2017 European Intelligence and Security Informatics Conference (EISIC)最新文献

Behavioural Markers: Bridging the Gap between Art of Analysis and Science of Analytics in Criminal Intelligence 行为标记:弥合犯罪情报中分析艺术与分析科学之间的鸿沟

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-12-28 DOI: 10.1109/EISIC.2017.30

Junayed Islam, B. Wong

引用次数: 0

Comparative Analysis of Crime Scripts: One CCTV Footage—Twenty-One Scripts 犯罪剧本的比较分析:一个CCTV录像- 21个剧本

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-11 DOI: 10.1109/EISIC.2017.23

H. Borrion, Hashem Dehghanniri, Yuanxi Li

引用次数: 4

How Analysts Think: How Do Criminal Intelligence Analysts Recognise and Manage Significant Information? 分析人员如何思考:犯罪情报分析人员如何识别和管理重要信息?

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-11 DOI: 10.1109/EISIC.2017.15

C. Groenewald, B. Wong, S. Attfield, P. Passmore, N. Kodagoda

引用次数: 5

A Framework for Measuring Imagination in Visual Analytics Systems 视觉分析系统中测量想象力的框架

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.31

M. Bedek, A. Nussbaumer, Eva-Catherine Hillemann, D. Albert

引用次数: 0

Catchem: A Browser Plugin for the Panama Papers Using Approximate String Matching

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.28

Panos Kostakos, Miika Moilanen, Arttu Niemela, M. Oussalah

引用次数: 0

Towards a Breakthrough Speaker Identification Approach for Law Enforcement Agencies: SIIP 面向执法机构的突破性说话人识别方法:SIIP

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.14

Khaled Khelif, Yann Mombrun, G. Backfried, Farhan Sahito, L. Scarpato, P. Motlícek, S. Madikeri, Damien Kelly, Gideon Hazzani, Emmanouil Chatzigavriil

引用次数: 8

How the Use of Ethically Sensitive Information Helps to Identify Co-Offenders via a Purposed Privacy Scale: A Pilot Study 如何使用道德敏感信息帮助识别共犯通过一个有目的的隐私量表:一项试点研究

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.35

Pragya Paudyal, C. Rooney, N. Kodagoda, B. Wong, P. Duquenoy, Nadeem Qazi

{"title":"How the Use of Ethically Sensitive Information Helps to Identify Co-Offenders via a Purposed Privacy Scale: A Pilot Study","authors":"Pragya Paudyal, C. Rooney, N. Kodagoda, B. Wong, P. Duquenoy, Nadeem Qazi","doi":"10.1109/EISIC.2017.35","DOIUrl":"https://doi.org/10.1109/EISIC.2017.35","url":null,"abstract":"Police analysts increasingly use data analysis techniques to make decisions that have an impact on society. Previous research shows that excluding ethically sensitive information (features) such as name, surname, address etc. during the data analysis process has implications for accuracy and decision-making, which may have negative consequences affecting individuals or a group within society. To assess whether the use of ethically sensitive features has implications for decision-making, we identified two important aspects: (i) transparency of the feature selection, and (ii) a way of assessing the impact of the selected features. In this paper, we define ethically sensitive information from two aspects: (a) features that identify an individual, known as personally identifiable information, and (b) sensitive features that discriminate against the individual, known as prejudice information. We investigate whether the selection of these features has an impact on accurately identifying co-offenders. For this, we propose a privacy scale, which consists of a value for each feature depending on the label of their sensitivity. To explore this, we used an anonymized dataset received from a UK law enforcement agency. Ground truths samples with known co-offender were selected for this study. We used the clustering algorithm K-MODE and included and excluded features that included personal, prejudice and other attributes to assess the relationship between the privacy score of the combined input attributes and the accuracy of the clustering. The results suggest that the use of ethically sensitive features does have an impact on correctly identifying potential co-offenders more accurately.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114579651","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: 0

An Inconvenient Truth: Algorithmic Transparency & Accountability in Criminal Intelligence Profiling 一个难以忽视的真相:刑事情报分析中的算法透明度和问责制

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.12

Erik T. Zouave, Thomas Marquenie

引用次数: 8

Cyber Threat Intelligence Model: An Evaluation of Taxonomies, Sharing Standards, and Ontologies within Cyber Threat Intelligence 网络威胁情报模型:网络威胁情报中的分类、共享标准和本体论的评估

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.20

Vasileios Mavroeidis, Siri Bromander

{"title":"Cyber Threat Intelligence Model: An Evaluation of Taxonomies, Sharing Standards, and Ontologies within Cyber Threat Intelligence","authors":"Vasileios Mavroeidis, Siri Bromander","doi":"10.1109/EISIC.2017.20","DOIUrl":"https://doi.org/10.1109/EISIC.2017.20","url":null,"abstract":"Threat intelligence is the provision of evidence-based knowledge about existing or potential threats. Benefits of threat intelligence include improved efficiency and effectiveness in security operations in terms of detective and preventive capabilities. Successful threat intelligence within the cyber domain demands a knowledge base of threat information and an expressive way to represent this knowledge. This purpose is served by the use of taxonomies, sharing standards, and ontologies.This paper introduces the Cyber Threat Intelligence (CTI) model, which enables cyber defenders to explore their threat intelligence capabilities and understand their position against the ever-changing cyber threat landscape. In addition, we use our model to analyze and evaluate several existing taxonomies, sharing standards, and ontologies relevant to cyber threat intelligence. Our results show that the cyber security community lacks an ontology covering the complete spectrum of threat intelligence. To conclude, we argue the importance of developing a multi-layered cyber threat intelligence ontology based on the CTI model and the steps should be taken under consideration, which are the foundation of our future work.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114065863","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: 164

Can an Automatic Tool Assess Risk of Radicalization Online? A Case Study on Facebook 自动工具能评估在线激进化风险吗?以Facebook为例

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.36

J. Torregrosa, Irene Gilpérez-López, R. Lara-Cabrera, David Garriga, David Camacho

引用次数: 2