Deep learning for android malware defenses: a systematic literature review
Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …
threat to developers and end-users. Numerous research efforts have been devoted to …
Cyber security in smart cities: a review of deep learning-based applications and case studies
D Chen, P Wawrzynski, Z Lv - Sustainable Cities and Society, 2021 - Elsevier
On the one hand, smart cities have brought about various changes, aiming to revolutionize
people's lives. On the other hand, while smart cities bring better life experiences and great …
people's lives. On the other hand, while smart cities bring better life experiences and great …
Android malware detection based on multi-head squeeze-and-excitation residual network
H Zhu, W Gu, L Wang, Z Xu, VS Sheng - Expert Systems with Applications, 2023 - Elsevier
The popularity and flexibility of the Android platform makes it the primary target of malicious
attackers. The behaviors of malware, such as malicious charges and privacy theft, pose …
attackers. The behaviors of malware, such as malicious charges and privacy theft, pose …
A malware detection approach using autoencoder in deep learning
Today, in the field of malware detection, the expanding limitations of traditional detection
methods and the increasing accuracy of detection methods designed on the basis of artificial …
methods and the increasing accuracy of detection methods designed on the basis of artificial …
An effective end-to-end android malware detection method
H Zhu, H Wei, L Wang, Z Xu, VS Sheng - Expert Systems with Applications, 2023 - Elsevier
Android has rapidly become the most popular mobile operating system because of its open
source, rich hardware selectivity, and millions of applications (Apps). Meanwhile, the open …
source, rich hardware selectivity, and millions of applications (Apps). Meanwhile, the open …
Obfuscation-resilient android malware analysis based on complementary features
Existing Android malware detection methods are usually hard to simultaneously resist
various obfuscation techniques. Therefore, bytecode-based code obfuscation becomes an …
various obfuscation techniques. Therefore, bytecode-based code obfuscation becomes an …
Classification and analysis of android malware images using feature fusion technique
The super packed functionalities and artificial intelligence (AI)-powered applications have
made the Android operating system a big player in the market. Android smartphones have …
made the Android operating system a big player in the market. Android smartphones have …
A two‐stage deep learning framework for image‐based android malware detection and variant classification
With the popularity of the internet and smartphones, malware on smartphones has increased
dramatically. In addition, the ubiquity and openness of the Android operating system have …
dramatically. In addition, the ubiquity and openness of the Android operating system have …
Android malware detection using tcn with bytecode image
W Zhang, N Luktarhan, C Ding, B Lu - Symmetry, 2021 - mdpi.com
With the rapid increase in the number of Android malware, the image-based analysis
method has become an effective way to defend against symmetric encryption and confusing …
method has become an effective way to defend against symmetric encryption and confusing …
Jadeite: a novel image-behavior-based approach for java malware detection using deep learning
Java malware exploiting language vulnerabilities has become increasingly prevalent in the
recent past. Since Java is a platform-independent language, these security threats open up …
recent past. Since Java is a platform-independent language, these security threats open up …