Results 101 to 110 of about 2,905 (223)

Mobile SDNs: Associating End‐User Commands with Network Flows in Android Devices

IET Communications, Volume 19, Issue 1, January/December 2025.
In our research, we combine user interface context with network flow data to improve network profiling on Android, achieving over 98.5% accuracy. We create “AppJudicator”, an Android access control app using host‐based SDN and default Android APIs, effectively addressing security concerns in enterprise networks.
Shuwen Liu, Craig A. Shue, Joseph P. Petitti, Yunsen Lei, Yu Liu   +4 more
wiley   +1 more source

AMALGAN: Image‐Based Android Malware Classification Using Generative Adversarial Network

The Journal of Engineering
The Android malware detection process requires analysing numerous files to ensure system security. Malware can also be embedded in media files and images.
Zahid Hussain Qaisar, Muhammad Faheem, Muhammad Waqar Ashraf   +2 more
doaj   +1 more source

Novel Multi-Classification Dynamic Detection Model for Android Malware Based on Improved Zebra Optimization Algorithm and LightGBM

Sensors
With the increasing popularity of Android smartphones, malware targeting the Android platform is showing explosive growth. Currently, mainstream detection methods use static analysis methods to extract features of the software and apply machine learning ...
Shuncheng Zhou, Honghui Li, Xueliang Fu, Daoqi Han, Xin He   +4 more
doaj   +1 more source

Deep Belief Networks-based framework for malware detection in Android systems

Alexandria Engineering Journal, 2018
Malware is the umbrella term that denotes attacking any system by malicious software. During the last few years, the popularity of Android smartphones led to the sneak of several malware applications into different Android markets without any difficulty.
Dina Saif, S.M. El-Gokhy, E. Sallam
doaj   +1 more source

Towards autonomous device protection using behavioural profiling and generative artificial intelligence

IET Cyber-Physical Systems: Theory &Applications, Volume 10, Issue 1, January/December 2025.
The article proposes a novel concept of autonomous device protection based on behavioural profiling by continuously monitoring internal resource usage and exploiting a large language model to distinguish between benign and malicious behaviour. Abstract Demand for autonomous protection in computing devices cannot go unnoticed, considering the rapid ...
Sandeep Gupta, Bruno Crispo
wiley   +1 more source

A Systematic Review of Sensor Vulnerabilities and Cyber‐Physical Threats in Industrial Robotic Systems

IET Cyber-Physical Systems: Theory &Applications, Volume 10, Issue 1, January/December 2025.
This paper addresses a critical gap in the literature of industrial robotics cybersecurity by presenting a comprehensive analysis of vulnerabilities in the sensing systems of industrial robots. In particular, we systematically explore how sensor performance limits, faults and biases can be exploited by attackers who can then turn these inherent ...
Abdul Kareem Shaik, Alireza Mohammadi, Hafiz Malik   +2 more
wiley   +1 more source

GNSTAM: Integrating Graph Networks With Spatial and Temporal Signature Analysis for Enhanced Android Malware Detection

IEEE Access
The sophistication of Android malware poses significant threats to user security and privacy. Traditional detection methods struggle with rapid malware evolution and benign application diversity, leading to high false positive rates and limited ...
Yogesh Kumar Sharma, Deepak Singh Tomar, R. K. Pateriya, Surendra Solanki   +3 more
doaj   +1 more source

OpCode-Level Function Call Graph Based Android Malware Classification Using Deep Learning

Sensors, 2020
Due to the openness of an Android system, many Internet of Things (IoT) devices are running the Android system and Android devices have become a common control terminal for IoT devices because of various sensors on them.
Weina Niu, Rong Cao, Xiaosong Zhang, Kangyi Ding, Kaimeng Zhang, Ting Li   +5 more
doaj   +1 more source

Malware Detection Techniques in Android [PDF]

, 2015
Mobile Phones have become an important need of today. The term mobile phone and smart phone are almost identical now-a-days. Smartphone market is booming with very high speed.
Amit Jain, Pallavi Kaushik
core  

Android Malware Detection Using Parallel Machine Learning Classifiers [PDF]

, 2014
Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices ...
Muttik, Igor, Igor Muttik, Yerima, Suleiman, Suleiman Y. Yerima, Yerima, Suleiman Y., Sezer, Sakir, Sakir Sezer, Muttik, I.   +7 more
core   +3 more sources