{"title":"Evolving Block-Based Neural Network and Field Programmable Gate Arrays for Host-Based Intrusion Detection System","authors":"Quang-Anh Tran, F. Jiang, Quang Minh Ha","doi":"10.1109/KSE.2012.31","DOIUrl":"https://doi.org/10.1109/KSE.2012.31","url":null,"abstract":"In this paper, we design a prototype with hybrid software-enabled detection engine on the basis of an evolving block-based neural network (BBNN), and integrate it with a Field Programmable Gate Arrays (FPGA) board to enable a real-time host-based intrusion detection system (IDS). The established prototype can feed sequence of system calls obtained from a server directly into the BBNN based IDS. The structure and weights of BBNN are evolved by Genetic Algorithms. Experimental performance comparisons have been conducted against four major Support Vector Machines (SVMs) by carrying out leave-one-out cross validation. The results show that the improved BBNN outperforms other algorithms with respect to the classification and detection performances. The false alarm rate is successfully reduced as low as 2.22% while the detection rate 100% is still maintained. The running times of the proposed hardware based IDS versus other software based systems are also discussed.","PeriodicalId":122680,"journal":{"name":"2012 Fourth International Conference on Knowledge and Systems Engineering","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133693698","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 Pessimistic Approach for Solving a Multi-criteria Decision Making","authors":"Hieu Nguyen Van, L. Utkin, D. D. Thang","doi":"10.1109/KSE.2012.12","DOIUrl":"https://doi.org/10.1109/KSE.2012.12","url":null,"abstract":"An extension of the DS/AHP method in the paper. The extension assumes that expert judgments concerning the criteria are often imprecise and incomplete. The proposed extension also uses groups of experts or decision makers for comparing decision alternatives and criteria. However, it does not require assigning favorable values for different groups of decision alternatives and criteria. The computation procedure for processing and aggregating the incomplete information about criteria and decision alternatives is reduced to solving a finite set of linear programming problems. Main results are explained and illustrated by numerical examples.","PeriodicalId":122680,"journal":{"name":"2012 Fourth International Conference on Knowledge and Systems Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133872526","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":"Exploring Neighborhood Influence in Text Classification","authors":"N. Le, T. Tran, M. Tran","doi":"10.1109/KSE.2012.35","DOIUrl":"https://doi.org/10.1109/KSE.2012.35","url":null,"abstract":"Standard supervised learning approaches have been widely applied on the text classification problem. These standard approaches exploit only the local content of the document. However, the additional information in the relationship between the items can be used to improve the overall accuracy of the classification process. To make use of this information, the authors propose a statistical model to capture both the contents and labels from each link the neighborhood. This link model is then incorporated with the Markov Random Field model to form the soft labeling model for text classification. This new approach has combined both the local content and the influence from the neighborhood. The results of soft labeling model on standard data sets are also promising. Moreover, the new model can be applied on not only the text classification problem but also many kinds of richly structured data sets.","PeriodicalId":122680,"journal":{"name":"2012 Fourth International Conference on Knowledge and Systems Engineering","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117243125","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}
Mai-Vu Tran, M. Nguyen, Sy-Quan Nguyen, Minh-Tien Nguyen, X. Phan
{"title":"VnLoc: A Real -- Time News Event Extraction Framework for Vietnamese","authors":"Mai-Vu Tran, M. Nguyen, Sy-Quan Nguyen, Minh-Tien Nguyen, X. Phan","doi":"10.1109/KSE.2012.34","DOIUrl":"https://doi.org/10.1109/KSE.2012.34","url":null,"abstract":"Event Extraction is a complex and interesting topic in Information Extraction that includes event extraction methods from free text or web data. The result of event extraction systems can be used in several fields such as risk analysis systems, online monitoring systems or decide support tools. In this paper, we introduce a method that combines lexico -- semantic and machine learning to extract event from Vietnamese news. Furthermore, we concentrate to describe event online monitoring system named VnLoc based on the method that was proposed above to extract event in Vietnamese language. Besides, in experiment phase, we have evaluated this method based on precision, recall and F1 measure. At this time of experiment, we on investigated on three types of event: FIRE, CRIME and TRANSPORT ACCIDENT.","PeriodicalId":122680,"journal":{"name":"2012 Fourth International Conference on Knowledge and Systems Engineering","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124782463","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}