James Decraene, Mahinthan Chandramohan, M. Low, Chwee Seng Choo
{"title":"自动化红队的演化模拟应用:初步研究","authors":"James Decraene, Mahinthan Chandramohan, M. Low, Chwee Seng Choo","doi":"10.1109/WSC.2010.5679047","DOIUrl":null,"url":null,"abstract":"We report preliminary studies on evolvable simulations applied to Automated Red Teaming (ART). ART is a vulnerability assessment tool in which agent-based models of simplified military scenarios are repeatedly and automatically generated, executed and varied. Nature-inspired heuristic techniques are utilized to drive the exploration of simulation models to exhibit desired system behaviors. To date, ART investigations have essentially addressed the evolution of a limited fixed set of parameters determining the agents' behavior. We propose to extend ART to widen the range of evolvable simulation model parameters. Using this “evolvable simulation” approach, we conduct experiments in which the agents' structure is evolved. Specifically, a maritime scenario is examined where the individual trajectories of belligerent vessels are evolved to break Blue. These experiments are conducted using a modular evolutionary framework coined CASE. The results present counter-intuitive outcomes and suggest that evolvable simulation is a promising technique to enhance ART.","PeriodicalId":272260,"journal":{"name":"Proceedings of the 2010 Winter Simulation Conference","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Evolvable simulations applied to Automated Red Teaming: A preliminary study\",\"authors\":\"James Decraene, Mahinthan Chandramohan, M. Low, Chwee Seng Choo\",\"doi\":\"10.1109/WSC.2010.5679047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We report preliminary studies on evolvable simulations applied to Automated Red Teaming (ART). ART is a vulnerability assessment tool in which agent-based models of simplified military scenarios are repeatedly and automatically generated, executed and varied. Nature-inspired heuristic techniques are utilized to drive the exploration of simulation models to exhibit desired system behaviors. To date, ART investigations have essentially addressed the evolution of a limited fixed set of parameters determining the agents' behavior. We propose to extend ART to widen the range of evolvable simulation model parameters. Using this “evolvable simulation” approach, we conduct experiments in which the agents' structure is evolved. Specifically, a maritime scenario is examined where the individual trajectories of belligerent vessels are evolved to break Blue. These experiments are conducted using a modular evolutionary framework coined CASE. The results present counter-intuitive outcomes and suggest that evolvable simulation is a promising technique to enhance ART.\",\"PeriodicalId\":272260,\"journal\":{\"name\":\"Proceedings of the 2010 Winter Simulation Conference\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2010 Winter Simulation Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSC.2010.5679047\",\"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 2010 Winter Simulation Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.2010.5679047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evolvable simulations applied to Automated Red Teaming: A preliminary study
We report preliminary studies on evolvable simulations applied to Automated Red Teaming (ART). ART is a vulnerability assessment tool in which agent-based models of simplified military scenarios are repeatedly and automatically generated, executed and varied. Nature-inspired heuristic techniques are utilized to drive the exploration of simulation models to exhibit desired system behaviors. To date, ART investigations have essentially addressed the evolution of a limited fixed set of parameters determining the agents' behavior. We propose to extend ART to widen the range of evolvable simulation model parameters. Using this “evolvable simulation” approach, we conduct experiments in which the agents' structure is evolved. Specifically, a maritime scenario is examined where the individual trajectories of belligerent vessels are evolved to break Blue. These experiments are conducted using a modular evolutionary framework coined CASE. The results present counter-intuitive outcomes and suggest that evolvable simulation is a promising technique to enhance ART.