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2023 IEEE International Conference on Cyber Security and Resilience (CSR)最新文献

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Introducing the TRUMPET project: TRUstworthy Multi-site Privacy Enhancing Technologies 介绍TRUMPET项目:可信赖的多站点隐私增强技术
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224961
A. Pedrouzo-Ulloa, J. Ramon, Fernando Péerez-González, Siyanna Lilova, Patrick Duflot, Zakaria Chihani, N. Gentili, P. Ulivi, Mohammad Ashadul Hoque, Twaha Mukammel, Zeev Pritzker, Augustin Lemesle, J. Loureiro-Acuña, Xavier Martínez, G. Jiménez-Balsa
{"title":"Introducing the TRUMPET project: TRUstworthy Multi-site Privacy Enhancing Technologies","authors":"A. Pedrouzo-Ulloa, J. Ramon, Fernando Péerez-González, Siyanna Lilova, Patrick Duflot, Zakaria Chihani, N. Gentili, P. Ulivi, Mohammad Ashadul Hoque, Twaha Mukammel, Zeev Pritzker, Augustin Lemesle, J. Loureiro-Acuña, Xavier Martínez, G. Jiménez-Balsa","doi":"10.1109/CSR57506.2023.10224961","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224961","url":null,"abstract":"This paper is an overview of the EU-funded project TRUMPET (https://trumpetproject.eu/), and gives an outline of its scope and main technical aspects and objectives. In recent years, Federated Learning has emerged as a revolutionary privacy-enhancing technology. However, further research has cast a shadow of doubt on its strength for privacy protection. The goal of TRUMPET is to research and develop novel privacy enhancement methods for Federated Learning, and to deliver a highly scalable Federated AI service platform for researchers, that will enable AI-powered studies of siloed, multi-site, cross-domain, cross-border European datasets with privacy guarantees that follow the requirements of GDPR. The generic TRUMPET platform will be piloted, demonstrated and validated in the specific use case of European cancer hospitals, allowing researchers and policymakers to extract AI-driven insights from previously inaccessible cross-border, cross-organization cancer data, while ensuring the patients' privacy.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121747149","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
Efficiency of Malware Detection Based on DNS Packet Analysis Over Real Network Traffic 基于DNS报文分析的真实网络流量恶意软件检测效率研究
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224973
Lorenzo Principi, M. Baldi, A. Cucchiarelli, L. Spalazzi
{"title":"Efficiency of Malware Detection Based on DNS Packet Analysis Over Real Network Traffic","authors":"Lorenzo Principi, M. Baldi, A. Cucchiarelli, L. Spalazzi","doi":"10.1109/CSR57506.2023.10224973","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224973","url":null,"abstract":"Domain names queried by infected network terminals to domain name system (DNS) servers may reveal connection attempts to some command and control (C&C) server, which makes DNS-based malware detection a well-established technique in network security. Such a technique clearly is the only one available when the analysis is performed on DNS server logs. Today, however, intrusion detection approaches that analyze the entire network traffic generated by an endpoint are becoming increasingly popular. In this paper, we assess the effectiveness of DNS-based malware detection even when working over the entire network traffic. We consider malware detection techniques exploiting neural network-based DNS packet analysis and study their effectiveness in detecting malware from real network traffic generated by an infected terminal, also identifying under which conditions they achieve their best detection performance.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133999182","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
Assessing Cybersecurity Hygiene and Cyber Threats Awareness in the Campus - A Case Study of Higher Education Institutions in Portugal and Poland 评估校园网络安全卫生和网络威胁意识——以葡萄牙和波兰高等教育机构为例
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224910
Luís Oliveira, A. Chmielewski, Paulina Rutecka, K. Cicha, Mariia Rizun, Nuno Torres, Pedro Pinto
{"title":"Assessing Cybersecurity Hygiene and Cyber Threats Awareness in the Campus - A Case Study of Higher Education Institutions in Portugal and Poland","authors":"Luís Oliveira, A. Chmielewski, Paulina Rutecka, K. Cicha, Mariia Rizun, Nuno Torres, Pedro Pinto","doi":"10.1109/CSR57506.2023.10224910","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224910","url":null,"abstract":"Cybersecurity skills are of utmost importance to prevent or mitigate the impact of cyberattacks. In higher education, there are graduations related to Information Technology (IT), where students are expected to develop technical skills, including cybersecurity. Thus, it is relevant to assess students' cybersecurity awareness regarding cybersecurity hygiene and cyber threats when they start their academic studies and to verify