{"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/deep-learning-at-the-shallow-end-malware","title":"Deep learning at the shallow end: Malware classification for non-domain experts","arxiv_id":"1807.08265","date":"2018-07-22","proceeding":null,"authors":["Quan Le","Oisín Boydell","Brian Mac Namee","Mark Scanlon"],"abstract":"Current malware detection and classification approaches generally rely on\ntime consuming and knowledge intensive processes to extract patterns\n(signatures) and behaviors from malware, which are then used for\nidentification. Moreover, these signatures are often limited to local,\ncontiguous sequences within the data whilst ignoring their context in relation\nto each other and throughout the malware file as a whole. We present a Deep\nLearning based malware classification approach that requires no expert domain\nknowledge and is based on a purely data driven approach for complex pattern and\nfeature identification.","url_abs":"http://arxiv.org/abs/1807.08265v1","url_pdf":"http://arxiv.org/pdf/1807.08265v1.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":"deep-learning-at-the-shallow-end-malware","repo_url":"https://bitbucket.org/ceadarireland/deeplearningattheshallowend","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"malware-classification","task_name":"Malware Classification"},{"task_slug":"malware-detection","task_name":"Malware Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/malware-classification-on-microsoft-malware","task":"Malware Classification","dataset":"Microsoft Malware Classification Challenge","model":"CNN BiLSTM - Reb Sampl","rank_in_archive_order":26,"of":29,"metrics":{"Accuracy (5-fold)":"98.20","F1 score (5-fold)":"96.05"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}