Results 1 to 10 of about 29,821 (199)
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
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
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
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
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