Artificial Intelligence-Based Malware Detection, Analysis, and Mitigation
Symmetry, 2023 Malware, a lethal weapon of cyber attackers, is becoming increasingly sophisticated, with rapid deployment and self-propagation. In addition, modern malware is one of the most devastating forms of cybercrime, as it can avoid detection, make digital ...
Amir Djenna +3 more
semanticscholar +1 more source
Automated System-Level Malware Detection Using Machine Learning: A Comprehensive Review
Applied Sciences, 2023 Malware poses a significant threat to computer systems and networks. This necessitates the development of effective detection mechanisms. Detection mechanisms dependent on signatures for attack detection perform poorly due to high false negatives.
Nana Kwame Gyamfi +3 more
doaj +1 more source
Malware Detection with Artificial Intelligence: A Systematic Literature Review
ACM Computing Surveys, 2023 In this survey, we review the key developments in the field of malware detection using AI and analyze core challenges. We systematically survey state-of-the-art methods across five critical aspects of building an accurate and robust AI-powered malware ...
Matthew Gaber +2 more
semanticscholar +1 more source
Obfuscated Memory Malware Detection in Resource-Constrained IoT Devices for Smart City Applications
Italian National Conference on Sensors, 2023 Obfuscated Memory Malware (OMM) presents significant threats to interconnected systems, including smart city applications, for its ability to evade detection through concealment tactics. Existing OMM detection methods primarily focus on binary detection.
S. S. Shafin, G. Karmakar, I. Mareels
semanticscholar +1 more source
GSIDroid: A Suspicious Subgraph-Driven and Interpretable Android Malware Detection System. [PDF]
Sensors (Basel)Huang H, Huang W, Jiang F.
europepmc +3 more sources
A Systematic Literature Review of Android Malware Detection Using Static Analysis
IEEE Access, 2020 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 without explicitly prompting the users or without the user's permission, and it ...
Ya Pan +3 more
doaj +1 more source
Android malware category detection using a novel feature vector-based machine learning model
Cybersecurity, 2023 Malware attacks on the Android platform are rapidly increasing due to the high consumer adoption of Android smartphones. Advanced technologies have motivated cyber-criminals to actively create and disseminate a wide range of malware on Android ...
Hashida Haidros Rahima Manzil +1 more
doaj +1 more source
Research on the Construction of Malware Variant Datasets and Their Detection Method
Applied Sciences, 2022 Malware detection is of great significance for maintaining the security of information systems. Malware obfuscation techniques and malware variants are increasingly emerging, but their samples and API (application programming interface) sequences are ...
Faming Lu +4 more
doaj +1 more source
Cryptography, 2021 According to recent security analysis reports, malicious software (a.k.a. malware) is rising at an alarming rate in numbers, complexity, and harmful purposes to compromise the security of modern computer systems.
Hossein Sayadi +6 more
doaj +1 more source
DroidDetectMW: A Hybrid Intelligent Model for Android Malware Detection
Applied Sciences, 2023 Malicious apps specifically aimed at the Android platform have increased in tandem with the proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect.
Fatma Taher +4 more
semanticscholar +1 more source