Future Internet, Volume 17, Issue 12
2025 December - 53 articles
Cover Story: The Internet’s evolution from Web 1.0 to Web 3.0 has expanded the attack surface for cybercriminals, making malware attacks more sophisticated. The use of AI in antivirus solutions challenges traditional detection methods. Research shows that converting malware files into textured images enhances resistance to obfuscation and improves the detection of zero-day threats. This paper explores the use of image quality assessment (IQA) to enhance the curation of visual malware datasets. We propose MalScore, a no-reference IQA algorithm designed to evaluate dataset quality and guide future dataset development. Our evaluation demonstrates that MalScore effectively differentiates dataset quality, with MalNet Tiny scoring 95% and NARAD 50%, highlighting its potential for visual malware detection and the integration of IQA techniques. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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