A comprehensive review of cyber security vulnerabilities, threats, attacks, and solutions
Internet usage has grown exponentially, with individuals and companies performing multiple
daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) …
daily transactions in cyberspace rather than in the real world. The coronavirus (COVID-19) …
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 …
NF-GNN: network flow graph neural networks for malware detection and classification
Malicious software (malware) poses an increasing threat to the security of communication
systems as the number of interconnected mobile devices increases exponentially. While …
systems as the number of interconnected mobile devices increases exponentially. While …
A hybrid feature selection approach-based Android malware detection framework using machine learning techniques
With more popularity and advancement in Internet-based services, the use of the Android
smartphone has been increasing very rapidly. The tremendous popularity of using the …
smartphone has been increasing very rapidly. The tremendous popularity of using the …
Android malware detection and classification based on network traffic using deep learning
Users of smartphones in the world has grown significantly, and attacks against these
devices have increased. Many protection techniques for android malware detection have …
devices have increased. Many protection techniques for android malware detection have …
[PDF][PDF] Enhanced android malware detection and family classification, using conversation-level network traffic features.
Signature-based malware detection algorithms are facing challenges to cope with the
massive number of threats in the Android environment. In this paper, conversation-level …
massive number of threats in the Android environment. In this paper, conversation-level …
Android malware defense through a hybrid multi-modal approach
The rapid proliferation of Android apps has given rise to a dark side, where increasingly
sophisticated malware poses a formidable challenge for detection. To combat this evolving …
sophisticated malware poses a formidable challenge for detection. To combat this evolving …
Nt-gnn: Network traffic graph for 5g mobile iot android malware detection
T Liu, Z Li, H Long, A Bilal - Electronics, 2023 - mdpi.com
IoT Android application is the most common implementation system in the mobile
ecosystem. As assaults have increased over time, malware attacks will likely happen on 5G …
ecosystem. As assaults have increased over time, malware attacks will likely happen on 5G …
An empirical evaluation of supervised learning methods for network malware identification based on feature selection
Malware is a sophisticated, malicious, and sometimes unidentifiable application on the
network. The classifying network traffic method using machine learning shows to perform …
network. The classifying network traffic method using machine learning shows to perform …
Android malware detection and categorization based on conversation-level network traffic features
MKA Abuthawabeh… - 2019 International Arab …, 2019 - ieeexplore.ieee.org
The number of malware in Android environment is increasing. As a result, the conventional
detection algorithms that employ signature detection methods are facing challenges to cope …
detection algorithms that employ signature detection methods are facing challenges to cope …