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A Survey of Intelligence Analysts' Perceptions of Analytic Tools 情报分析员对分析工具的看法的调查
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.26
Mandeep K. Dhami
{"title":"A Survey of Intelligence Analysts' Perceptions of Analytic Tools","authors":"Mandeep K. Dhami","doi":"10.1109/EISIC.2017.26","DOIUrl":"https://doi.org/10.1109/EISIC.2017.26","url":null,"abstract":"This article presents a survey of 278 intelligence analysts' views of fully operational analytic technologies and their newly developed replacements. It was found that usability was an important concept in analysts' reasons for and against using analytic tools. The perceived usability of a tool was not necessarily indicative of its perceived usefulness. Analysts' decisions to recommend an analytic tool to others were best predicted by how usable analysts perceived the tool to be rather than how useful they considered the tool to be. These findings have implications for the development and implementation of new analytic technologies in the intelligence community.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"5 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":"123686005","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: 1
Photometrix (TM): A Digital Seal for Offline Identity Picture Authentication Photometrix (TM):用于离线身份图片认证的数字印章
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.34
M. Pic, Amine Ouddan
{"title":"Photometrix (TM): A Digital Seal for Offline Identity Picture Authentication","authors":"M. Pic, Amine Ouddan","doi":"10.1109/EISIC.2017.34","DOIUrl":"https://doi.org/10.1109/EISIC.2017.34","url":null,"abstract":"Picture falsification on identity documents is a recurring problem. Text falsification can be mitigated on printed documents thanks to digital signature, but for picture the only safe strategy was to integrate an expensive electronic chip in the document. This paper proposes a low-cost alternative, allowing to check offline the authenticity of the image thanks to digitally signed characteristics extracted from the picture.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"10 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":"125313233","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: 3
Author Profiling in the Wild 《野外作家剖析
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.32
Lisa Kaati, Elias Lundeqvist, A. Shrestha, Maria Svensson
{"title":"Author Profiling in the Wild","authors":"Lisa Kaati, Elias Lundeqvist, A. Shrestha, Maria Svensson","doi":"10.1109/EISIC.2017.32","DOIUrl":"https://doi.org/10.1109/EISIC.2017.32","url":null,"abstract":"In this paper, we use machine learning for profiling authors of online textual media. We are interested in determining the gender and age of an author. We use two different approaches, one where the features are learned from raw data and one where features are manually extracted.We are interested in understanding how well author profiling works in the wild and therefore we have tested our models on different domains than they are trained on. Our results show that applying models to a different domain then they were trained on significantly decreases the performance of the models. The results show that more efforts need to be put into making models domain independent if techniques such as author profiling should be used operationally, for example by training on many different datasets and by using domain independent features.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"53 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":"114589915","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: 3
Gender Classification with Data Independent Features in Multiple Languages 基于数据独立特征的多语言性别分类
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.16
T. Isbister, Lisa Kaati, Katie Cohen
{"title":"Gender Classification with Data Independent Features in Multiple Languages","authors":"T. Isbister, Lisa Kaati, Katie Cohen","doi":"10.1109/EISIC.2017.16","DOIUrl":"https://doi.org/10.1109/EISIC.2017.16","url":null,"abstract":"Gender classification is a well-researched problem, and state-of-the-art implementations achieve an accuracy of over 85%. However, most previous work has focused on gender classification of texts written in the English language, and in many cases, the results cannot be transferred to different datasets since the features used to train the machine learning models are dependent on the data. In this work, we investigate the possibilities to classify the gender of an author on five different languages: English, Swedish, French, Spanish, and Russian. We use features of the word counting program Linguistic Inquiry and Word Count (LIWC) with the benefit that these features are independent of the dataset. Our results show that by using machine learning with features from LIWC, we can obtain an accuracy of 79% and 73% depending on the language. We also, show some interesting differences between the uses of certain categories among the genders in different languages.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"1079 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":"122894467","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: 9
