2010 IEEE International Conference on Intelligence and Security Informatics最新文献_第5页

Entity refinement using latent semantic indexing 使用潜在语义索引进行实体细化

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484765

R. Bradford

引用次数: 0

Tweets mining using WIKIPEDIA and impurity cluster measurement 使用维基百科和杂质聚类度量来挖掘推文

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484758

Qing Chen, Timothy Shipper, L. Khan

引用次数: 18

Real time tracking of a remote moving object by active zoom cameras 动态变焦相机对远程移动物体的实时跟踪

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484753

Yan Gao, Xiaolin Zhang

{"title":"Real time tracking of a remote moving object by active zoom cameras","authors":"Yan Gao, Xiaolin Zhang","doi":"10.1109/ISI.2010.5484753","DOIUrl":"https://doi.org/10.1109/ISI.2010.5484753","url":null,"abstract":"Object detecting and tracking at a distance has been a big problem in the research field of wide area security. This paper introduces a real time active vision system which can track a moving object from 1 meter to 200 meters. This visual servo system is mainly structured of three mechanical freedoms of pan, tilt and zoom. An eagle's eye mechanism is proposed to obtain a wide field of view (FOV) in high resolution. A fusion schemes that combines the results of the three separate zoom cameras for detecting and tracking a moving object at distance is also developed. A high performance pan-tilt unit and an algorithm of high frequency motor control is proposed to smooth the tracking. This system has the tracking and zooming functions to monitor an unexpected object at a long distance. The camera can zoom in to capture the high resolution detail of a pedestrian and record a series of available images while tracking. In order to demonstrate the effectiveness of the approaches adopted, an experiment of tracking a pedestrian from a distance of 100–200 meters has been carried out. Experimental results show that the proposed system is valid for tracking a pedestrian at a distance.","PeriodicalId":434501,"journal":{"name":"2010 IEEE International Conference on Intelligence and Security Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129221361","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

Cross-level behavioral analysis for robust early intrusion detection 鲁棒早期入侵检测的跨层行为分析

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484768

Shun-Wen Hsiao, Yeali S. Sun, Meng Chang Chen, Hui Zhang

{"title":"Cross-level behavioral analysis for robust early intrusion detection","authors":"Shun-Wen Hsiao, Yeali S. Sun, Meng Chang Chen, Hui Zhang","doi":"10.1109/ISI.2010.5484768","DOIUrl":"https://doi.org/10.1109/ISI.2010.5484768","url":null,"abstract":"We anticipate future attacks would evolve to become more sophisticated to outwit existing intrusion detection techniques. Existing anomaly analysis techniques and signature-based detection practices can no longer effective. We believe intrusion detection systems (IDSs) of the future will need to be capable to detect or infer attacks based on more valuable information from the network-related properties and characteristics. We observed that even though the signatures or traffic patterns of future stealthy attacks can be modified to outwit current IDSs, certain behavioral aspects of an attack are invariant. We propose a novel approach that jointly monitors network activities at three different levels: transport layer protocols, (vulnerable) network services, and invariant anomaly behaviors (called attack symptoms). Our system, SecMon, captures the network behaviors by simultaneously performing cross-level state correlation for effective detection of anomaly behaviors. For the most part, the invariant anomaly behavior has not been fully exploited in the past. A probabilistic attack inference model is also proposed for attack assessment by correlating the observed attack symptoms to achieve the low false alarm rate. The evaluations demonstrate our prototype system is efficient and effective for sophisticated attacks, including polymorphism, stealthy, and unknown attack.","PeriodicalId":434501,"journal":{"name":"2010 IEEE International Conference on Intelligence and Security Informatics","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121156414","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: 9

Rationalizing police patrol beats using Voronoi Tessellations 合理化警察巡逻殴打使用Voronoi镶嵌

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484750

A. Verma, Ramyaa, S. Marru, Ye Fan, Raminderjeet Singh

引用次数: 6

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484732

Minh Tam Le, J. Sweeney, Edo Liberty, S. Zucker

引用次数: 1

News mining for border security Intelligence 新闻挖掘边境安全情报

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484744

M. Atkinson, Jenya Belayeva, Vanni Zavarella, J. Piskorski, Silja Huttunen, Arto Vihavainen, R. Yangarber

引用次数: 8

Integrated assessment modeling of energy consumption behavior and carbon emissions 能源消费行为与碳排放的综合评价模型

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484734

T. Sanquist, B. Shui, Heather Orr

引用次数: 3

Computational knowledge and information management in veterinary epidemiology 兽医流行病学中的计算知识与信息管理

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484764

Svitlana Volkova, W. Hsu

引用次数: 9

Identifying high risk crime areas using topology 使用拓扑识别高风险犯罪区域

2010 IEEE International Conference on Intelligence and Security Informatics Pub Date : 2010-05-23 DOI: 10.1109/ISI.2010.5484782

Richard Frank, Andrew J. Park, P. Brantingham, J. Clare, Kathryn Wuschke, M. Vajihollahi

{"title":"Identifying high risk crime areas using topology","authors":"Richard Frank, Andrew J. Park, P. Brantingham, J. Clare, Kathryn Wuschke, M. Vajihollahi","doi":"10.1109/ISI.2010.5484782","DOIUrl":"https://doi.org/10.1109/ISI.2010.5484782","url":null,"abstract":"Computational criminology is an area of research that joins advanced theories in criminology with theories and methods in mathematics, computing science, geography and behavioural psychology. It is a multidisciplinary approach that takes the strengths of several disciplines and, with semantic challenges, builds new methods for the analysis of crime and crime patterns. This paper presents a developing algorithm for linking the geographic and cognitive psychology sides of criminology research with a prototype topology algorithm that joins local urban areas together using rules that define similarity between adjacent small units of analysis. The approach produces irregular shapes when mapped in a Euclidean space, but which follow expectations in a non-Euclidean topological sense. There are high local concentrations or hot spots of crime but frequently there is a sharp break on one side of the hot spot and with a gradual diffusion on the other. These shapes follow the cognitive psychological way of moving from one location to another without noticing gradual changes or conversely being aware of sharp changes from one location to the next. This article presents a pattern modeling approach that uses topology to spatially identify the concentrations of crime and their crisp breaks and gradual blending into adjacent areas using the basic components: interior, boundary and exterior. This topology algorithm is used to analyze crimes in a moderate sized city in British Columbia.","PeriodicalId":434501,"journal":{"name":"2010 IEEE International Conference on Intelligence and Security Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130341025","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: 4