whether there are context-dependent differences. This paper presents the results of an assessment regarding the cybersecurity awareness level of 110 first-year students from computer science graduations from two different countries, Poland and Portugal. The assessment was designed as a survey divided into the following two main groups of questions: (1) awareness regarding cybersecurity hygiene and (2) awareness regarding major cyber threats considered in the European Union Agency for Cybersecurity (ENISA) 2021 cyber threat report. The survey results show that Polish and Portuguese students present different self-perceptions and knowledge regarding cybersecurity hygiene and knowledge of cybersecurity. In these areas, Polish students are generally more confident than Portuguese students. Also, Polish students presented better scores around 70%, against the ones obtained by the Portuguese students, scoring around 58%.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133038624","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
Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design 融合基于模型和数据驱动的弹性系统数字孪生设计方法
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224945
L. Campanile, Maria Stella de Biase, Roberta De Fazio, Michele Di Giovanni, F. Marulli, Laura Verde
{"title":"Merging Model-Based and Data-Driven Approaches for Resilient Systems Digital Twins Design","authors":"L. Campanile, Maria Stella de Biase, Roberta De Fazio, Michele Di Giovanni, F. Marulli, Laura Verde","doi":"10.1109/CSR57506.2023.10224945","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224945","url":null,"abstract":"Nowadays, the problem of system robustness, es-pecially in critical infrastructures, is a challenging open question. Some systems provide crucial services continuously failing, threatening the availability of the provided services. By designing a robust architecture, this criticality could be overcome or limited, ensuring service continuity. The definition of a resilient system involves not only its architecture but also the methodology implemented for the calculation and analysis of some indices, quantifying system performance. This study provides an innovative architecture for Digital Twins implementation based on a hybrid methodology for improving the control system in realtime. The introduced approach brings together different techniques. In particular, the work combines the point of strengths of Model-based methods and Data-driven ones, aiming to improve system performances.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115096014","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
Comparative Analysis of Pattern Mining Algorithms for Event Logs 事件日志模式挖掘算法的比较分析
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224996
Orkhan Gasimov, Risto Vaarandi, Mauno Pihelgas
{"title":"Comparative Analysis of Pattern Mining Algorithms for Event Logs","authors":"Orkhan Gasimov, Risto Vaarandi, Mauno Pihelgas","doi":"10.1109/CSR57506.2023.10224996","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224996","url":null,"abstract":"During the last two decades, the mining of message patterns from textual event logs has become an important security monitoring and system management task. A number of algorithms have been developed for that purpose, and recently several comparative studies of these algorithms have been published. However, existing studies have several drawbacks like the lack of performance evaluation on real-life data sets and the use of suboptimal settings for evaluated algorithms. This paper addresses these issues and evaluates commonly used log mining algorithms on a number of security and system event logs.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115538031","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
Counteracting Modeling Attacks Using Hardware-Based Dynamic Physical Unclonable Function 基于硬件的动态物理不可克隆函数对抗建模攻击
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224914
Shailesh Rajput, Jaya Dofe
{"title":"Counteracting Modeling Attacks Using Hardware-Based Dynamic Physical Unclonable Function","authors":"Shailesh Rajput, Jaya Dofe","doi":"10.1109/CSR57506.2023.10224914","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224914","url":null,"abstract":"The widespread adoption of Internet of Things (IoT) devices across various application domains has significantly improved quality of life. However, the resource-constrained, heterogeneous, and low-power nature of these devices poses challenges in ensuring secure communication and authenticity. Physical Unclonable Functions (PUFs) provide a solution by creating a unique and device-specific identity through manufacturing process variations without requiring additional resources. To authenticate IoT devices, a challenge-response pair (CRP) is generated based on the unique characteristics of each device. However, the CRPs generated by PUFs often exhibit high