Android malware detection methods are urgently needed. As is known …

Effective detection of android malware based on the usage of data flow APIs and machine learning

S Wu, P Wang, X Li, Y Zhang - Information and software technology, 2016 - Elsevier
Context. Android has been ranked as the top smartphone platform nowadays. Studies show
that Android malware have increased dramatically and that personal privacy theft has …

Minimizing network traffic features for android mobile malware detection

A Arora, SK Peddoju - Proceedings of the 18th international conference …, 2017 - dl.acm.org
Smartphones have emerged as one of the dominant computing platforms in today's era
where Android has been the first choice for users as well as app developers due to its open …

Android malware detection using complex-flows

F Shen, J Del Vecchio, A Mohaisen… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper proposes a new technique to detect mobile malware based on information flow
analysis. Our approach examines the structure of information flows to identify patterns of …