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Intelligence and Security Informatics Conference (EISIC), 2011 European

Date 12-14 Sept. 2011

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Displaying Results 1 - 25 of 90
  • [Front cover]

    Page(s): C1
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  • [Title page i]

    Page(s): i
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  • [Title page iii]

    Page(s): iii
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  • [Copyright notice]

    Page(s): iv
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  • Table of contents

    Page(s): v - x
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  • Message from the General Chairs of EISIC 2011

    Page(s): xi
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  • Message from the Program Co-Chairs of EISIC 2011

    Page(s): xii
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  • Message from the General Chairs of OSINT-WM 2011

    Page(s): xiii
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  • Message from the Program Chairs of OSINT-WM 2011

    Page(s): xiv
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  • EISIC 2011 Organizers

    Page(s): xv
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  • EISIC 2011 Program Committee and Reviewers

    Page(s): xvi - xvii
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  • EISIC 2011 Sponsors

    Page(s): xviii
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  • OSINT-WM 2011 Organizers

    Page(s): xix
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  • OSINT-WM 2011 Program Committee

    Page(s): xx
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  • Dark Web: Exploring and Mining the Dark Side of the Web

    Page(s): 1 - 2
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (186 KB) |  | HTML iconHTML  

    This talk will review the emerging research in Terrorism Informatics based on a web mining perspective. Recent progress in the internationally renowned Dark Web project will be reviewed, including: deep/dark web spidering (web sites, forums, Youtube, virtual worlds), web metrics analysis, dark network analysis, web-based authorship analysis, and sentiment and affect analysis for terrorism tracking. In collaboration with selected international terrorism research centers and intelligence agencies, the Dark Web project has generated one of the largest databases in the world about extremist/terrorist-generated Internet contents (web sites, forums, blogs, and multimedia documents). Dark Web research has received significant international press coverage, including: Associated Press, USA Today, The Economist, NSF Press, Washington Post, Fox News, BBC, PBS, Business Week, Discover magazine, WIRED magazine, Government Computing Week, Second German TV (ZDF), Toronto Star, and Arizona Daily Star, among others. Recent Dark Web research includes: (1) epidemiological and social network modeling of internet radicalization and violent intents; (2) Dark Web Forum Portal and Video Portal for researchers and analysts; and (3) Geopolitical Web research of social media and news tracking for multi-cultural at-risk regions. View full abstract»

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  • Computational Criminology

    Page(s): 3
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (147 KB) |  | HTML iconHTML  

    Crime and terrorism in the 21st century call for advancement in the modeling and simulation of criminal events in the complex environment. This presentation reviews the field of computational criminology, an emerging blend of criminology, computer science and applied mathematics. Modern concerns about public safety and security include a focus on a range of events from less serious everyday crimes like shoplifting through to personal violent crimes like homicide and ultimately to terrorism. Underlying all of these events is a decision process or chain of steps in target identification, steps that focus first on rough and vague decisions and move towards the precise. Minor and major crimes involve people moving about in a known space in identifiable patterns to find weaknesses. The field of computational criminology involves using computational power to identify: (1) patterns and emerging patterns; (2) crime generators and crime attractors; (3) terrorist, organized crime and gang social and spatial networks as well as co-offending networks; and, (4) cybercrime. Algorithms are developed using computational topology, hyper-graphs, SNA, KDD, agent based simulations, dynamic information systems analysis and more. This presentation is designed to provide information about crime pattern theory, pattern identification and research in computational criminology. It is designed to identify research areas of potential interest to participants at the conference. Computational criminology is an emerging field that is opening doors for new and innovative approaches. The presentation will show how people (offenders and non-offenders) move about in space with a routine time and location chronologies (in physical and internet space). Anchor points develop; primary routes emerge. Navigation and rules for navigation shape both commuting patterns; shopping patterns; web sites-forums, blogs, and shared information; and crime and terrorism patterns. Crime and terrorism are not - - random; they appear to follow rules similar to those in many types of non-criminal behavior. Better understanding these rules and developing appropriate algorithms for identifying risky areas is the continuing focus of computational criminology. View full abstract»

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  • Data Mining for Malicious Code Detection and Security Applications

    Page(s): 4 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (165 KB) |  | HTML iconHTML  