A Monitoring Tool for Terrorism-Related Key-Players and Key-Communities in Social Media Networks 社会媒体网络中与恐怖主义有关的关键人物和关键社区的监测工具
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.41
Stelios Andreadis, Ilias Gialampoukidis, George Kalpakis, T. Tsikrika, S. Papadopoulos, S. Vrochidis, Y. Kompatsiaris
{"title":"A Monitoring Tool for Terrorism-Related Key-Players and Key-Communities in Social Media Networks","authors":"Stelios Andreadis, Ilias Gialampoukidis, George Kalpakis, T. Tsikrika, S. Papadopoulos, S. Vrochidis, Y. Kompatsiaris","doi":"10.1109/EISIC.2017.41","DOIUrl":"https://doi.org/10.1109/EISIC.2017.41","url":null,"abstract":"Terrorists communicate and disseminate their activitiesusing social media, such as Twitter, where complex networksof user accounts are formed and need to be effectively analysedby Law Enforcement Agencies (LEAs). To this end, we proposea novel visualisation tool that assists intelligence analysts andinvestigators through the presentation of the network formation,components, key-players, key-communities and through supportof keyword search in the terrorism domain, highlighting alsosuspended users and offering navigation in the user network","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"432 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":"122872022","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: 2
Detecting Crime Series Based on Route Estimation and Behavioral Similarity 基于路径估计和行为相似度的犯罪序列检测
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.10
Anton Borg, Martin Boldt, J. Eliasson
{"title":"Detecting Crime Series Based on Route Estimation and Behavioral Similarity","authors":"Anton Borg, Martin Boldt, J. Eliasson","doi":"10.1109/EISIC.2017.10","DOIUrl":"https://doi.org/10.1109/EISIC.2017.10","url":null,"abstract":"A majority of crimes are committed by a minority of offenders. Previous research has provided some support for the theory that serial offenders leave behavioral traces on the crime scene which could be used to link crimes to serial offenders. The aim of this work is to investigate to what extent it is possible to use geographic route estimations and behavioral data to detect serial offenders. Experiments were conducted using behavioral data from authentic burglary reports to investigate if it was possible to find crime routes with high similarity. Further, the use of burglary reports from serial offenders to investigate to what extent it was possible to detect serial offender crime routes. The result show that crime series with the same offender on average had a higher behavioral similarity than random crime series. Sets of crimes with high similarity, but without a known offender would be interesting for law enforcement to investigate further. The algorithm is also evaluated on 9 crime series containing a maximum of 20 crimes per series. The results suggest that it is possible to detect crime series with high similarity using analysis of both geographic routes and behavioral data recorded at crime scenes.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"22 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":"128722451","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: 2
Interpretable Probabilistic Divisive Clustering of Large Node-Attributed Networks 大节点属性网络的可解释概率分裂聚类
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.18
Lisa Kaati, Adam Ruul
{"title":"Interpretable Probabilistic Divisive Clustering of Large Node-Attributed Networks","authors":"Lisa Kaati, Adam Ruul","doi":"10.1109/EISIC.2017.18","DOIUrl":"https://doi.org/10.1109/EISIC.2017.18","url":null,"abstract":"Social network analysis is an important set of techniques that are used in many different areas. One such area is intelligence and law enforcement where social network analysis is used to study various kinds of networks. One of the problems with social networks that are extracted from social media is that easily becomes very large and as a consequence difficult to analyze. Therefore, there is a need for techniques that can divide a large network into smaller communities that are more feasible to analyze. Existing community detection algorithms usually only focus on creating communities based on the underlying networks structure and therefore it can be hard to interpret the meaning of communities.In this work, we present two methods for community detection that allows a user to detect communities with an underlying meaning not only based on the relations in the network but also on attributes of the nodes. Our methods use iterative approaches that allow the user to define meaningful properties and are applicable on large social networks with attributed nodes.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"43 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":"128075276","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: 1
Customs Risk Analysis through the ConTraffic Visual Analytics Tool 通过ConTraffic可视化分析工具进行海关风险分析
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.22
M. Poulymenopoulou, A. Tsois
