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Hybrid Input Model Using Multiple Features From Surface Analysis for Malware Detection
IEEE AccessMany malware detection models have been proposed to protect computers from the ever- increasing number of malware attacks. The features that are obtained from surface analysis and machine learning are often used for malware detection.
Mamoru Mimura, Satoki Kanno
doaj +1 more source
A Survey of Malware Detection Using Deep Learning [PDF]
arXiv.orgA. Bensaoud, J. Kalita, Mahmoud Bensaoud
semanticscholar +1 more source
MIDALF—multimodal image and audio late fusion for malware detection
EURASIP Journal on Information SecurityMalware detection remains a critical challenge in cybersecurity due to the rapid evolution of sophisticated malware and adversarial threats. Traditional detection systems struggle to adapt to dynamic malware behavior and are particularly vulnerable to ...
Setia Juli Irzal Ismail +4 more
doaj +1 more source
A survey on hardware-based malware detection approaches [PDF]
, 2023 Cristiano Pegoraro Chenet +2 more
openalex +1 more source
IEEE AccessThe sophistication of Android malware poses significant threats to user security and privacy. Traditional detection methods struggle with rapid malware evolution and benign application diversity, leading to high false positive rates and limited ...
Yogesh Kumar Sharma +3 more
doaj +1 more source
Malware Detection using Deep Learning Methods
, 2020 Nourin N. S, A Sulphikar
openalex +1 more source
Android Malware Detection Based on Feature Selection and Weight Measurement [PDF]
, 2022 Huizhong Sun +3 more
openalex +1 more source
A Multimodal Malware Detection Technique for Android IoT Devices Using Various Features [PDF]
, 2019 Rajesh Kumar +5 more
openalex +1 more source
Federated Learning for Malware Detection in IoT Devices [PDF]
Comput. Networks, 2021 Valerian Rey +4 more
semanticscholar +1 more source