Proceedings of the 16th International Conference on Availability, Reliability and Security最新文献

Network Intrusion Detection in the Wild - the Orange use case in the SIMARGL project 野外的网络入侵检测——sigml项目中的Orange用例

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3470091

Mikołaj Komisarek, M. Pawlicki, M. Kowalski, A. Marzecki, R. Kozik, M. Choraś

引用次数: 2

Building Open Source Cyber Range To Teach Cyber Security 构建开源网络范围以教授网络安全

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3469188

Tomáš Lieskovan, J. Hajny

引用次数: 5

A Formal Analysis of EnOcean’s Teach-in and Authentication EnOcean教学与认证的形式化分析

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3470097

Katharina Hofer-Schmitz

引用次数: 3

SecTULab: A Moodle-Integrated Secure Remote Access Architecture for Cyber Security Laboratories SecTULab:用于网络安全实验室的模块化集成安全远程访问架构

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3470034

J. Fabini, Alexander Hartl, Fares Meghdouri, Claudia Breitenfellner, T. Zseby

引用次数: 2

Fighting organized crime by automatically detecting money laundering-related financial transactions 通过自动侦测与洗钱有关的金融交易，打击有组织犯罪

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3469196

A. Tundis, Soujanya Nemalikanti, M. Mühlhäuser

{"title":"Fighting organized crime by automatically detecting money laundering-related financial transactions","authors":"A. Tundis, Soujanya Nemalikanti, M. Mühlhäuser","doi":"10.1145/3465481.3469196","DOIUrl":"https://doi.org/10.1145/3465481.3469196","url":null,"abstract":"Money laundering is the set of operations aimed at giving a legitimate appearance to capital whose origin is illegal, thus making it more difficult to identify and subsequently recover it. It is one of the phenomena on which the so-called underground economy relies and therefore constitutes a crime for which the charge for money laundering applies. For supporting the fight against this phenomenon, the interest towards analysis models for Anti-Money Laundering (AML) based on a combined use of automatic tools and artificial intelligence (AI) techniques increases, as it is also shown by the European Central Bank (ECB) during recent press conferences. Following this direction, this paper proposes a model for enhancing the detection of suspicious transactions related to money laundering. It is based on a set of features that are defined by considering different aspects such as the time, the amount of money, number of transactions, type of operations and level of internationalization. An AI-based computational approach centered on Machine Learning (ML) techniques has been adopted to evaluate the goodness of such feature-based model, in supporting the automatic detection of suspicious transactions, by experimenting 5 different classifiers. From the experiments emerged that the Random Forest provided the best performance not only among the classifiers tested within the paper, but also in comparison to those presented in the related work with an accuracy, a recall and f1-score greater than 94% by decreasing the False Positive Rate (FPR). Furthermore, an analysis on the feature importance has been provided, to understand which feature, among the proposed ones, plays the major role in such application domain.","PeriodicalId":417395,"journal":{"name":"Proceedings of the 16th International Conference on Availability, Reliability and Security","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114197307","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

Template Protected Authentication based on Location History and b-Bit MinHash 基于位置历史和b-Bit MinHash的模板保护认证

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3470473

Masakazu Fujio, Kenta Takahashi, Yosuke Kaga, Wataru Nakamura, Yoshiko Yasumura, R. Yamaguchi

{"title":"Template Protected Authentication based on Location History and b-Bit MinHash","authors":"Masakazu Fujio, Kenta Takahashi, Yosuke Kaga, Wataru Nakamura, Yoshiko Yasumura, R. Yamaguchi","doi":"10.1145/3465481.3470473","DOIUrl":"https://doi.org/10.1145/3465481.3470473","url":null,"abstract":"Various services ranging from finance to public services are digitalized in recent years for higher efficiency and user convenience. With this service digitalization, the need for identifying and authenticating users is increasing. Amongst the user authentication methods, biometric authentication is spreading as it does not require the user to remember a password or to have a specific token. As a more convenient authentication method, research is also being conducted on unconscious authentication using smartphones’ movement history. In this paper, we propose location history-based implicit user authentication acquired through GPS-equipped mobile devices. This method enables hands-free user authentication just by having a mobile device. However, location data are sensitive information that needs to be secured from the risk of location data leakage. By using the template protection technique, location data can be transformed so that the original location data cannot be recovered while enabling authentication. However, it has a trade-off between security and accuracy and remains as a problem to be solved. This paper proposes a new location history matching method based on Modified Weighted Jaccard Coefficient. Then it extends it to template protected location history authentication by presenting a new template protection technique using b-Bit MinHash. Our experimental results show that our proposed location matching method achieves practical accuracy compared with the conventional location history matching method. Furthermore, our template-protected location authentication has comparable accuracy to unprotected matching.","PeriodicalId":417395,"journal":{"name":"Proceedings of the 16th International Conference on Availability, Reliability and Security","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114199116","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

