A comprehensive survey on deep learning based malware detection techniques
M Gopinath, SC Sethuraman - Computer Science Review, 2023 - Elsevier
Recent theoretical and practical studies have revealed that malware is one of the most
harmful threats to the digital world. Malware mitigation techniques have evolved over the …
harmful threats to the digital world. Malware mitigation techniques have evolved over the …
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 …
DeepAMD: Detection and identification of Android malware using high-efficient Deep Artificial Neural Network
Android smartphones are being utilized by a vast majority of users for everyday planning,
data exchanges, correspondences, social interaction, business execution, bank …
data exchanges, correspondences, social interaction, business execution, bank …
Extensible android malware detection and family classification using network-flows and API-calls
Android OS-based mobile devices have attracted numerous end-users since they are
convenient to work with and offer a variety of features. As a result, Android has become one …
convenient to work with and offer a variety of features. As a result, Android has become one …
Security analysis of IoT devices by using mobile computing: a systematic literature review
Internet of Things (IoT) devices are operating in various domains like healthcare
environment, smart cities, smart homes, transportation, and smart grid system. These …
environment, smart cities, smart homes, transportation, and smart grid system. These …
[HTML][HTML] Kronodroid: time-based hybrid-featured dataset for effective android malware detection and characterization
Android malware evolution has been neglected by the available data sets, thus providing a
static snapshot of a non-stationary phenomenon. The impact of the time variable has not had …
static snapshot of a non-stationary phenomenon. The impact of the time variable has not had …
Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach
The evolution of mobile malware poses a serious threat to smartphone security. Today,
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …
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 …
Deep learning for image-based mobile malware detection
F Mercaldo, A Santone - Journal of Computer Virology and Hacking …, 2020 - Springer
Current anti-malware technologies in last years demonstrated their evident weaknesses due
to the signature-based approach adoption. Many alternative solutions were provided by the …
to the signature-based approach adoption. Many alternative solutions were provided by the …
EntropLyzer: Android malware classification and characterization using entropy analysis of dynamic characteristics
DS Keyes, B Li, G Kaur, AH Lashkari… - … Privacy, and Security …, 2021 - ieeexplore.ieee.org
The unmatched threat of Android malware has tremendously increased the need for
analyzing prominent malware samples. There are remarkable efforts in static and dynamic …
analyzing prominent malware samples. There are remarkable efforts in static and dynamic …