2013 European Intelligence and Security Informatics Conference最新文献_第5页

Exploiting Twitter for Border Security-Related Intelligence Gathering 利用推特进行边境安全相关情报收集

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.63

J. Piskorski, Hristo Tanev, A. Balahur

引用次数: 10

Increasing NER Recall with Minimal Precision Loss 以最小的精度损失增加NER召回率

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.23

J. Kuperus, C. Veenman, M. V. Keulen

引用次数: 7

Automated Counter-Terrorism 自动化的反恐

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.48

Leslie Ball, M. Craven

引用次数: 1

Cross Domain Assessment of Document to HTML Conversion Tools to Quantify Text and Structural Loss during Document Analysis 文档到HTML转换工具的跨域评估，以量化文档分析期间的文本和结构损失

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.22

Kyle Goslin, M. Hofmann

{"title":"Cross Domain Assessment of Document to HTML Conversion Tools to Quantify Text and Structural Loss during Document Analysis","authors":"Kyle Goslin, M. Hofmann","doi":"10.1109/EISIC.2013.22","DOIUrl":"https://doi.org/10.1109/EISIC.2013.22","url":null,"abstract":"During forensic text analysis, the automation of the process is key when working with large quantities of documents. As documents often come in a wide variety of different file types, this creates the need for tailored tools to be developed to analyze each document type to correctly identify and extract text elements for analysis without loss. These text extraction tools often omit sections of text that are unreadable from documents leaving drastic inconsistencies during the forensic text analysis process. As a solution to this a single output format, HTML, was chosen as a unified analysis format. Document to HTML/CSS extraction tools each with varying techniques to convert common document formats to rich HTML/CSS counterparts were tested. This approach can reduce the amount of analysis tools needed during forensic text analysis by utilizing a single document format. Two tests were designed, a 10 point document overview test and a 48 point detailed document analysis test to assess and quantify the level of loss, rate of error and overall quality of outputted HTML structures. This study concluded that tools that utilize a number of different approaches and have an understanding of the document structure yield the best results with the least amount of loss.","PeriodicalId":229195,"journal":{"name":"2013 European Intelligence and Security Informatics Conference","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115416855","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

Keystroke Biometric Studies on Password and Numeric Keypad Input 密码和数字键盘输入的击键生物识别研究

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.45

Ned Bakelman, John V. Monaco, Sung-Hyuk Cha, C. Tappert

引用次数: 26

Semi-automatic Ontology Maintenance in the Virtuoso News Monitoring System Virtuoso新闻监控系统中的半自动本体维护

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.29

F. Amardeilh, Wessel Kraaij, Martijn Spitters, C. Versloot, Sinan Yurtsever

引用次数: 5

Digital-Forensics Based Pattern Recognition for Discovering Identities in Electronic Evidence 基于数字取证的模式识别在电子证据中的身份发现

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.24

Hans Henseler, J. Hofste, M. V. Keulen

引用次数: 4

National Security and Social Media Monitoring: A Presentation of the EMOTIVE and Related Systems 国家安全和社会媒体监测:EMOTIVE和相关系统的介绍

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.38

M. Sykora, Thomas W. Jackson, A. O'Brien, Suzanne Elayan

{"title":"National Security and Social Media Monitoring: A Presentation of the EMOTIVE and Related Systems","authors":"M. Sykora, Thomas W. Jackson, A. O'Brien, Suzanne Elayan","doi":"10.1109/EISIC.2013.38","DOIUrl":"https://doi.org/10.1109/EISIC.2013.38","url":null,"abstract":"Today social media streams, such as Twitter, represent vast amounts of 'real-time' daily streaming data. Topics on these streams cover every range of human communication, ranging from banal banter, to serious reactions to events and information sharing regarding any imaginable product, item or entity. It has now become the norm for publicly visible events to break news over social media streams first, and only then followed by main stream media picking up on the news. It has been suggested in literature that social-media are a valid, valuable and effective real-time tool for gauging public subjective reactions to events and entities. Due to the vast big-data that is generated on a daily basis on social media streams, monitoring and gauging public reactions has to be automated and most of all scalable - i.e. human, expert monitoring is generally unfeasible. In this paper the EMOTIVE system, a project funded jointly by the DSTL (Defence Science and Technology Laboratory) and EPSRC, which focuses on monitoring fine-grained emotional responses relating to events of national security importance, will be presented. Similar systems for monitoring national security events are also presented and the primary traits of such national security social media monitoring systems are introduced and discussed.","PeriodicalId":229195,"journal":{"name":"2013 European Intelligence and Security Informatics Conference","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121754394","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: 19

Probability Analysis of Cyber Attack Paths against Business and Commercial Enterprise Systems 针对商业和商业企业系统的网络攻击路径概率分析

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.13

Dmitry Dudorov, D. Stupples, M. Newby

引用次数: 26

Countering Plagiarism by Exposing Irregularities in Authors' Grammar 通过揭露作者语法中的不规则性来打击剽窃

2013 European Intelligence and Security Informatics Conference Pub Date : 2013-08-12 DOI: 10.1109/EISIC.2013.10

Michael Tschuggnall, Günther Specht

{"title":"Countering Plagiarism by Exposing Irregularities in Authors' Grammar","authors":"Michael Tschuggnall, Günther Specht","doi":"10.1109/EISIC.2013.10","DOIUrl":"https://doi.org/10.1109/EISIC.2013.10","url":null,"abstract":"Unauthorized copying or stealing of intellectual propierties of others is a serious problem in modern society. In case of textual plagiarism, it becomes more and more easier to find appropriate sources using the huge amount of data available through online databases. To counter this problem, the two main approaches are categorized as external and intrinsic plagiarism detection, respectively. While external algorithms have the possibility to compare a suspicious document with numerous sources, intrinsic algorithms are allowed to solely inspect the suspicious document in order to predict plagiarism, which is important especially if no sources are available. In this paper we present a novel approach in the field of intrinsic plagiarism detection by analyzing syntactic information of authors and finding irregularities in sentence constructions. The main idea follows the assumption that authors have their mostly unconsciously used set of how to build sentences, which can be utilized to distinguish authors. Therefore the algorithm splits a suspicious document into single sentences, tags each word with part-of-speech (POS) classifiers and creates POS-sequences representing each sentence. Subsequently, the distance between every distinct pair of sentences is calculated by applying modified sequence alignment algorithms and stored into a distance matrix. After utilizing a Gaussian normal distribution function over the mean distances for each sentence, suspicious sentences are selected, grouped and predicted to be plagiarized. Finally, thresholds and parameters the algorithm uses are optimized by applying genetic algorithms. The approach has been evaluated against a large test corpus of English documents, showing promising results.","PeriodicalId":229195,"journal":{"name":"2013 European Intelligence and Security Informatics Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129042137","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