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IEEE Access, 2021 Malware variants are the major emerging threats that face cybersecurity due to the potential damage to computer systems. Many solutions have been proposed for detecting malware variants.
Abdulbasit A. Darem +5 more
doaj +1 more source
A Survey on Malware and Malware Detection Systems [PDF]
International Journal of Computer Applications, 2013 Lately, a new kind of war takes place between the security community and malicious software developers, the security specialists use all possible techniques, methods and strategies to stop and remove the threats while the malware developers utilize new ...
Ali M. A. Abuagoub +2 more
core +3 more sources
Technique for IoT malware detection based on control flow graph analysis
Радіоелектронні і комп'ютерні системи, 2022 The Internet of Things (IoT) refers to the millions of devices around the world that are connected to the Internet. Insecure IoT devices designed without proper security features are the targets of many Internet threats.
Kira Bobrovnikova +4 more
doaj +1 more source
Morphological detection of malware [PDF]
2008 3rd International Conference on Malicious and Unwanted Software (MALWARE), 2008 In the field of malware detection, method based on syntactical consideration are usually efficient. However, they are strongly vulnerable to obfuscation techniques. This study proposes an efficient construction of a morphological malware detector based on a syntactic and a semantic analysis, technically on control flow graphs of programs (CFG).
Bonfante, Guillaume +2 more
openaire +3 more sources
HMLET: Hunt Malware Using Wavelet Transform on Cross-Platform
IEEE Access, 2022 As the importance of cyberspace grows, malicious software (malware) is threatening not only individuals but also countries. In addition, numerous malware is still circulating in cyberspace, and as technology advances, new or advanced malware are emerging.
Sangmin Park +2 more
doaj +1 more source
The rise of obfuscated Android malware and impacts on detection methods [PDF]
PeerJ Computer Science, 2022 The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malicious
Wael F. Elsersy +2 more
doaj +2 more sources
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
Adaptive secure malware efficient machine learning algorithm for healthcare data
CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed +8 more
wiley +1 more source
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, 2023 The "Malware Detection on Application using Machine Learning" project is a focused initiative aimed at enhancing the security of mobile applications through advanced detection mechanisms. As the threat landscape for mobile app-based malware continues to evolve, this project leverages the power of machine learning to develop robust and adaptive ...
EL-MOUSSA FADI, AZVINE BEHNAN
openaire +3 more sources
Detecting Malware with Information Complexity [PDF]
Entropy, 2020 Malware concealment is the predominant strategy for malware propagation. Black hats create variants of malware based on polymorphism and metamorphism. Malware variants, by definition, share some information. Although the concealment strategy alters this information, there are still patterns on the software.
Nadia Alshahwan +4 more
openaire +4 more sources