Results 41 to 50 of about 4,196 (220)
An Android Malicious Code Detection Method Based on Improved DCA Algorithm
Entropy, 2017 Recently, Android malicious code has increased dramatically and the technology of reinforcement is increasingly powerful. Due to the development of code obfuscation and polymorphic deformation technology, the current Android malicious code static ...
Chundong Wang +5 more
doaj +1 more source
SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System
IEEE Access, 2018 For the last few years, Android is known to be the most widely used operating system and this rapidly increasing popularity has attracted the malware developer's attention.
Saba Arshad +5 more
doaj +1 more source
vinayakumarr/Android-Malware-Detection v1
, 2019 Android malware detection using static and dynamic ...
Vinayakumar R
core +1 more source
Monitoring Real Android Malware [PDF]
, 2015 In the most comprehensive study on Android attacks so far (undertaken by the Android Malware Genome Project), the behaviour of more than 1, 200 malwares was analysed and categorised into common, recurring groups of attacks. Based on this work (and the corresponding actual malware files), we present an approach for specifying and identifying these (and ...
Jan-Christoph Küster +1 more
openaire +1 more source
A machine learning technique for Android malicious attacks detection based on API calls [PDF]
Decision Science LettersAndroid malware is widespread and it is considered as one of the most threatening attacks recently. The threat is targeting to damage access data or information or leaking them; in general, malicious software consists of viruses, worms, and ...
Mousa AL-Akhras +3 more
doaj +1 more source
Efficient Deep Learning Network With Multi-Streams for Android Malware Family Classification
IEEE Access, 2022 It is important to effectively detect, mitigate, and defend against Android malware attacks, because Android malware has long represented a major threat to Android app security.
Hyun-Il Kim +3 more
doaj +1 more source
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
Finding Minimum‐Cost Explanations for Predictions Made by Tree Ensembles
Software: Practice and Experience, Volume 56, Issue 6, Page 615-642, June 2026.ABSTRACT The ability to reliably explain why a machine learning model arrives at a particular prediction is crucial when used as decision support by human operators of critical systems. The provided explanations must be provably correct, and preferably without redundant information, called minimal explanations.
John Törnblom +2 more
wiley +1 more source
Generating Pattern‐Based Datasets for Cyber Attack Detection Using Machine‐Learning Techniques
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.The aim of this work is to review the state of the art in the design, generation, and labeling of attack pattern datasets for training of detection systems based on machine learning. ABSTRACT This work aims to review the state of the art in the design, generation, and labeling of attack pattern datasets for the training of detection systems based on ...
Pedro Díaz García +4 more
wiley +1 more source
Android Fragmentation in Malware Detection
Computers & Security, 2019 Abstract Differences between Android versions affect not only application developers but also make the task of securing Android harder, as it is not easy to keep track of updates. In this paper, we first systematically analyze the Android framework, which includes APIs and enforced manifest permissions to realize the inconsistency currently exists in
Long Nguyen-Vu, Jinung Ahn, Souhwan Jung
openaire +1 more source