{"title":"Further experiments in biocomputational structural analysis of malware","authors":"Vijay Naidu, A. Narayanan","doi":"10.1109/ICNC.2014.6975904","DOIUrl":null,"url":null,"abstract":"Initial work on structural analysis of malware using the nature-inspired technique of projecting malware signatures into the amino acid/protein domain was promising in a number of ways, including the demonstration of potential links with real-world pathogen proteins. That initial work was necessarily speculative and limited by a number of experimental factors. The aim of the research reported here is to address some of these limitations and to repeat, with malware code and signatures that can be assured as genuine, the experiments previously reported but with enhancements and improvements. Intriguingly, the outcome is the same: for some reason that is not yet known, matching artificial malware code consensuses after multiple alignment against protein databases returns a high proportion of naturally occurring viral proteins.","PeriodicalId":208779,"journal":{"name":"2014 10th International Conference on Natural Computation (ICNC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 10th International Conference on Natural Computation (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2014.6975904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Initial work on structural analysis of malware using the nature-inspired technique of projecting malware signatures into the amino acid/protein domain was promising in a number of ways, including the demonstration of potential links with real-world pathogen proteins. That initial work was necessarily speculative and limited by a number of experimental factors. The aim of the research reported here is to address some of these limitations and to repeat, with malware code and signatures that can be assured as genuine, the experiments previously reported but with enhancements and improvements. Intriguingly, the outcome is the same: for some reason that is not yet known, matching artificial malware code consensuses after multiple alignment against protein databases returns a high proportion of naturally occurring viral proteins.