{"title":"攻击图生成的并发策略","authors":"Ming Li, P. Hawrylak, J. Hale","doi":"10.1109/ICDIS.2019.00033","DOIUrl":null,"url":null,"abstract":"The network attack graph is a powerful tool for analyzing network security, but the generation of a large-scale graph is non-trivial. The main challenge is from the explosion of network state space, which greatly increases time and storage costs. In this paper, three parallel algorithms are proposed to generate scalable attack graphs. An OpenMP-based programming implementation is used to test their performance. Compared with the serial algorithm, the best performance from the proposed algorithms provides a 10X speedup.","PeriodicalId":181673,"journal":{"name":"2019 2nd International Conference on Data Intelligence and Security (ICDIS)","volume":"699 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Concurrency Strategies for Attack Graph Generation\",\"authors\":\"Ming Li, P. Hawrylak, J. Hale\",\"doi\":\"10.1109/ICDIS.2019.00033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The network attack graph is a powerful tool for analyzing network security, but the generation of a large-scale graph is non-trivial. The main challenge is from the explosion of network state space, which greatly increases time and storage costs. In this paper, three parallel algorithms are proposed to generate scalable attack graphs. An OpenMP-based programming implementation is used to test their performance. Compared with the serial algorithm, the best performance from the proposed algorithms provides a 10X speedup.\",\"PeriodicalId\":181673,\"journal\":{\"name\":\"2019 2nd International Conference on Data Intelligence and Security (ICDIS)\",\"volume\":\"699 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 2nd International Conference on Data Intelligence and Security (ICDIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDIS.2019.00033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference on Data Intelligence and Security (ICDIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIS.2019.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Concurrency Strategies for Attack Graph Generation
The network attack graph is a powerful tool for analyzing network security, but the generation of a large-scale graph is non-trivial. The main challenge is from the explosion of network state space, which greatly increases time and storage costs. In this paper, three parallel algorithms are proposed to generate scalable attack graphs. An OpenMP-based programming implementation is used to test their performance. Compared with the serial algorithm, the best performance from the proposed algorithms provides a 10X speedup.