2021 IEEE International Conference on Cyber Security and Resilience (CSR)最新文献_第2页

A Scalable Multi-Agent System for Black Start Restoration in Low Voltage Microgrids 低压微电网黑启动恢复的可扩展多智能体系统

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527919

Achilleas Pasias, Alexandros Schoinas, A. Drosou, D. Tzovaras

引用次数: 3

Conference Sponsors 会议的赞助商

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/csr51186.2021.9527929

引用次数: 0

Towards a Maritime Cyber Range training environment 迈向海上网络靶场训练环境

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527904

Georgios Potamos, A. Peratikou, S. Stavrou

引用次数: 5

Toward Automated Threat Modeling of Edge Computing Systems 边缘计算系统的自动威胁建模

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527937

V. Casola, Alessandra De Benedictis, Carlo Mazzocca, R. Montanari

{"title":"Toward Automated Threat Modeling of Edge Computing Systems","authors":"V. Casola, Alessandra De Benedictis, Carlo Mazzocca, R. Montanari","doi":"10.1109/CSR51186.2021.9527937","DOIUrl":"https://doi.org/10.1109/CSR51186.2021.9527937","url":null,"abstract":"Edge computing brings processing and storage capabilities closer to the data sources, to reduce network latency, save bandwidth, and preserve data locality. Despite the clear benefits, this paradigm brings unprecedented cyber risks due to the combination of the security issues and challenges typical of cloud and Internet of Things (IoT) worlds. Notwithstanding an increasing interest in edge security by academic and industrial communities, there is still no discernible industry consensus on edge computing security best practices, and activities like threat analysis and countermeasure selection are still not well established and are completely left to security experts.In order to cope with the need for a simplified yet effective threat modeling process, which is affordable in presence of limited security skills and economic resources, and viable in modern development approaches, in this paper, we propose an automated threat modeling and countermeasure selection strategy targeting edge computing systems. Our approach leverages a comprehensive system model able to describe the main involved architectural elements and the associated data flow, with a focus on the specific properties that may actually impact on the applicability of threats and of associated countermeasures.","PeriodicalId":253300,"journal":{"name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124620637","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

CTI Blockchain-Based Sharing using Proof-of-Quality Consensus Algorithm 使用质量证明共识算法的CTI区块链共享

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527959

Dimitrios Chatziamanetoglou, K. Rantos

引用次数: 0

Influence Pathways: Mapping the Narratives and Psychological Effects of Russian COVID-19 Disinformation 影响途径:绘制俄罗斯COVID-19虚假信息的叙事和心理效应

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527953

A. Hoyle, Thomas Powell, Beatrice Cadet, J. Kuijt

{"title":"Influence Pathways: Mapping the Narratives and Psychological Effects of Russian COVID-19 Disinformation","authors":"A. Hoyle, Thomas Powell, Beatrice Cadet, J. Kuijt","doi":"10.1109/CSR51186.2021.9527953","DOIUrl":"https://doi.org/10.1109/CSR51186.2021.9527953","url":null,"abstract":"While the content of hostile disinformation narratives is relatively well-researched, how these narratives interact and are amplified to generate psychological effects requires further scrutiny. To address this gap, this study uses Russian COVID-19 disinformation combined with network methodologies to contextualize a novel hypothetical model of this process. Specifically, we conduct a content analysis of known disinformation articles about COVID-19 (N = 65) from Russian news sources (e.g. RT, Sputnik, New Eastern Outlook). Using co-occurrence network visualizations, we map the pathways from narrative to psychological effects to provide new insights and testable models of the effects of COVID-19 disinformation. Main findings show that hostile anti-Western narratives primarily target the emotions of anger, disgust, and confusion to undermine citizens' trust in (supra-) governmental institutions and the media. This is the first step in a research agenda that can help media practitioners develop interventions and aid policy makers bolster societal resilience to hostile disinformation campaigns.","PeriodicalId":253300,"journal":{"name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123477289","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