    Summary form only given. Data mining is the process of posing queries and extracting patterns, often previously unknown from large quantities of data using pattern matching or other reasoning techniques. Data mining has many applications in security including for national security as well as for cyber security. The threats to national security include attacking buildings, destroying critical infrastructures such as power grids and telecommunication systems. Data mining techniques are being investigated to find out who the suspicious people are and who is capable of carrying out terrorist activities. Cyber security is involved with protecting the computer and network systems against corruption due to Trojan horses, worms and viruses. Data mining is also being applied to provide solutions such as intrusion detection and auditing. The first part of the presentation will discuss my joint research with Prof. Latifur Khan and our students at the University of Texas at Dallas on data mining for cyber security applications. For example, anomaly detection techniques could be used to detect unusual patterns and behaviors. Link analysis may be used to trace the viruses to the perpetrators. Classification may be used to group various cyber attacks and then use the profiles to detect an attack when it occurs. Prediction may be used to determine potential future attacks depending in a way on information learned about terrorists through email and phone conversations. Data mining is also being applied for intrusion detection and auditing. Other applications include data mining for malicious code detection such as worm detection and managing firewall policies. This second part of the presentation will discuss the various types of threats to national security and describe data mining techniques for handling such threats. Threats include non real-time threats and real time threats. We need to understand the types of threats and also gather good data to carry out mining and obtain usef- - ul results. The challenge is to reduce false positives and false negatives. The third part of the presentation will discuss some of the research challenges. We need some form of real-time data mining, that is, the results have to be generated in real-time, we also need to build models in real-time for real-time intrusion detection. Data mining is also being applied for credit card fraud detection and biometrics related applications. While some progress has been made on topics such as stream data mining, there is still a lot of work to be done here. Another challenge is to mine multimedia data including surveillance video. Finally, we need to maintain the privacy of individuals. Much research has been carried out on privacy preserving data mining. In summary, the presentation will provide an overview of data mining, the various types of threats and then discuss the applications of data mining for malicious code detection and cyber security. Then we will discuss the consequences to privacy. View full abstract»

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  • Desktop Text Mining for Open Source Intelligence

    Page(s): 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (108 KB) |  | HTML iconHTML  

    Summary form only given. The use of the Internet permeates more and more areas of our daily life. People share and use information in forums and social networks in ways unimaginable just a few years ago. This fantastic medium with global reach, easy access and fast information propagation is, unfortunately, also often a tool for illegal activities. Especially in areas like commercial fraud a huge increase of criminal acts can be observed. To meet these challenges, law enforcement authorities need to build and reinforce capabilities in the domain of OSINT. Characteristics of the Internet like the volume of available data, the plurality of languages and the speed of change make it difficult for public authorities to keep pace. The OPTIMA group of the Joint Research Centre (JRC) does research in the field of open source information extraction and text mining. As part of this research it develops tools which can be used in operational settings. As part of its mission to provide scientific and technical support to EU policies, these tools are provided to law enforcement authorities in Member States of the European Union. The first part of the talk will give an overview of our research in information extraction and text mining. Furthermore, our desktop text mining tool, EMM OSINT Suite, which is in use by law enforcement authorities in Europe, will be presented. Our "lessons learned" with relevance to the research community will be shared. The second part will discuss the impact of general trends in internet technology and research on our work now and in the future. View full abstract»

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  • Discovering Complex Networks of Events and Relations in News Surveillance

    Page(s): 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (107 KB) |  | HTML iconHTML  

    When faced with the need for analyzing vast streams of on-line text data, we require methods that go well beyond keyword-based queries. Large-scale surveillance of on-line news streams requires an understanding of the text on a deeper level than is afforded by names and keywords alone, it becomes essential to understand complex interactions among the entities relationships and events. We will discuss the interplay between two aspects of this kind of deep analysis: a. how to extract knowledge from text "upstream" and b. how that knowledge may be utilized in downstream applications. We will use as live examples several systems in different application domains: cross-border crime and security, epidemiological surveillance, and business intelligence. We will present the experiences from the development of such systems and from interaction with real-world users, who are experts in their respective domains. View full abstract»

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  • Visualisation for Decision-Makers

    Page(s): 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (105 KB) |  | HTML iconHTML  

