HEMD: a highly efficient random forest-based malware detection framework for Android
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computing and Applications"
DOI: 10.1007/s00521-017-2914-y
Abstract: Mobile phones are rapidly becoming the most widespread and popular form of communication; thus, they are also the most important attack target of malware. The amount of malware in mobile phones is increasing exponentially and… read more here.
Keywords: malware detection; detection; proposed method; hemd highly ... See more keywords
Malware visualization and detection using DenseNets
Sign Up to like & getrecommendations! Published in 2021 at "Personal and Ubiquitous Computing"
DOI: 10.1007/s00779-021-01581-w
Abstract: Rapid advancement in the sophistication of malware has posed a serious impact on the device connected over the Internet. Malware writing is driven by economic benefits; thus, an alarming increase in malware variants is witnessed.… read more here.
Keywords: visualization detection; detection using; malware visualization; using densenets ... See more keywords
Improvement of malware detection and classification using API call sequence alignment and visualization
Sign Up to like & getrecommendations! Published in 2017 at "Cluster Computing"
DOI: 10.1007/s10586-017-1110-2
Abstract: Conventional malware detection technologies have the limitation to detect malware because recent malware uses a variety of the avoidance techniques such as obfuscation, packing, anti-virtualization, anti-emulation, encapsulation technology in order to evade the detection of… read more here.
Keywords: malware detection; detection; api call; detection classification ... See more keywords
Crypto-Preserving Investigation Framework for Deep Learning Based Malware Attack Detection for Network Forensics
Sign Up to like & getrecommendations! Published in 2021 at "Wireless Personal Communications"
DOI: 10.1007/s11277-021-09026-6
Abstract: The exponential growth in technology observed over the past decade has introduced newer ways to exploit network and cyber-physical system-related vulnerabilities. Cybercriminals perform malware attacks by exploiting vulnerabilities to cause damage to a network or… read more here.
Keywords: attack; network; deep learning; evidence ... See more keywords
Feature Selection for Malware Detection on the Android Platform Based on Differences of IDF Values
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Computer Science and Technology"
DOI: 10.1007/s11390-020-9323-x
Abstract: Android is the mobile operating system most frequently targeted by malware in the smartphone ecosystem, with a market share significantly higher than its competitors and a much larger total number of applications. Detection of malware… read more here.
Keywords: malware detection; android platform; malware; feature selection ... See more keywords
Android malware detection method based on bytecode image
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-020-02196-4
Abstract: Traditional machine learning based malware detection methods often use decompiling techniques or dynamic monitoring techniques to extract the feature representation of malware. This procedure is time consuming and strongly depends on the skills of experts.… read more here.
Keywords: malware detection; detection; detection method; method based ... See more keywords
On Malfunction, Mechanisms and Malware Classification
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DOI: 10.1007/s13347-018-0334-2
Abstract: Malware has been around since the 1980s and is a large and expensive security concern today, constantly growing over the past years. As our social, professional and financial lives become more digitalised, they present larger… read more here.
Keywords: classification; mechanisms malware; philosophy; malfunction mechanisms ... See more keywords
Heterogeneous Opcode Space for Metamorphic Malware Detection
Sign Up to like & getrecommendations! Published in 2017 at "Arabian Journal for Science and Engineering"
DOI: 10.1007/s13369-016-2264-6
Abstract: Metamorphic viruses are equipped with morphing engine responsible for transforming the structure of the code in subsequent generations, thereby retaining the malicious behavior. Thus, commercial anti-virus software based on signature approach is unable to identify… read more here.
Keywords: detection; space; feature; metamorphic malware ... See more keywords
Empirical Evaluation of a System Call-Based Android Malware Detector
Sign Up to like & getrecommendations! Published in 2018 at "Arabian Journal for Science and Engineering"
DOI: 10.1007/s13369-017-2828-0
Abstract: The extensive use of smartphones and increased popularity of Android operating system have proliferated in malware attacks. In order to overcome these malicious attacks, numerous malware detectors are now available and have been described in… read more here.
Keywords: system; system call; call based; malware detector ... See more keywords
End-to-end malware detection for android IoT devices using deep learning
Sign Up to like & getrecommendations! Published in 2020 at "Ad Hoc Networks"
DOI: 10.1016/j.adhoc.2020.102098
Abstract: Abstract The Internet of Things (IoT) has grown rapidly in recent years and has become one of the most active areas in the global market. As an open source platform with a large number of… read more here.
Keywords: malware detection; detection; deep learning; malware ... See more keywords
Compact feature hashing for machine learning based malware detection
Sign Up to like & getrecommendations! Published in 2021 at "ICT Express"
DOI: 10.1016/j.icte.2021.08.005
Abstract: Abstract Machine learning can detect variant malware files that can evade signature-based detection. Feature hashing is used to convert features into a fixed-length vector. In this paper, we study the appropriate vector size for feature… read more here.
Keywords: detection; machine learning; feature; feature hashing ... See more keywords