Gibert et al. (2019b) proposed a file agnostic deep learning approach for malware categorization to efficiently group malicious software into families based on ...
With the continuous exploration of malware authors, the methods of malicious software for attacking the operating system and code obfuscation anti-detection ...
With the continuous exploration of malware authors, the methods of malicious software for attacking the operating system and code obfuscation anti-detection ...
Malware is typically identified via a technique called hashing. A hashing application is used to run the malicious software, producing a distinct hash that ...
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ARES. 2023. In this paper, we propose a novel approach to Android malware analysis and categorization that leverages the power of BERT (Bidirectional Encoder ...
Also called MalBERT but oriented to the detection of malware affecting win- dows systems using BERT, MalBERT: A novel pre-training method for malware.
Jul 18, 2024 · In this work, we propose EarlyMalDetect, a novel approach for early Windows malware detection based on sequences of API calls.
Mar 5, 2021 · Static Malware Detection Using Stacked BiLSTM and GPT-2 · Using Pre-trained Transformers to Detect Malicious Source Code Within JavaScript ...
Mar 4, 2023 · To proactively mitigate malware threats, cybersecurity tools, such as anti-virus and anti-malware software, as well as firewalls, ...
Jun 20, 2022 · In this paper, we propose two empirical studies to (1) detect Android malware and (2) classify Android malware into families.