    Summary form only given. How should we communicate the results of our analysis to decision-makers? This talk will argue that visualisations and infographics can play a very important role, not only for analytical processes of data analysts, but also for explaining our analytical results to decision-makers at the highest of levels. Some care must be taken to avoid various common pitfalls when designing such visuals: the talk will cover bad examples as well as good in order to uncover design guidelines and practical advice for those wishing to pursue a more visual approach. View full abstract»

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  • Who, What, When, Where and How: Semantics Semantics Help Connect the Dots

    Page(s): 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (126 KB) |  | HTML iconHTML  

    Summary form only given. In this session you will learn: to leverage semantic technology to bring information and intelligence from around the Web, inside your operation. Semantic technology can improve on your traditional data management methods through better data identification, classification, mapping and evaluation. Semantic Web technology can provide a window into how people, places, things and events come together into both threats and opportunities, adding a semantic layer to your existing intelligence platform supports the strategic process of intelligence gathering and data analysis. Semantics can help in cyber security and threat detection with semantic-based classification, filtering, data mining, and meta-tagging to expose non-obvious relationships. View full abstract»

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  • Engineering Situation Analysis Decision Support Systems

    Page(s): 10 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2397 KB) |  | HTML iconHTML  

    This paper explores a new approach to model-driven engineering (MDE) of situation analysis decision support systems for Marine Safety & Security Operations. Realistic situation analysis scenarios routinely deal with complex dynamic situations involving multiple mobile agents and events distributed in space and time. The work presented here builds on Abstract State Machine (ASM) modeling paired with CoreASM tool support to analyze and validate ASM models experimentally. The proposed approach facilitates analysis of the problem space and supports reasoning about design decisions and conformance criteria so as to ensure they are properly established and well understood prior to building the system. We provide an extension to Core ASM for the Marine Safety & Security domain, specifically for capturing rendezvous scenarios and illustrate the application of the proposed modeling approach using sample scenarios. View full abstract»

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  • Law Enforcement Ontology for Identification of Related Information of Interest Across Free Text Dcouments

    Page(s): 19 - 27
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (939 KB) |  | HTML iconHTML  

    A law enforcement ontology that incorporates extensions such as Thesauri, specialized rules, abductive hypothesis and process modeling for expansion of extracted entity phrases, is described. The ontology is part of a project to facilitate automated, reliable identification of related information of interest found in law enforcement-related free-text documents. Results of testing on a complex, real-world law enforcement dataset show that the addition of the ontology significantly improves the expanded entity phrase extraction used for the identification of related information of interest in free-text documents and merits additional expansion. Future work will add semantic inference and insertion functions and extend the specialized rules and abductive hypotheses components. View full abstract»

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  • Cybercrime: Awareness and Fear: Slovenian Perspectives

    Page(s): 28 - 33
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (333 KB) |  | HTML iconHTML  

    In this paper the Slovene perspective on the perception of cyber crime in terms of awareness and fear is presented. On the basis of theoretical knowledge the online survey has been prepared and conducted. The results of the perception of cyber crime and its understanding have been analyzed. The results and their interpretations are the basis for further work with the cyberspace users. Based on the results some guidelines on how to raise awareness, reduce risk and thereby reduce the fear of cyber crime in Slovenia are given. View full abstract»

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  • U.S. and EU Legislation on Cybercrime

    Page(s): 34 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (187 KB) |  | HTML iconHTML  

    The advent of Internet technologies has created global cyber crime problems. Cyber crimes affect all of us at the time when online transactions are in billions of dollars per year and cyber criminals are costing e-commerce billions of dollars in damages [1]. These are the components of cyber crime through which cyber criminals have perpetrated these areas: hacking, distributed denial-of-service, phishing, spoofing, identity theft and credit card fraud which have increased in frequency over time. As e-commerce and online businesses are dominating today's business world and as new technologies emerges cyber crime has a bigger impact on the global economy. The U.S. legal systems and law enforcement agencies seem to be lagging behind in their efforts to capture and prosecute cyber criminals. This paper reviews both U.S. and EU cyber legislations and how effective they are in controlling cyber crimes. The factors affecting U.S. from taking a leadership role in fighting cyber crime is reviewed. EU legislations are compared to see if U.S. can benefit from EU Convention approach. View full abstract»

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