{"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/novel-feature-extraction-selection-and-fusion","title":"Novel Feature Extraction, Selection and Fusion for Effective Malware Family Classification","arxiv_id":"1511.04317","date":"2015-11-13","proceeding":null,"authors":["Mansour Ahmadi","Dmitry Ulyanov","Stanislav Semenov","Mikhail Trofimov","Giorgio Giacinto"],"abstract":"Modern malware is designed with mutation characteristics, namely polymorphism\nand metamorphism, which causes an enormous growth in the number of variants of\nmalware samples. Categorization of malware samples on the basis of their\nbehaviors is essential for the computer security community, because they\nreceive huge number of malware everyday, and the signature extraction process\nis usually based on malicious parts characterizing malware families. Microsoft\nreleased a malware classification challenge in 2015 with a huge dataset of near\n0.5 terabytes of data, containing more than 20K malware samples. The analysis\nof this dataset inspired the development of a novel paradigm that is effective\nin categorizing malware variants into their actual family groups. This paradigm\nis presented and discussed in the present paper, where emphasis has been given\nto the phases related to the extraction, and selection of a set of novel\nfeatures for the effective representation of malware samples. Features can be\ngrouped according to different characteristics of malware behavior, and their\nfusion is performed according to a per-class weighting paradigm. The proposed\nmethod achieved a very high accuracy ($\\approx$ 0.998) on the Microsoft Malware\nChallenge dataset.","url_abs":"http://arxiv.org/abs/1511.04317v2","url_pdf":"http://arxiv.org/pdf/1511.04317v2.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":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/ManSoSec/Microsoft-Malware-Challenge","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/GopiSumanth/Microsoft-Malware-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/KarthikMurugadoss1804/Malware-Prediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/Pathakvishnu/Microsoft-Malware-Detection--Kaggle","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/PrasunDutta007/Microsoft-Malware-Detection-Analysis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/PrasunDutta007/Microsoft-Malware-Detection-Research-Project-","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/Raman-Raje/Microsoft-Malware-Detecion","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/Raman-Raje/Microsoft-Malware-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/SamratSengupta/Microsoft-malware-detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/Tarunkumar111/Microsoft-Malware-Detection-ML","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/bharath7896/Microsoft-malware-detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/dangmc/Malware","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/h1n1ron/Microsoft-Malware-Classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/heenasingh1995/Microsoft-Malware-Detection-problem","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/manish-vi/Malware-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/shashank3009/malware","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/sujitjean/Microsoft-Malware-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/vkm007/Microsoft-Malware-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"novel-feature-extraction-selection-and-fusion","repo_url":"https://github.com/wizard-kv/Microsoft-Malware-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"computer-security","task_name":"Computer Security"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"malware-classification","task_name":"Malware Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}