2018 European Intelligence and Security Informatics Conference (EISIC)最新文献_第2页

Digital Transformation in Border Checks: Mapping Border Guard Training in Automated Processes 边境检查的数字化转型:在自动化过程中绘制边境警卫培训

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-10-01 DOI: 10.1109/EISIC.2018.00017

Laura Salmela, Sirra Toivonen, Minna Kulju, Mari Ylikauppila

{"title":"Digital Transformation in Border Checks: Mapping Border Guard Training in Automated Processes","authors":"Laura Salmela, Sirra Toivonen, Minna Kulju, Mari Ylikauppila","doi":"10.1109/EISIC.2018.00017","DOIUrl":"https://doi.org/10.1109/EISIC.2018.00017","url":null,"abstract":"Automated border control represents one area in the digital transformation of border control. It is gradually becoming a commonplace particularly at air borders, where the concept of self-service has had the strongest business case also in other steps of the passenger's journey, such as check-in or baggage drop. Besides providing a means to enhance efficiency and security in passenger clearing processes, the new technology significantly reshapes current ways of conducting border checks from employee perspective. Successful implementation of automated border check technologies thus demands border organizations to equip their workforce with new skills and remodel existing ones. This paper presents a preliminary analysis on current technology training of border guards and assesses its effects on how the new technology is received among employees at the frontline. The results are based on field studies conducted in five EU member states. The study loosely applies a Technology Training Model that extends traditional Technology Acceptance Model by incorporating training as an additional variable to explain employee intention to use new technology.","PeriodicalId":110487,"journal":{"name":"2018 European Intelligence and Security Informatics Conference (EISIC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128921407","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

Using Wearable Device Data in a Criminal Investigation: A Preliminary Study 在刑事调查中使用可穿戴设备数据:初步研究

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-10-01 DOI: 10.1109/EISIC.2018.00023

Sarah McNary, Aaron Hunter

引用次数: 0

Optical Covert Channel from Air-Gapped Networks via Remote Orchestration of Router/Switch LEDs 通过路由器/开关led的远程编排从气隙网络的光隐蔽通道

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-10-01 DOI: 10.1109/EISIC.2018.00016

Mordechai Guri

引用次数: 4

Policing The Cyber Threat: Exploring the Threat from Cyber Crime and the Ability of Local Law Enforcement to Respond 网络威胁的监管:探讨网络犯罪的威胁和地方执法部门的应对能力

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-10-01 DOI: 10.1109/EISIC.2018.00011

M. Hull, Ted C. Eze, Lee Speakman

引用次数: 2

Towards Mobile Contactless 4-Fingerprint Authentication for Border Control 面向边境管制的移动非接触式4指纹认证

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-10-01 DOI: 10.1109/EISIC.2018.00020

Axel Weissenfeld, A. Zoufal, Christoph Weiß, B. Strobl, G. F. Domínguez

引用次数: 6

Inferring Demographic Data of Marginalized Users in Twitter with Computer Vision APIs 用计算机视觉api推断Twitter边缘用户的人口统计数据

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-10-01 DOI: 10.1109/EISIC.2018.00022

Panos Kostakos, Abhinay Pandya, Olga Kyriakouli, M. Oussalah

{"title":"Inferring Demographic Data of Marginalized Users in Twitter with Computer Vision APIs","authors":"Panos Kostakos, Abhinay Pandya, Olga Kyriakouli, M. Oussalah","doi":"10.1109/EISIC.2018.00022","DOIUrl":"https://doi.org/10.1109/EISIC.2018.00022","url":null,"abstract":"Inferring demographic intelligence from unlabeled social media data is an actively growing area of research, challenged by low availability of ground truth annotated training corpora. High-accuracy approaches for labeling demographic traits of social media users employ various heuristics that do not scale up and often discount non-English texts and marginalized users. First, we present a framework for inferring the demographic attributes of Twitter users from their profile pictures (avatars) using the Microsoft Azure Face API. Second, we measure the inter-rater agreement between annotations made using our framework against two pre-labeled samples of Twitter users (N1=1163; N2=659) whose age labels were manually annotated. Our results indicate that the strength of the inter-rater agreement (Gwet's AC1=0.89; 0.90) between the gold standard and our approach is ‘very good’ for labelling the age group of users. The paper provides a use case of Computer Vision for enabling the development of large cross-sectional labeled datasets, and further advances novel solutions in the field of demographic inference from short social media texts.","PeriodicalId":110487,"journal":{"name":"2018 European Intelligence and Security Informatics Conference (EISIC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133617719","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

On Wash Trade Detection in Energy Markets 论能源市场的洗仓交易检测

2018 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2018-04-17 DOI: 10.1109/EISIC.2018.00018

U. Akhmedov

{"title":"On Wash Trade Detection in Energy Markets","authors":"U. Akhmedov","doi":"10.1109/EISIC.2018.00018","DOIUrl":"https://doi.org/10.1109/EISIC.2018.00018","url":null,"abstract":"A wash trade in energy markets refers to entering into arrangements for the sale or purchase of a financial or physical instrument, a related spot commodity contract, or an auctioned product based on emission allowances, where there is no change in beneficial interests or market risk or where beneficial interest or market risk is transferred between parties who are acting in concert or collusion. Market abuse scenarios such as wash trade compromise the efficiency and integrity of energy markets. The research of abusive trading behavior in financial markets is well ahead of peers in energy markets. Effective solutions for monitoring abusive scenarios such as wash trade in energy markets are yet to be developed. This paper describes a practical implementation example of detecting wash trade behavior in energy markets using simple techniques. An easily reusable method is then proposed to detect the potential wash trade activities involved in an instrument by first detecting trades resulting in no overall change in market risk and then further identifying the collusive behavior between the counterparties. The proposed method is tested and evaluated on energy instruments order data sets from the Trayport trading platform. We find that the proposed approach can effectively detect all primary wash trade indicators across energy instruments.","PeriodicalId":110487,"journal":{"name":"2018 European Intelligence and Security Informatics Conference (EISIC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121840704","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