Reischaga, Charles Lim, Yohanes Syailendra Kotualubun
{"title":"使用混合分析发现恶意软件特征","authors":"Reischaga, Charles Lim, Yohanes Syailendra Kotualubun","doi":"10.1145/3429789.3429867","DOIUrl":null,"url":null,"abstract":"Malware, its volume increases each year and its threat becoming ever more prevalent, is responsible for a large portion of security incidents. Unfortunately, most of the time information regarding the threat that it poses are notional. In this paper, we conduct heuristic static and dynamic analysis in order to extract the necessary static analysis and dynamic analysis features for detecting, assessing and measuring malware threats. Based on the given datasets, i.e. 876 malware and 49 benignware, our proposed method was able to quantitatively assess the threat level of malware and detect malware with promising results.","PeriodicalId":416230,"journal":{"name":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uncovering Malware Traits Using Hybrid Analysis\",\"authors\":\"Reischaga, Charles Lim, Yohanes Syailendra Kotualubun\",\"doi\":\"10.1145/3429789.3429867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Malware, its volume increases each year and its threat becoming ever more prevalent, is responsible for a large portion of security incidents. Unfortunately, most of the time information regarding the threat that it poses are notional. In this paper, we conduct heuristic static and dynamic analysis in order to extract the necessary static analysis and dynamic analysis features for detecting, assessing and measuring malware threats. Based on the given datasets, i.e. 876 malware and 49 benignware, our proposed method was able to quantitatively assess the threat level of malware and detect malware with promising results.\",\"PeriodicalId\":416230,\"journal\":{\"name\":\"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3429789.3429867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 International Conference on Engineering and Information Technology for Sustainable Industry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3429789.3429867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Malware, its volume increases each year and its threat becoming ever more prevalent, is responsible for a large portion of security incidents. Unfortunately, most of the time information regarding the threat that it poses are notional. In this paper, we conduct heuristic static and dynamic analysis in order to extract the necessary static analysis and dynamic analysis features for detecting, assessing and measuring malware threats. Based on the given datasets, i.e. 876 malware and 49 benignware, our proposed method was able to quantitatively assess the threat level of malware and detect malware with promising results.