Automated and On-Demand Cybersecurity Certification 自动化和按需网络安全认证

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527958

Stylianos Karagiannis, Marco Manso, E. Magkos, Luís L. Ribeiro, Luís Campos

{"title":"Automated and On-Demand Cybersecurity Certification","authors":"Stylianos Karagiannis, Marco Manso, E. Magkos, Luís L. Ribeiro, Luís Campos","doi":"10.1109/CSR51186.2021.9527958","DOIUrl":"https://doi.org/10.1109/CSR51186.2021.9527958","url":null,"abstract":"The digital world nowadays consists of a very high number of devices and software services that are being used and constantly exposed to the Internet. Furthermore, with the evolution of the Internet of Things (IoT), the cybersecurity threat landscape has overall increased. Consequently, various certification frameworks have been developed for maintaining the overall security posture and supporting the required security tests. This paper describes an approach for conducting automated and on-demand cybersecurity certification on systems and software components. Taking the existing cybersecurity frameworks and guidelines into consideration, the developed software/service component aims to provide auditing information and insights from the systems-on-the-test, to certify newly entering components that could increase the security risk. The recommended approach can be used for collecting, extracting, and generating reports regarding the security aspects of the submitted digital assets by deploying automated security tests and auditing processes that will contribute to the certification process.","PeriodicalId":253300,"journal":{"name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078945","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

Reinforcement Learning-driven Attack on Road Traffic Signal Controllers 基于强化学习的道路交通信号控制器攻击

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527951

Najmeh Seifollahpour Arabi, Talal Halabi, Mohammad Zulkernine

{"title":"Reinforcement Learning-driven Attack on Road Traffic Signal Controllers","authors":"Najmeh Seifollahpour Arabi, Talal Halabi, Mohammad Zulkernine","doi":"10.1109/CSR51186.2021.9527951","DOIUrl":"https://doi.org/10.1109/CSR51186.2021.9527951","url":null,"abstract":"Intelligent Transportation Systems (ITS) combine emerging communication, computer, and system technologies to deliver intelligent road traffic services and optimize decision making within the transportation infrastructure. The advancement of connected vehicles, which generate dynamic data through wireless communications, enables ITS to improve their efficiency, especially in Traffic Signal Control (TSC), which is the backbone of traffic flow scheduling. However, wireless communications channels are vulnerable to various types of cyberattacks and can pose serious threats to dynamic TSC systems. Attackers may attempt to manipulate normal traffic flows and cause severe traffic congestion. Deep Reinforcement Learning (DRL) is a powerful technique that has been used to improve TSC systems performance in real-time environments. However, it can be used by attackers to exploit the dynamics of the ITS and learn the optimal attack policy under the lack of deterministic information about system behavior. In this work, to highlight and exploit existing vulnerabilities in TSC systems, we leverage DRL to create an intelligent Sybil attack on a traffic intersection, wherein connected vehicles with fake identities are optimally placed to alter traffic signal timings by corrupting traffic data. The results show that this attack leads to substantial increase in the vehicles’ travel time and yields disastrous traffic congestion, especially if carried out for a prolonged period of time, which will give rise to serious problems such as higher fuel consumption and air pollution in heavily dense cities. In the presence of such intelligent attacks, the design assumptions of existing TSC systems become highly questionable.","PeriodicalId":253300,"journal":{"name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131255173","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

A Dynamic Reconfiguration-based Approach to Resilient State Estimation 基于动态重构的弹性状态估计方法

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527991

A. Joss, Austin Grassbaugh, M. Poshtan, Joseph Callenes

{"title":"A Dynamic Reconfiguration-based Approach to Resilient State Estimation","authors":"A. Joss, Austin Grassbaugh, M. Poshtan, Joseph Callenes","doi":"10.1109/CSR51186.2021.9527991","DOIUrl":"https://doi.org/10.1109/CSR51186.2021.9527991","url":null,"abstract":"The increasing complexity and connectivity of power systems is making it increasingly likely that they will be subject to malicious attacks that compromise operation. Recent studies have shown that these systems are vulnerable to a wide range of cyber-attacks, including False Data Injection (FDI). Conventional security monitoring and protection tools are based on passive defense strategies. In this paper, we propose an approach for active defense that improves system security and the FDI attack detection rate. The key insight for this approach is that emerging micro-grids can utilize distributed energy resources to dynamically reconfigure the system (e.g. current flow paths), across multiple acceptable configurations. Instead of using information from only a single configuration to detect FDI attacks, our proposed approach uses dynamic reconfiguration to compare measured and estimated states under multiple configurations to accurately detect FDI attacks. We evaluate our approach in the specific scenario of emerging micro-grids. We develop a novel technique for state estimation using multiple configurations and demonstrate that this approach significantly improves FDI detection accuracy.","PeriodicalId":253300,"journal":{"name":"2021 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127053312","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

Cyber-Security Training Evaluation Metrics 网络安全培训评估指标

2021 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2021-07-26 DOI: 10.1109/CSR51186.2021.9527946

N. Koutsouris, C. Vassilakis, N. Kolokotronis

引用次数: 3