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2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications最新文献

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Improved Missile Route Planning and Targeting using Game-Based Computational Intelligence 基于博弈的计算智能改进导弹航路规划和瞄准
2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications Pub Date : 2007-04-01 DOI: 10.1109/CISDA.2007.368136
Ken Doris, D. Silvia
{"title":"Improved Missile Route Planning and Targeting using Game-Based Computational Intelligence","authors":"Ken Doris, D. Silvia","doi":"10.1109/CISDA.2007.368136","DOIUrl":"https://doi.org/10.1109/CISDA.2007.368136","url":null,"abstract":"This paper discusses a research project that employs computational intelligence (CI) to improve the ability of military planners to route sensors and weapons to effectively engage mobile targets. Future target motion is predicted through the use of multiple software agents employing goal oriented action planning (GOAP). Derived from the Stanford Research Institute Planning System (STRIPS), GOAP is a relatively new class of CI that is ideally suited to dynamic real-time environments such as military operations. The project is unusual in its adaptation of computer gaming industry technology for use in real-time, tactical military applications","PeriodicalId":403553,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126982106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
The PSO-Based Adaptive Window for People Tracking 基于pso的人物跟踪自适应窗口
2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications Pub Date : 2007-04-01 DOI: 10.1109/CISDA.2007.368130
Yuhua Zheng, Y. Meng
{"title":"The PSO-Based Adaptive Window for People Tracking","authors":"Yuhua Zheng, Y. Meng","doi":"10.1109/CISDA.2007.368130","DOIUrl":"https://doi.org/10.1109/CISDA.2007.368130","url":null,"abstract":"This paper presents a robust tracking algorithm using an adaptive tracking window associated with five parameters, where the parameters of the tracking window are optimized by a particle swarm optimization (PSO) algorithm. Basically, the optimization of a tracking window is transformed into a searching algorithm in a five-dimension feature space, which constrains the possibilities of the window. Particles associated with different parameters fly around the searching space independently, while they are sharing information from the society and adjust their behaviors to achieve the global optimization, which means the most optimized parameters for the tracking window. Appearance histogram is employed to calculate the fitness function for particles, where the distance between histograms is measured by histogram intersection. Estimated people motion is utilized to expedite the convergence of particles. Experimental results of people tracking demonstrate that the algorithm is efficient, robust, and adaptive to various rigid and non-rigid people motions","PeriodicalId":403553,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134104875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Automatically Evading IDS Using GP Authored Attacks 使用GP授权攻击自动逃避IDS
2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications Pub Date : 2007-04-01 DOI: 10.1109/CISDA.2007.368148
H. G. Kayacik, A. N. Zincir-Heywood, M. Heywood
{"title":"Automatically Evading IDS Using GP Authored Attacks","authors":"H. G. Kayacik, A. N. Zincir-Heywood, M. Heywood","doi":"10.1109/CISDA.2007.368148","DOIUrl":"https://doi.org/10.1109/CISDA.2007.368148","url":null,"abstract":"A mimicry attack is a type of attack where the basic steps of a minimalist 'core' attack are used to design multiple attacks achieving the same objective from the same application. Research in mimicry attacks is valuable in determining and eliminating weaknesses of detectors. In this work, we provide a genetic programming based automated process for designing all components of a mimicry attack relative to the Stide detector under a vulnerable Traceroute application. Results indicate that the automatic process is able to generate mimicry attacks that reduce the alarm rate from ~65% of the original attack, to ~2.7%, effectively making the attack indistinguishable from normal behaviors","PeriodicalId":403553,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115383755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
Architectural Design and Complexity Analysis of Large-Scale Cortical Simulation on a Hybrid Computing Platform 混合计算平台上大规模皮质模拟的体系结构设计与复杂性分析
2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications Pub Date : 2007-04-01 DOI: 10.1109/CISDA.2007.368154
Qing Wu, Qinru Qiu, R. Linderman, Daniel J. Burns, Michael J. Moore, D. Fitzgerald
{"title":"Architectural Design and Complexity Analysis of Large-Scale Cortical Simulation on a Hybrid Computing Platform","authors":"Qing Wu, Qinru Qiu, R. Linderman, Daniel J. Burns, Michael J. Moore, D. Fitzgerald","doi":"10.1109/CISDA.2007.368154","DOIUrl":"https://doi.org/10.1109/CISDA.2007.368154","url":null,"abstract":"Research and development in modeling and simulation of human cognizance functions requires a high-performance computing platform for manipulating large-scale mathematical models. Traditional computing architectures cannot fulfill the attendant needs in terms of arithmetic computation and communication bandwidth. In this work, we propose a novel hybrid computing architecture for the simulation and evaluation of large-scale associative neural memory models. The proposed architecture achieves very high computing and communication performances by combining the technologies of hardware-accelerated computing, parallel distributed data operation and the publish/subscribe protocol. Analysis has been done on the computation and data bandwidth demands for implementing a large-scale brain-state-in-a-box (BSB) model. Compared to the traditional computing architecture, the proposed architecture can achieve at least 100X speedup.","PeriodicalId":403553,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115261600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Face Recognition System Using Ant Colony Optimization-Based Selected Features 基于蚁群优化选择特征的人脸识别系统
2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications Pub Date : 2007-04-01 DOI: 10.1109/CISDA.2007.368135
H. Kanan, K. Faez, Mehdi Hosseinzadeh Aghdam
{"title":"Face Recognition System Using Ant Colony Optimization-Based Selected Features","authors":"H. Kanan, K. Faez, Mehdi Hosseinzadeh Aghdam","doi":"10.1109/CISDA.2007.368135","DOIUrl":"https://doi.org/10.1109/CISDA.2007.368135","url":null,"abstract":"Feature selection (FS) is a most important step which can affect the performance of pattern recognition system. This paper presents a novel feature selection method that is based on ant colony optimization (ACO). ACO algorithm is inspired of ant's social behavior in their search for the shortest paths to food sources. In the proposed algorithm, classifier performance and the length of selected feature vector are adopted as heuristic information for ACO. So, we can select the optimal feature subset without the priori knowledge of features. Simulation results on face recognition system and ORL database show the superiority of the proposed algorithm","PeriodicalId":403553,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134295153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 72
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