Results 91 to 100 of about 2,609 (164)

Deep visualization classification method for malicious code based on Ngram-TFIDF

Tongxin xuebao
With the continuous increase in the scale and variety of malware, traditional malware analysis methods, which relied on manual feature extraction, become time-consuming and error-prone, rendering them unsuitable.
WANG Jinwei, CHEN Zhengjia, XIE Xue, LUO Xiangyang, MA Bin   +4 more
doaj   +2 more sources

Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data

Sensors
Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas.
Mehwish Naseer, Farhan Ullah, Samia Ijaz, Hamad Naeem, Amjad Alsirhani, Ghadah Naif Alwakid, Abdullah Alomari   +6 more
doaj   +1 more source

OpCode-Level Function Call Graph Based Android Malware Classification Using Deep Learning. [PDF]

Sensors (Basel), 2020
Niu W, Cao R, Zhang X, Ding K, Zhang K, Li T.   +5 more
europepmc   +1 more source

Malware Classification with BERT

, 2022
openaire   +2 more sources

An Explainable Hybrid CNN-Transformer Architecture for Visual Malware Classification. [PDF]

Sensors (Basel)
Alshomrani M, Albeshri A, Alsulami AA, Alturki B.   +3 more
europepmc   +1 more source

Research on APT groups malware classification based on TCN-GAN. [PDF]

PLoS One
Chen D, Yan H.
europepmc   +1 more source

MALWARE CLASSIFICATION USING DEEP LEARNING

Proceedings of International Conference on Artificial Life and Robotics, 2020
Cheng-Hsiang Lo, Ta-Che Liu, I-Hsien Liu, Jung-Shian Li, Chuan-Gang Liu, Chu-Fen Li   +5 more
openaire   +1 more source

Semantic lossless encoded image representation for malware classification. [PDF]

Sci Rep
Yu Y, Cai B, Aziz K, Wang X, Luo J, Iqbal MS, Chakrabarti P, Chakrabarti T.   +7 more
europepmc   +1 more source

Multimodal malware classification using proposed ensemble deep neural network framework. [PDF]

Sci Rep
Nazim S, Alam MM, Rizvi S, Mustapha JC, Hussain SS, Su'ud MM.   +5 more
europepmc   +1 more source