{"title":"Research on government on-line information management and service","authors":"Yin-zhi Lei, Xiaodong Zhou, Xi-peng Wei","doi":"10.1109/ISI.2011.5984086","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984086","url":null,"abstract":"Combined with the changes of the government online information management and service in recent years, the paper discuss the Development and Current Status about Government online information resource management, service quality and service standards, availability and proposed to increase government online information management and service concerns from the theoretical and practical.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132555912","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}
{"title":"Criminal identity resolution using social behavior and relationship attributes","authors":"Jiexun Li, G. A. Wang","doi":"10.1109/ISI.2011.5983994","DOIUrl":"https://doi.org/10.1109/ISI.2011.5983994","url":null,"abstract":"We propose a criminal identity resolution technique that utilizes both personal identity and social identity information. Guided by existing identity theories, we examine three types of identity features, namely personal identity attributes, social behavior attributes, and social relationship attributes. We also explore three matching strategies, namely pair-wise comparison, transitive-closure, and collective resolution. Our experiment on synthetic data sets show that both social behavior and relationship attributes improve the performance of identity matching as compared to the use of personal identity attributes alone. The results also show that the collective relational resolution approach outperformed other approaches in terms of F-measure.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"322 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132202295","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}
{"title":"Citizen-generated spatial data and information: Risks and opportunities","authors":"P. Mooney, Huabo Sun, P. Corcoran, Lei Yan","doi":"10.1109/ISI.2011.5984087","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984087","url":null,"abstract":"The use of location-enabled mobile technology is ubiquituos. We outline the opportunities and risks involved in using user-generated spatial data and information. User generated spatial data is a very dynamic but has many inconsistencies. This could severely limit its use in many security and intelligence applications.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125813415","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}
H. Y. Shahir, U. Glässer, Piper J. Jackson, H. Wehn
{"title":"Test-case generation for marine safety and security scenarios","authors":"H. Y. Shahir, U. Glässer, Piper J. Jackson, H. Wehn","doi":"10.1109/ISI.2011.5984049","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984049","url":null,"abstract":"Marine safety & security is critical for Canada's coasts given the vulnerability of sea lanes, ports and harbors to a variety of threats and illegal activities. Decision support systems and simulation environments play a key role in facilitating surveillance operations. Meaningful results from simulation runs require appropriate test cases, the production of which is in itself a complex activity. In this paper, we propose an approach for the generation of test-cases for marine safety & security scenarios. The conceptual design issues including the main requirements, the architecture, and other detailed design issues of the proposed system are discussed. We also propose a formal representation of test-cases using the Abstract State Machine method and illustrate the approach by means of simple examples.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126191242","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}
{"title":"Anomaly detection using weak estimators","authors":"J. Zhan, B. Oommen, Johanna Crisostomo","doi":"10.1109/ISI.2011.5984065","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984065","url":null,"abstract":"Anomaly detection involves identifying observations that deviate from the normal behavior of a system. One of the ways to achieve this is by identifying the phenomena that characterize “normal” observations. Subsequently, based on the characteristics of data learned from the “normal” observations, new observations are classified as being either “normal” or not. Most state-of-the-art approaches, especially those which belong to the family parameterized statistical schemes, work under the assumption that the underlying distributions of the observations are stationary. That is, they assume that the distributions that are learned during the training (or learning) phase, though unknown, are not time-varying. They further assume that the same distributions are relevant even as new observations are encountered. Although such a “stationarity” assumption is relevant for many applications, there are some anomaly detection problems where stationarity cannot be assumed. For example, in network monitoring, the patterns which are learned to represent normal behavior may change over time due to several factors such as network infrastructure expansion, new services, growth of user population, etc. Similarly, in meteorology, identifying anomalous temperature patterns involves taking into account seasonal changes of normal observations. Detecting anomalies or outliers under these circumstances introduces several challenges. Indeed, the ability to adapt to changes in non-stationary environments is necessary so that anomalous observations can be identified even with changes in what would otherwise be classified as “normal” behavior. In this paper, we proposed to apply weak estimation theory for anomaly detection in dynamic environments. In particular, we apply this theory to detect anomaly activities in system calls. Our experimental results demonstrate that our proposal is both feasible and effective for the detection of such anomalous activities.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127417273","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}
