He Gao, Yuanzhuo Wang, Li Wang, Li Liu, Jinming Li, Xueqi Cheng
{"title":"基于随机Petri网的木马特征分析","authors":"He Gao, Yuanzhuo Wang, Li Wang, Li Liu, Jinming Li, Xueqi Cheng","doi":"10.1109/ISI.2011.5984084","DOIUrl":null,"url":null,"abstract":"Trojan's attack behavior has become increasingly common and diversifiable. How to judge Trojan-like features of the softwares which the users download has become the problem that the users concern about. In this paper, we first capture the software's behavior and related parameters from our virtual software test bed, then a modeling method using Stochastic Petri Nets is proposed, which supports quantitative analysis for the application software's behaviors. Based on the model, the similarity degree between application software and Trojan software is analyzed quantitatively. This analysis show that the model can be used to design an effective anti-Trojan system. The paper concludes with an example to illustrate the effectiveness of the model and analysis method.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Trojan characteristics analysis based on Stochastic Petri Nets\",\"authors\":\"He Gao, Yuanzhuo Wang, Li Wang, Li Liu, Jinming Li, Xueqi Cheng\",\"doi\":\"10.1109/ISI.2011.5984084\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Trojan's attack behavior has become increasingly common and diversifiable. How to judge Trojan-like features of the softwares which the users download has become the problem that the users concern about. In this paper, we first capture the software's behavior and related parameters from our virtual software test bed, then a modeling method using Stochastic Petri Nets is proposed, which supports quantitative analysis for the application software's behaviors. Based on the model, the similarity degree between application software and Trojan software is analyzed quantitatively. This analysis show that the model can be used to design an effective anti-Trojan system. The paper concludes with an example to illustrate the effectiveness of the model and analysis method.\",\"PeriodicalId\":220165,\"journal\":{\"name\":\"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISI.2011.5984084\",\"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 2011 IEEE International Conference on Intelligence and Security Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISI.2011.5984084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Trojan characteristics analysis based on Stochastic Petri Nets
Trojan's attack behavior has become increasingly common and diversifiable. How to judge Trojan-like features of the softwares which the users download has become the problem that the users concern about. In this paper, we first capture the software's behavior and related parameters from our virtual software test bed, then a modeling method using Stochastic Petri Nets is proposed, which supports quantitative analysis for the application software's behaviors. Based on the model, the similarity degree between application software and Trojan software is analyzed quantitatively. This analysis show that the model can be used to design an effective anti-Trojan system. The paper concludes with an example to illustrate the effectiveness of the model and analysis method.