Results 1 to 10 of about 2,609 (164)
FedHGCDroid: An Adaptive Multi-Dimensional Federated Learning for Privacy-Preserving Android Malware Classification. [PDF]
Entropy (Basel), 2022 With the popularity of Android and its open source, the Android platform has become an attractive target for hackers, and the detection and classification of malware has become a research hotspot.
Jiang C, Yin K, Xia C, Huang W.
europepmc +2 more sources
An Analysis of Android Malware Classification Services. [PDF]
Sensors (Basel), 2021 The increasing number of Android malware forced antivirus (AV) companies to rely on automated classification techniques to determine the family and class of suspicious samples. The research community relies heavily on such labels to carry out prevalence studies of the threat ecosystem and to build datasets that are used to validate and benchmark novel ...
Rashed M, Suarez-Tangil G.
europepmc +6 more sources
CSMC: A Secure and Efficient Visualized Malware Classification Method Inspired by Compressed Sensing. [PDF]
Sensors (Basel)With the rapid development of the Internet of Things (IoT), the sophistication and intelligence of sensors are continually evolving, playing increasingly important roles in smart homes, industrial automation, and remote healthcare.
Wu W, Peng H, Zhu H, Zhang D.
europepmc +2 more sources
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
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
Binary and Multi-Class Malware Threads Classification
Applied Sciences, 2022 The security of a computer system can be harmed by specific applications, such as malware. Malware comprises unwanted, dangerous enemies that aim to compromise the security and generate significant loss.
Ismail Taha Ahmed +3 more
doaj +1 more source
MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware
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.
Eren, Maksim E. +4 more
openaire +2 more sources
Robust Malware Family Classification Using Effective Features and Classifiers
Applied Sciences, 2022 Malware development has significantly increased recently, posing a serious security risk to both consumers and businesses. Malware developers continually find new ways to circumvent security research’s ongoing efforts to guard against malware attacks ...
Baraa Tareq Hammad +4 more
doaj +1 more source
Applied Sciences, 2021 Malware are developed for various types of malicious attacks, e.g., to gain access to a user’s private information or control of the computer system. The identification and classification of malware has been extensively studied in academic societies and ...
Dong-Kyu Chae +4 more
doaj +1 more source
Detection of Exceptional Malware Variants Using Deep Boosted Feature Spaces and Machine Learning
Applied Sciences, 2021 Malware is a key component of cyber-crime, and its analysis is the first line of defence against cyber-attack. This study proposes two new malware classification frameworks: Deep Feature Space-based Malware classification (DFS-MC) and Deep Boosted ...
Muhammad Asam +8 more
doaj +1 more source