{"title":"Quantitative risk analysis model of integrating fuzzy fault tree with Bayesian Network","authors":"Yan Fu Wang, M. Xie, K. Ng, Y. Meng","doi":"10.1109/ISI.2011.5984095","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984095","url":null,"abstract":"In this paper, a new quantitative risk analysis model of integrating fuzzy fault tree (FFT) with Bayesian Network (BN) is proposed. The first step involves describing a fuzzy fault tree analysis technique based on the Takagi and Sugeno model. The second step proposes the translation rules for converting FFT into BN. Based on this, the integration algorithm is demonstrated by an offshore fire case study. The example clearly shows that FFT can be directly converted into BN and the classical parameters of FFT can be obtained by the basic inference techniques of BN. By using the advantages of both techniques, the model of integrating FFT with BN is more flexible and useful than traditional fault tree model. This new model not only can be used for describing the causal effect of accident escalation but also for computing the occurrence probability of accident based on historical data and fuzzy logic.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129914262","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}
{"title":"A nonparametric fault isolation approach through hybrid novelty score","authors":"Gulanbaier Tuerhong, S. Kim","doi":"10.1109/ISI.2011.5984094","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984094","url":null,"abstract":"Isolating the variable or set of variables responsible for an out-of-control signal is a challenging task in multivariate statistical process control. Several fault isolation approaches have been proposed. However, all assumed a multivariate normal distribution on the process data, an assumption that limits their applicability in many situations. In the present study we propose a nonparametric fault isolation approach based on a hybrid novelty score (HNS). A simulation study was conducted to examine the performance of our proposed HNS-based fault isolation approach, and its results were compared with both parametric and nonparametric T2 decomposition approaches. The performance of our approach was superior in the simulation to either parametric or nonparametric T2 decompositions. This was especially true in nonnormal situations.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130262746","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}
{"title":"Forecasting group behavior via multiple plan recognition","authors":"Xiaochen Li, W. Mao, D. Zeng, Huachi Zhu","doi":"10.1109/ISI.2011.5983997","DOIUrl":"https://doi.org/10.1109/ISI.2011.5983997","url":null,"abstract":"Forecasting group behavior is critical to national and international security. Various forecasting methods have been developed previously. However, the majority of them are data-driven methods and rely heavily on the structured data which are often hard to obtain. To overcome the limitation of previous methods, we propose a novel plan recognition method for detecting multiple group behavior based on graph search. We further conduct human experiments in security informatics domain to empirically evaluate our proposed method. The experimental results show the effectiveness of our method.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131403085","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}
{"title":"A cost-based FMEA decision tool for product quality design and management","authors":"Michael H. Wang","doi":"10.1109/ISI.2011.5984101","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984101","url":null,"abstract":"Failure Mode and Effect Analysis (FMEA) method has been a popular tool by the design and quality/reliability engineering profession for product design and quality/reliability improvement. Fundamentally, through the prioritized improvement targets suggested by FMEA, designers and engineers can improve the overall quality and reliability of either products or processes. The priority is based on a ranked compound score named Risk Priority Number (RPN) which is the product of three factors: occurrence, severity, and detection. However, one of the main disadvantages for FMEA is the fuzziness of assigning a value (zero to ten) toward the three factors which could be considered as subjective decision and the value may vary from person to person. In this article, we proposed the adoption of quality cost factors that are used to replace the ambiguous factors used in the traditional FMEA calculation. In addition, a Graphical-User-Interface (GUI) has been developed which can present the FMEA outcome in a cause-effect relationship figure rather than the traditional FMEA table-form format.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133308407","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}
{"title":"Compiling the marine environment spectrum based on inversion satellite remote sensing data","authors":"T. Zhang, W. Zhao, Xiao-Hua Yang, Z. Cai","doi":"10.1109/ISI.2011.5984113","DOIUrl":"https://doi.org/10.1109/ISI.2011.5984113","url":null,"abstract":"Through inversion of the satellite remote sensing data, the values of the environmental factors in the corresponding research area are obtained. By synthesizing the influence of marine environment on damage of the structure, equipment or system, the specific affecting factors in he research area have been determined, and the inversion result has been verified by the measured data. The problem in analyzing and processing large scale data has been solved by using the weight fuzzy clustering theory and the data trace technology, and the marine environment spectrum with more applicability has been established.","PeriodicalId":220165,"journal":{"name":"Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics","volume":"301 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134502642","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}