Results 31 to 40 of about 31,810 (207)
DroidPortrait: Android Malware Portrait Construction Based on Multidimensional Behavior Analysis
Applied Sciences, 2020 Recently, security incidents such as sensitive data leakage and video/audio hardware control caused by Android malware have raised severe security issues that threaten Android users, so thus behavior analysis and detection research researches of ...
Xin Su +5 more
doaj +1 more source
Scientific Reports, 2023 With the rise in popularity and usage of Android operating systems, malicious applications are targeted by applying innovative ways and techniques.
Sana Aurangzeb, Muhammad Aleem
doaj +1 more source
A Method for Automatic Android Malware Detection Based on Static Analysis and Deep Learning
IEEE Access, 2022 The computers nowadays are being replaced by the smartphones for the most of the internet users around the world, and Android is getting the most of the smartphone systems’ market.
Mulhem Ibrahim +2 more
doaj +1 more source
DroidRL: Feature selection for android malware detection with reinforcement learning [PDF]
Computers & security, 2022 Due to the completely open-source nature of Android, the exploitable vulnerability of malware attacks is increasing. Machine learning, leading to a great evolution in Android malware detection in recent years, is typically applied in the classification ...
Y. Wu +6 more
semanticscholar +1 more source
TTGNet-AMD: Android malware detection based on multi-modal feature fusion [PDF]
PeerJ Computer ScienceThe application of static features for Android malware detection has been extensively studied and developed. Existing methods exhibit limitations in both the completeness and discriminability of feature representation, which affects the enhancement of ...
Jiayin Feng +5 more
doaj +2 more sources
A Dynamic DL-Driven Architecture to Combat Sophisticated Android Malware
IEEE Access, 2020 The predominant Android operating system has captured enormous attention globally not only in smart phone industry but also for varied smart devices.
Iram Bibi +5 more
doaj +1 more source
Black-box Adversarial Example Attack towards FCG Based Android Malware Detection under Incomplete Feature Information [PDF]
USENIX Security Symposium, 2023 The function call graph (FCG) based Android malware detection methods have recently attracted increasing attention due to their promising performance. However, these methods are susceptible to adversarial examples (AEs).
Heng Li +6 more
semanticscholar +1 more source
A Lightweight Multi-Source Fast Android Malware Detection Model
Applied Sciences, 2022 Most of the current malware detection methods running on Android are based on signature and cloud technologies leading to poor protection against new types of malware. Deep learning techniques take Android malware detection to a new level.
Tao Peng +6 more
doaj +1 more source
Review of Android Malware Detection Based on Deep Learning
IEEE Access, 2020 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 malware has increased dramatically.
Zhiqiang Wang, Qian Liu, Yaping Chi
doaj +1 more source
Detection and Visualization of Android Malware Behavior [PDF]
Journal of Electrical and Computer Engineering, 2016 Malware analysts still need to manually inspect malware samples that are considered suspicious by heuristic rules. They dissect software pieces and look for malware evidence in the code. The increasing number of malicious applications targeting Android devices raises the demand for analyzing them to find where the malcode is triggered when user ...
Oscar Somarriba Jarquín +4 more
openaire +3 more sources