Results 1 to 10 of about 31,501 (227)

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

Effective and Reliable Malware Group Classification for a Massive Malware Environment [PDF]

International Journal of Distributed Sensor Networks, 2016
Most of the cyber-attacks are caused by malware, and damage from them has escalated from cyber space to home appliances and infrastructure, thus affecting the daily living of the people. As such, anticipative analysis and countermeasures for malware have
Tae‐Jin Lee, Jin Kwak
openalex   +2 more sources

A Classification System for Visualized Malware Based on Multiple Autoencoder Models

IEEE Access, 2021
In this paper, we propose a classification system that uses multiple autoencoder models for identifying malware images. It is crucial to accurately classify malware before we can deploy appropriate countermeasures to prevent them from spreading.
Jongkwan Lee, Jongdeog Lee
openalex   +3 more sources

Malware Classification Using Transfer Learning [PDF]

, 2021
With the rapid growth of the number of devices on the Internet, malware poses a threat not only to the affected devices but also their ability to use said devices to launch attacks on the Internet ecosystem. Rapid malware classification is an important tools to combat that threat.
Hikmat Farhat, Veronica Rammouz
openalex   +3 more sources

Learning and Classification of Malware Behavior [PDF]

, 2008
Malicious software in form of Internet worms, computer viruses, and Trojan horses poses a major threat to the security of networked systems. The diversity and amount of its variants severely undermine the effectiveness of classical signature-based detection.
Konrad Rieck, Thorsten Holz, Carsten Willems, Patrick Düssel, Pavel Laskov   +4 more
openalex   +3 more sources

Classification of Malware Images Using Fine-Tunned ViT

Sakarya University Journal of Computer and Information Sciences
Malware detection and classification have become critical tasks in ensuring the security and integrity of computer systems and networks. Traditional methods of malware analysis often rely on signature-based approaches, which struggle to cope with the ...
Oğuzhan KATAR, Özal Yıldırım
openalex   +4 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, Joon-Young Paik, Eun-Sun Cho   +2 more
doaj   +1 more source