Research on Malware Detection Technology for Mobile Terminals Based on API Call Sequence
Mathematics, 2023 With the development of the Internet, the types and quantities of malware have grown rapidly, and how to identify unknown malware is becoming a new challenge.
Ye Yao +6 more
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Android Malware Characterization using Metadata and Machine Learning Techniques [PDF]
, 2017 Android Malware has emerged as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features and meta-data to ...
Guzmán, Antonio +3 more
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A Comprehensive Survey on Machine Learning Techniques for Android Malware Detection
Information, 2021 Year after year, mobile malware attacks grow in both sophistication and diffusion. As the open source Android platform continues to dominate the market, malware writers consider it as their preferred target.
Vasileios Kouliaridis +1 more
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Longitudinal performance analysis of machine learning based Android malware detectors [PDF]
, 2019 This paper presents a longitudinal study of the performance of machine learning classifiers for Android malware detection. The study is undertaken using features extracted from Android applications first seen between 2012 and 2016.
Khan, Sarmadullah, Yerima, Suleiman
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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 +9 more
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A Survey and Evaluation of Android-Based Malware Evasion Techniques and Detection Frameworks
Information, 2023 Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware.
Parvez Faruki +5 more
doaj +1 more source
Evolution and Detection of Polymorphic and Metamorphic Malwares: A Survey [PDF]
, 2015 Malwares are big threat to digital world and evolving with high complexity. It can penetrate networks, steal confidential information from computers, bring down servers and can cripple infrastructures etc.
Sahay, S. K., Sharma, Ashu
core +1 more source
International Journal of Engineering & Technology, 2018 Android malware is growing in such an exponential pace which lead to the need of an efficient malware intrusion detection technique. The single approach of clustering or classification technique in malware intrusion detection yield to high negative positive alarm rate..
Zolidah Kasiran +2 more
openaire +1 more source
A Multifaceted Deep Generative Adversarial Networks Model for Mobile Malware Detection
Applied Sciences, 2022 Malware’s structural transformation to withstand the detection frameworks encourages hackers to steal the public’s confidential content. Researchers are developing a protective shield against the intrusion of malicious malware in mobile devices. The deep
Fahad Mazaed Alotaibi, Fawad
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Intensive Malware Detection Approach based on Data Mining
Journal of Applied Engineering and Technological Science, 2023 Malicious software, sometimes known as malware, is software designed to harm a computer, network, or any of the connected resources. Without the user's knowledge, malware can spread throughout their computer system. Malware is typically disseminated via
Israa Ezzat Salem, Karim Hashim Al-Saedi
doaj +1 more source