{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/improving-malware-detection-accuracy-by","title":"Improving Malware Detection Accuracy by Extracting Icon Information","arxiv_id":"1712.03483","date":"2017-12-10","proceeding":null,"authors":["Pedro Silva","Sepehr Akhavan-Masouleh","Li Li"],"abstract":"Detecting PE malware files is now commonly approached using statistical and\nmachine learning models. While these models commonly use features extracted\nfrom the structure of PE files, we propose that icons from these files can also\nhelp better predict malware. We propose an innovative machine learning approach\nto extract information from icons. Our proposed approach consists of two steps:\n1) extracting icon features using summary statics, histogram of gradients\n(HOG), and a convolutional autoencoder, 2) clustering icons based on the\nextracted icon features. Using publicly available data and by using machine\nlearning experiments, we show our proposed icon clusters significantly boost\nthe efficacy of malware prediction models. In particular, our experiments show\nan average accuracy increase of 10% when icon clusters are used in the\nprediction model.","url_abs":"http://arxiv.org/abs/1712.03483v1","url_pdf":"http://arxiv.org/pdf/1712.03483v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"improving-malware-detection-accuracy-by","repo_url":"https://github.com/CylanceSPEAR/improving-malware-detection-accuracy-by-extracting-icon-information","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"malware-detection","task_name":"Malware Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}