A novel permission-based Android malware detection system using feature selection based on linear regression
Sign Up to like & getrecommendations! Published in 2021 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-05875-1
Abstract: With the developments in mobile and wireless technology, mobile devices have become an important part of our lives. While Android is the leading operating system in market share, it is the platform most targeted by… read more here.
Keywords: system; android malware; malware detection; selection ... See more keywords
AdDroid: Rule-Based Machine Learning Framework for Android Malware Analysis
Sign Up to like & getrecommendations! Published in 2020 at "Mobile Networks and Applications"
DOI: 10.1007/s11036-019-01248-0
Abstract: Recent years have witnessed huge growth in Android malware development. Colossal reliance on Android applications for day to day working and their massive development dictates for an automated mechanism to distinguish malicious applications from benign… read more here.
Keywords: android; android malware; based machine; machine learning ... See more keywords
Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-018-0803-6
Abstract: Android security incidents occurred frequently in recent years. To improve the accuracy and efficiency of large-scale Android malware detection, in this work, we propose a hybrid model based on deep autoencoder (DAE) and convolutional neural… read more here.
Keywords: android malware; model; deep autoencoder; cnn ... See more keywords
A Novel Dynamic Android Malware Detection System With Ensemble Learning
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2844349
Abstract: With the popularity of Android smartphones, malicious applications targeted Android platform have explosively increased. Proposing effective Android malware detection method for preventing the spread of malware has become an emerging issue. Various features extracted through… read more here.
Keywords: ensemble learning; android malware; malware detection; malware ... See more keywords
Predicting the Impact of Android Malicious Samples via Machine Learning
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DOI: 10.1109/access.2019.2914311
Abstract: Recently, Android malicious samples threaten billions of mobile end users’ security or privacy. The community researchers have designed many methods to automatically and accurately identify Android malware samples. However, the rapid increase of Android malicious… read more here.
Keywords: android malware; malicious samples; android malicious; security ... See more keywords
Android Malware Familial Classification Based on DEX File Section Features
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DOI: 10.1109/access.2020.2965646
Abstract: The rapid proliferation of Android malware is challenging the classification of the Android malware family. The traditional static method for classification is easily affected by the confusion and reinforcement, while the dynamic method is expensive… read more here.
Keywords: android malware; classification; method; dex file ... See more keywords
A Review of Android Malware Detection Approaches Based on Machine Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3006143
Abstract: Android applications are developing rapidly across the mobile ecosystem, but Android malware is also emerging in an endless stream. Many researchers have studied the problem of Android malware detection and have put forward theories and… read more here.
Keywords: android malware; android; machine learning; detection ... See more keywords
FAMD: A Fast Multifeature Android Malware Detection Framework, Design, and Implementation
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3033026
Abstract: With Android’s dominant position within the current smartphone OS, increasing number of malware applications pose a great threat to user privacy and security. Classification algorithms that use a single feature usually have weak detection performance.… read more here.
Keywords: android malware; malware detection; framework; detection ... See more keywords
Efficient Deep Learning Network With Multi-Streams for Android Malware Family Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2021.3139334
Abstract: 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. Characterizing and classifying similar malicious apps into groups plays… read more here.
Keywords: malware family; network; classification; multi streams ... See more keywords
LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
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DOI: 10.1109/access.2022.3146363
Abstract: In this study, a framework for Android malware detection based on permissions is presented. This framework uses multiple linear regression methods. Application permissions, which are one of the most critical building blocks in the security… read more here.
Keywords: linear regression; regression; android malware; detection ... See more keywords
FAM: Featuring Android Malware for Deep Learning-Based Familial Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3151357
Abstract: 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… read more here.
Keywords: malware; android malware; analysis; deep learning ... See more keywords