Results 11 to 20 of about 37,609 (225)
MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware [PDF]
2023 IEEE International Conference on Intelligence and Security Informatics (ISI), 2023 Malware is one of the most dangerous and costly cyber threats to national security and a crucial factor in modern cyber-space. However, the adoption of machine learning (ML) based solutions against malware threats has been relatively slow. Shortcomings in the existing ML approaches are likely contributing to this problem.
Maksim Ekin Eren +4 more
core +5 more sources
A Comprehensive Review on Malware Detection Approaches
IEEE Access, 2020 According to the recent studies, malicious software (malware) is increasing at an alarming rate, and some malware can hide in the system by using different obfuscation techniques.
Refik Samet, Ömer Aslan
exaly +3 more sources
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
openaire +2 more sources
Malware behavior image for malware variant identification
2014 International Symposium on Biometrics and Security Technologies (ISBAST), 2014 Several methods have been devised by researchers to facilitate malware analysis and one of them is through malware visualization. Malware visualization is a field that focuses on representing malware features in a form of visual cues that could be used to convey more information about a particular malware.
Syed Zainudeen Mohd Shaid +1 more
openaire +3 more sources
Adversarial Malware Generation Method Based on Genetic Algorithm [PDF]
Jisuanji kexue, 2023 In recent years,with the development of Internet technology,malware has become an important method of network attack.To defend against malware attacks,deep learning techniques can be applied to malware detection.However,due to the limitations of deep ...
LI Kun, GUO Wei, ZHANG Fan, DU Jiayu, YANG Meiyue
doaj +1 more source
Attention-Based Cross-Modal CNN Using Non-Disassembled Files for Malware Classification
IEEE Access, 2023 The role of malware classification is crucial in addressing the explosive increase in malware variants. By classifying malware instances into malware families, malware analysts can apply appropriate techniques and tools to handle malware variants in each
Jeongwoo Kim +2 more
doaj +1 more source
Malware-on-the-Brain: Illuminating Malware Byte Codes With Images for Malware Classification
IEEE Transactions on Computers, 2023 Malware is a piece of software that was written with the intent of doing harm to data, devices, or people. Since a number of new malware variants can be generated by reusing codes, malware attacks can be easily launched and thus become common in recent years, incurring huge losses in businesses, governments, financial institutes, health providers, etc.
Fangtian Zhong +5 more
openaire +2 more sources
IEEE Access, 2022 Malware has plagued the internet and computing systems for decades. The war against malware has always been an arms race. Researchers and industry have constantly improved detection and prevention methodologies against increasingly more evasive malware ...
Siwon Huh +4 more
doaj +1 more source
Study on Malware Classification Based on N-Gram Static Analysis Technology [PDF]
Jisuanji kexue, 2022 In order to solve the problem of low accuracy of malware classification,this paper proposes a research on malware classification based on N-Gram static analysis technology.Firstly,the N-Gram method is used to extract the byte sequence of length 2 from ...
ZHANG Guang-hua, GAO Tian-jiao, CHEN Zhen-guo, YU Nai-wen
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