[HTML][HTML] A state-of-the-art survey of malware detection approaches using data mining techniques
A Souri, R Hosseini - Human-centric Computing and Information Sciences, 2018 - Springer
Data mining techniques have been concentrated for malware detection in the recent
decade. The battle between security analyzers and malware scholars is everlasting as …
decade. The battle between security analyzers and malware scholars is everlasting as …
A systematic literature review of android malware detection using static analysis
Android malware has been in an increasing trend in recent years due to the pervasiveness
of Android operating system. Android malware is installed and run on the smartphones …
of Android operating system. Android malware is installed and run on the smartphones …
Mobile operating system (Android) vulnerability analysis using machine learning
Because of the computational processing, seamless functioning and benefits that it gives to
Android-users, cyber thieves have been drawn towards it. Conventional AMD: android …
Android-users, cyber thieves have been drawn towards it. Conventional AMD: android …
A review on the effectiveness of machine learning and deep learning algorithms for cyber security
R Geetha, T Thilagam - Archives of Computational Methods in …, 2021 - Springer
In recent years there exists a wide variety of cyber attacks with the drastic development of
the internet technology. Detection of these attacks is of more significant in today's cyber …
the internet technology. Detection of these attacks is of more significant in today's cyber …
[HTML][HTML] Detection of malware by deep learning as CNN-LSTM machine learning techniques in real time
MS Akhtar, T Feng - Symmetry, 2022 - mdpi.com
Cyber-attacks on the numerous parts of today's fast developing IoT are only going to
increase in frequency and severity. A reliable method for detecting malicious attacks such as …
increase in frequency and severity. A reliable method for detecting malicious attacks such as …
DroidEncoder: Malware detection using auto-encoder based feature extractor and machine learning algorithms
Android Malware detection became a hot topic over the last several years. Although
considerable studies have been conducted utilizing machine learning-based methods, little …
considerable studies have been conducted utilizing machine learning-based methods, little …
AMalNet: A deep learning framework based on graph convolutional networks for malware detection
X Pei, L Yu, S Tian - Computers & Security, 2020 - Elsevier
The increasing popularity of Android apps attracted widespread attention from malware
authors. Traditional malware detection systems suffer from some shortcomings; …
authors. Traditional malware detection systems suffer from some shortcomings; …
Malicious application detection in android—a systematic literature review
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …
gadgets became an essential necessity of day-to-day life. People are using new …
Constructing features for detecting android malicious applications: issues, taxonomy and directions
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
Hybrid intrusion detection system using machine learning
A Meryem, BEL Ouahidi - Network Security, 2020 - Elsevier
Recent technologies and innovations have encouraged users to adopt cloud-based
architectures. 1, 2 This has reduced IT barriers and provided new capabilities of dynamic …
architectures. 1, 2 This has reduced IT barriers and provided new capabilities of dynamic …