Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference最新文献

Covert Channels in One-Time Passwords Based on Hash Chains 基于哈希链的一次性密码隐蔽通道

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424966

Jörg Keller, Steffen Wendzel

引用次数: 0

Covert Channels in Transport Layer Security 传输层安全中的隐蔽通道

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424962

C. Heinz, W. Mazurczyk, L. Caviglione

引用次数: 4

Cross-domain meta-learning for bug finding in the source codes with a small dataset 使用小数据集在源代码中查找bug的跨域元学习

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424957

Jongho Shin

{"title":"Cross-domain meta-learning for bug finding in the source codes with a small dataset","authors":"Jongho Shin","doi":"10.1145/3424954.3424957","DOIUrl":"https://doi.org/10.1145/3424954.3424957","url":null,"abstract":"In terms of application security, detecting security vulnerabilities in prior and fixing them is one of the effective ways to prevent malicious activities. However, finding security bugs is highly reliant upon human experts due to its complexity. Therefore, source code auditing, one of the ways to find bugs, costs a lot, and the quality of auditing quite varies according to the performer. There have been many attempts to make automated systems for code auditing, but they have been suffered from huge false positives and false negatives. Meanwhile, machine learning technology is advancing dramatically in recent years, and it is outperforming humans in many tasks with high accuracy. Thus there have been lots of efforts to accommodate machine learning technology for security research. Most of the time, however, it is very difficult to obtain legitimate training data, and rarer often means more lethal in security. Therefore it is not easy to build reliable machine learning systems for security defects, and we are highly relying on human experts who can learn easily by a few examples. To overcome the obstacle, this paper proposes a deep neural network model for finding security bugs, which takes advantages of the recent developments in the machine learning technology; the language model adapted sub-word tokenization and self-attention based transformer from natural language processing for source code understanding, and a meta-learning technique from computer vision to overcome lack of legitimate vulnerability samples for the deep learning model. The model is also evaluated for finding DOM-based XSS bugs which is prevalent but hard to spot with traditional detection methods. The result shows that the model outperforms the baseline by 45% in the F1 score.","PeriodicalId":166844,"journal":{"name":"Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134244347","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

Privacy-Preserving Warning Management for an Identity Leakage Warning Network 身份泄露预警网络的隐私保护预警管理

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424955

Saffija Kasem-Madani, Timo Malderle, Felix Boes, M. Meier

{"title":"Privacy-Preserving Warning Management for an Identity Leakage Warning Network","authors":"Saffija Kasem-Madani, Timo Malderle, Felix Boes, M. Meier","doi":"10.1145/3424954.3424955","DOIUrl":"https://doi.org/10.1145/3424954.3424955","url":null,"abstract":"Identity leakage is the public disclosure of user accounts that were stolen from an online service provider, e.g. email adresses and passwords. Identity leakage is an emerging threat to the security of user accounts because the number of online identities grows notably faster than the amount of used email adresses and passwords. In order to protect users against potential identity thefts after a cyber heist, a system that proactively warns the victims seems inevitable. In the design of such a system, there are technical, legal and psychological goals, e.g., the system has to fulfill the General Data Protection Regulation and users do not want to be flooded with warnings about potential identity thefts. In this paper, we propose a warning management system for online service providers that want to cooperate whilst keeping their users' data private from each other. Most importantly, victims will be informed only once if their user identity was found in an identity leak and the cooperating service providers preserve the privacy of the victims by design. Therefore, our warning system complies with the NIST recommendation.","PeriodicalId":166844,"journal":{"name":"Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121648493","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

Shadow-Heap: Preventing Heap-based Memory Corruptions by Metadata Validation Shadow-Heap:通过元数据验证防止基于堆的内存损坏

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424956

Johannes Bouché, Lukas Atkinson, Martin Kappes

引用次数: 1

Raising Security Awareness on Mobile Systems through Gamification 通过游戏化提高移动系统的安全意识

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424958

Kris Heid, J. Heider, Kasra Qasempour

引用次数: 3

Anomaly Detection in ICS based on Data-history Analysis 基于数据历史分析的ICS异常检测

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424963

Laura Hartmann, S. Wendzel

{"title":"Anomaly Detection in ICS based on Data-history Analysis","authors":"Laura Hartmann, S. Wendzel","doi":"10.1145/3424954.3424963","DOIUrl":"https://doi.org/10.1145/3424954.3424963","url":null,"abstract":"Data of industrial control systems (ICS) are increasingly subject to cyber attacks which should be detected by approaches such as anomaly detection before they can take effect. However, examples such as Stuxnet, Industroyer or Triton show that, despite all the precautions taken, it is still possible to overcome anomaly detection systems and cause damage. Similarly, damage can be made by intentional malicious and unintentional changes by employees in programming or configuration of ICS components. An example is an employee who unintentionally manipulates a machine's configuration to a higher temperature limit than it should have. The potential consequence would be that the machine overheats and breaks. The aim of the project MADISA (Machine Learning for Attack Detection Using Data of Industrial Control Systems) is to identify such anomalies in the data of ICS by examining the data-sets and creating a machine learning system (MLS) based on heuristics over meta-data, configurations and code content. For this purpose, this poster provides a structured analysis of real-world projects from a German automobile manufacturer which lead to first attributes in this unexplored approach for creating heuristics to anomaly detection of historic data in ICS.","PeriodicalId":166844,"journal":{"name":"Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126292599","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

The role of information sensitivity in adoption of E2EE communication software 信息敏感性在E2EE通信软件采用中的作用

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424967

Luka Jelovčan, Damjan Fujs, Simon L. R. Vrhovec, Anže Mihelič

引用次数: 0

Data hiding: New opportunities for security and privacy? 数据隐藏:安全和隐私的新机遇?

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3425511

D. Megías

引用次数: 5

What Brings Women to Cybersecurity?: A Qualitative Study of Women's Pathways to Cybersecurity in Norway 是什么让女性投身网络安全?:挪威女性网络安全路径的定性研究

Proceedings of the 2020 European Interdisciplinary Cybersecurity Conference Pub Date : 2020-11-18 DOI: 10.1145/3424954.3424965

H. Corneliussen

引用次数: 2