Chaotic Pseudo Random Number Generators: A Case Study on Replication Study Challenges 混沌伪随机数生成器:复制研究挑战的案例研究

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3470062

J. Keller

引用次数: 1

OVANA: An Approach to Analyze and Improve the Information Quality of Vulnerability Databases OVANA:分析和提高漏洞数据库信息质量的方法

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3465744

Philip D. . Kuehn, Markus Bayer, Marc Wendelborn, Christian A. Reuter

{"title":"OVANA: An Approach to Analyze and Improve the Information Quality of Vulnerability Databases","authors":"Philip D. . Kuehn, Markus Bayer, Marc Wendelborn, Christian A. Reuter","doi":"10.1145/3465481.3465744","DOIUrl":"https://doi.org/10.1145/3465481.3465744","url":null,"abstract":"Vulnerability databases are one of the main information sources for IT security experts. Hence, the quality of their information is of utmost importance for anyone working in this area. Previous work has shown that machine readable information is either missing, incorrect, or inconsistent with other data sources. In this paper, we introduce a system called Overt Vulnerability source ANAlysis (OVANA), which analyzes the information quality of vulnerability databases utilizing state-of-the-art machine learning (ML) and natural language processing (NLP) techniques, searches the free-form description for relevant information missing from structured fields, and updates it accordingly. Our paper exemplifies that on the National Vulnerability Database, showing that OVANA is able to improve the information quality by 51.23% based on the indicators of accuracy, completeness, and uniqueness. Moreover, we present information which should be incorporated into the structured fields to increase the uniqueness of vulnerability entries and improve the discriminability of different vulnerability entries. The identified information from OVANA enables a more targeted vulnerability search and provides guidance for IT security experts in finding relevant information in vulnerability descriptions for severity assessment.","PeriodicalId":417395,"journal":{"name":"Proceedings of the 16th International Conference on Availability, Reliability and Security","volume":"359 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115899599","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: 12

Irish Attitudes Toward COVID Tracker App & Privacy: Sentiment Analysis on Twitter and Survey Data 爱尔兰人对COVID跟踪应用程序和隐私的态度:对Twitter和调查数据的情绪分析

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3469193

P. Lohar, Guodong Xie, Malika Bendechache, Rob Brennan, Edoardo Celeste, R. Trestian, Irina Tal

{"title":"Irish Attitudes Toward COVID Tracker App & Privacy: Sentiment Analysis on Twitter and Survey Data","authors":"P. Lohar, Guodong Xie, Malika Bendechache, Rob Brennan, Edoardo Celeste, R. Trestian, Irina Tal","doi":"10.1145/3465481.3469193","DOIUrl":"https://doi.org/10.1145/3465481.3469193","url":null,"abstract":"Contact tracing apps used in tracing and mitigating the spread of COVID-19 have sparked discussions and controversies worldwide. The major concerns in relation to these apps are around privacy. Ireland was in general praised for the design of its COVID tracker app, and the transparency through which privacy issues were addressed. However, the ”voice” of the Irish public was not really heard or analysed. This study aimed to analyse the Irish public sentiment towards privacy and COVID tracker app. For this purpose we have conducted sentiment analysis on Twitter data collected from public Twitter accounts from Republic of Ireland. We collected COVID-19 related tweets generated in Ireland over a period of time from January 1, 2020 up to December 31, 2020 in order to perform sentiment analysis on this data set. Moreover, the study performed sentiment analysis on the feedback received from a national survey on privacy conducted in Republic of Ireland. The findings of the study reveal a significant criticism towards the app that relate to privacy concerns, but other aspects of the app as well. The findings also reveal some positive attitude towards the fight against COVID-19, but these are not necessarily related to the technological solutions employed for this purpose. The findings of the study contributed to the formulation of useful recommendations communicated to the relevant Irish actors.","PeriodicalId":417395,"journal":{"name":"Proceedings of the 16th International Conference on Availability, Reliability and Security","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132522573","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: 10

Time for Truth: Forensic Analysis of NTFS Timestamps 时间真相:NTFS时间戳的法医分析

Proceedings of the 16th International Conference on Availability, Reliability and Security Pub Date : 2021-08-16 DOI: 10.1145/3465481.3470016

Michael Galhuber, R. Luh

引用次数: 5