Results 41 to 50 of about 20,533 (244)

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, Bayan Issa, Muhammed Basheer Jasser   +2 more
doaj   +1 more source

FAM: Featuring Android Malware for Deep Learning-Based Familial Analysis

IEEE Access, 2022
To handle relentlessly emerging Android malware, deep learning has been widely adopted in the research community. Prior work proposed deep learning-based approaches that use different features of malware, and reported a high accuracy in malware detection,
Younghoon Ban, Sunjun Lee, Dokyung Song, Haehyun Cho, Jeong Hyun Yi   +4 more
doaj   +1 more source

Gauss-Mapping Black Widow Optimization With Deep Extreme Learning Machine for Android Malware Classification Model

IEEE Access, 2023
Nowadays, the malware on the Android platform is found to be increasing. With the prevalent use of code obfuscation technology, the precision of antivirus software and classical detection techniques is low.
Ghadah Aldehim, Munya A. Arasi, Majdi Khalid, Sumayh S. Aljameel, Radwa Marzouk, Heba Mohsen, Ishfaq Yaseen, Sara Saadeldeen Ibrahim   +7 more
doaj   +1 more source

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, Zhiyuan Li, Liangyi Gong, Xiuliang Mo, Hong Yang, Yi Zhao   +5 more
doaj   +1 more source

ACTS: Extracting Android App Topological Signature through Graphlet Sampling [PDF]

, 2016
Android systems are widely used in mobile & wireless distributed systems. In the near future, Android is believed to dominate the mobile distributed environment.
Al Hasan, Mohammad, Gao, Tianchong, Li, Feng, Peng, Wei, Saha, Tanay Kumar, Sisodia, Devkishen   +5 more
core   +1 more source

Trends in Android Malware Detection

Journal of Digital Forensics, Security and Law, 2013
This paper analyzes different Android malware detection techniques from several research papers, some of these techniques are novel while others bring a new perspective to the research work done in the past. The techniques are of various kinds ranging from detection using host based frameworks and static analysis of executable to feature extraction and
Kaveh Shaerpour, Ali Dehghantanha, Ramlan Mahmod   +2 more
openaire   +3 more sources

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild [PDF]

, 2018
In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild.
Chen, Kai, Diao, Wenrui, Dong, Shuaike, Li, Menghao, Li, Zhou, Liu, Jian, Liu, Xiangyu, Wang, Xiaofeng, Xu, Fenghao, Zhang, Kehuan   +9 more
core   +2 more sources

A machine learning technique for Android malicious attacks detection based on API calls [PDF]

Decision Science Letters
Android 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, Saud Alghamdi, Hani Omar, Hazzaa Alshareef   +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, Adnan Akhunzada, Jahanzaib Malik, Javed Iqbal, Arslan Musaddiq, Sungwon Kim   +5 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, Moonyoung Kang, Seong-Je Cho, Sang-Il Choi   +3 more
doaj   +1 more source