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Harnessing LLMs for IoT Malware Detection: A Comparative Analysis of BERT and GPT-2

open access: yes2024 8th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
In recent years, the proliferation of Internet of Things (IoT) devices has introduced significant vulnerabilities in cybersecurity, particularly with the rise of sophisticated malware targeting these systems. Traditional detection methods, often based on
Marwan Omar   +3 more
openaire   +2 more sources

Ultra-Lightweight Malware Detection of Android Using 2-Level Machine Learning

2016 3rd International Conference on Information Science and Control Engineering (ICISCE), 2016
As Android becoming the most popular smart phone operating system, malicious applications running on the Android platform appears very frequently and poses the major threat to the security of Android. Considering the resources of smart phone are severely limited, a stable, simple and quick malware detection method for Android is indispensable.
Li Ma   +3 more
openaire   +1 more source

Malware Detection Using Transformers-based Model GPT-2

2021
Zararlı içeriğin çeşitliliği, karmaşıklığının yanı sıra Bilgi ve İletişim Teknolojilerinin (BİT) son kullanıcılarını önemli ölçüde etkilemiştir. Zararlı içeriğin etkisini azaltmak, kullanıcı sistemlerini zararlı yazılımlara karşı proaktif olarak savunmak için otomatikleştirilmiş makine öğrenme teknikleri geliştirildi.
openaire   +1 more source

Session details: Session 2: Malware Detection

Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security, 2020
openaire   +1 more source

A comprehensive survey on deep learning based malware detection techniques

Computer Science Review, 2023
Sibi Chakkaravarthy Sethuraman
exaly  

Malware Detection Issues, Challenges, and Future Directions: A Survey

Applied Sciences (Switzerland), 2022
Faitouri A Aboaoja   +2 more
exaly  

EfficientNet convolutional neural networks-based Android malware detection

Computers and Security, 2022
Neeraj Menon   +2 more
exaly  

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