{"title":"Customs Risk Analysis through the ConTraffic Visual Analytics Tool","authors":"M. Poulymenopoulou, A. Tsois","doi":"10.1109/EISIC.2017.22","DOIUrl":"https://doi.org/10.1109/EISIC.2017.22","url":null,"abstract":"Customs risk analysis is crucial for detecting fraud and contraband goods in the massive flows of internationally traded goods. Most of non-bulk goods are transported in shipping containers and, as customs can control only about 2% of them, efficient customs risk analysis is crucial. In support to EU customs, the Joint Research Centre of the European Commission has developed the ConTraffic visual analytics research prototype that is currently used by EU customs on an experimental basis. This paper presents the main architectural elements of this application and some of the custom-made visualization and user-interaction techniques employed in order to help customs explore the large volumes of shipping container data and perform route-based risk analysis. Moreover, we validate the usefulness of this application with illustrative examples of route-based risk analysis workflows than can be performed with our system.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"57 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120818438","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
IoT Data Profiles: The Routines of Your Life Reveals Who You Are 物联网数据简介:你的日常生活揭示了你是谁
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.17
Johan Fernquist, Torbjorn Fangstrom, Lisa Kaati
{"title":"IoT Data Profiles: The Routines of Your Life Reveals Who You Are","authors":"Johan Fernquist, Torbjorn Fangstrom, Lisa Kaati","doi":"10.1109/EISIC.2017.17","DOIUrl":"https://doi.org/10.1109/EISIC.2017.17","url":null,"abstract":"Preserving privacy is getting more and more important. The new EU general data protection regulation (GDPR) which will apply from May 2018 will introduce developments to some areas of EU data protection law and increase the privacy and personal integrity by strengthen and unify data protection for all individuals in EU. GDPR will most likely have an impact on many organizations and put pressure on many organizations that handle data.In this work, we investigate to what extent data profiles consisting of data from connected things can be used to identify a user. We use time and event profiles that can be created based on when, where and how a user communicates and uses digital devices. Our results show that such data profiles can be used to identify individuals and that collecting and creating data profiles of users can be seen as a serious threat towards privacy and personal integrity.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"1 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":"128774076","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: 6
An Integrated Framework for the Timely Detection of Petty Crimes 及时发现轻微罪行的综合框架
2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI: 10.1109/EISIC.2017.13
N. Dimitriou, G. Kioumourtzis, A. Sideris, G. Stavropoulos, Evdoxia Taka, N. Zotos, G. Leventakis, D. Tzovaras
{"title":"An Integrated Framework for the Timely Detection of Petty Crimes","authors":"N. Dimitriou, G. Kioumourtzis, A. Sideris, G. Stavropoulos, Evdoxia Taka, N. Zotos, G. Leventakis, D. Tzovaras","doi":"10.1109/EISIC.2017.13","DOIUrl":"https://doi.org/10.1109/EISIC.2017.13","url":null,"abstract":"While petty crimes are considered misdemeanors from a judicial point of view and are typically punished with light sentences, they greatly affect citizens' perception of safety and are related to substantial financial losses. In this paper, we describe a technological solution for the timely detection of petty crimes, based on the developments of the EU project P-REACT. Concretely, a modular framework is presented where an embedded system processes in-situ a camera stream for the real-time detection of petty criminality incidents and the timely notification of authorities. This paper provides details on the various hardware options and the key software components of the system, which include a set of appropriately implemented video analytics algorithms for the detection of different petty crimes as well as modules for the capturing, transcoding and secure transmission of video clips in case of an alarm. An evaluation of the system is also provided covering both experimental results on the accuracy of the platform but also focusing on the feedback received during the trials phase of P-REACT through the participation of external stakeholders. Evaluation during this phase was based on the live demonstration of system's operation in a series of simulated events corresponding to different types of petty crimes. In both cases evaluation results were very promising, attesting to the high innovation potential of the platform.","PeriodicalId":436947,"journal":{"name":"2017 European Intelligence and Security Informatics Conference (EISIC)","volume":"05 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":"129416609","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: 8
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