correlation, making them vulnerable to modeling attacks. Despite the proposal of numerous intricate PUF architectures, such as XOR PUF and Interpose PDF, the advancement in machine learning algorithms has enabled modeling attacks on these PUFs. This work presents a hardware-based dynamic PUF and evaluates its performance on field programmable gate arrays (FPGAs). The dynamic nature of the proposed PUF architecture makes it challenging for prevalent machine learning models to predict accurate PUF responses. The research also compares the efficacy of logistic regression and multilayer perceptron-based modeling attacks on Arbiter PUF and XOR PUF architectures. The experimental findings reveal that the dynamic PUF outperforms the other two PUFs against machine learning-based attacks. These results suggest that the dynamic PUF architecture is viable for IoT applications.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116752852","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
FedGA-Meta: Federated Learning Framework using Genetic Algorithms and Meta-Learning for Aggregation in Industrial Cyber- Physical Systems FedGA-Meta:在工业网络物理系统中使用遗传算法和元学习进行聚合的联邦学习框架
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224975
Souhila Badra Guendouzi, Samir Ouchani, Hiba El Assaad, Madeleine El Zaher
{"title":"FedGA-Meta: Federated Learning Framework using Genetic Algorithms and Meta-Learning for Aggregation in Industrial Cyber- Physical Systems","authors":"Souhila Badra Guendouzi, Samir Ouchani, Hiba El Assaad, Madeleine El Zaher","doi":"10.1109/CSR57506.2023.10224975","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224975","url":null,"abstract":"In Industry 4.0, factories encounter significant challenges in making informed decisions to maintain or enhance their industry standing. By utilizing machine learning (ML), they can improve product quality, decrease production downtime, and boost operational efficiency. However, acquiring datasets with sufficient variation and diversity to train a robust neural network centrally is a challenge within the industrial sector. Consequently, federated learning (FL) offers a decentralized approach that safeguards data privacy, enabling smart infrastructures to train collaborative models locally and independently while retaining local data. In this paper, we present FedGA-Meta framework, which combines FL, meta-learning, and domain adaptation to enhance model performance and generalizability, particularly when training across distributed factories with varying network and data conditions. The results obtained demonstrate the effectiveness and efficiency of our FedGA-Meta framework.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115512288","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
Conference Sponsors 会议的赞助商
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/csr57506.2023.10224988
{"title":"Conference Sponsors","authors":"","doi":"10.1109/csr57506.2023.10224988","DOIUrl":"https://doi.org/10.1109/csr57506.2023.10224988","url":null,"abstract":"","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125001204","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
VulDetect: A novel technique for detecting software vulnerabilities using Language Models VulDetect:一种使用语言模型检测软件漏洞的新技术
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10224924
Marwan Omar, S. Shiaeles
{"title":"VulDetect: A novel technique for detecting software vulnerabilities using Language Models","authors":"Marwan Omar, S. Shiaeles","doi":"10.1109/CSR57506.2023.10224924","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10224924","url":null,"abstract":"Recently, deep learning techniques have garnered substantial attention for their ability to identify vulnerable code patterns accurately. However, current state-of-the-art deep learning models, such as Convolutional Neural Networks (CNN), and Long Short-Term Memories (LSTMs) require substantial computational resources. This results in a level of overhead that makes their implementation unfeasible for deployment in realtime settings. This study presents a novel transformer-based vulnerability detection framework, referred to as VulDetect, which is achieved through the fine-tuning of a pretrained large language model, (GPT) on various benchmark datasets of vulnerable code. Our empirical findings indicate that our framework is capable of identifying vulnerable software code with an accuracy of up to 92.65%. Our proposed technique outperforms SyseVR and VuIDeBERT, two state-of-the-art vulnerability detection techniques.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123029062","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
HSchain: Anonymous Permissioned Blockchain with Enhanced Auditability HSchain:具有增强可审计性的匿名许可区块链
2023 IEEE International Conference on Cyber Security and Resilience (CSR) Pub Date : 2023-07-31 DOI: 10.1109/CSR57506.2023.10225006
Jipeng Hou, Lei Xu, Liehuang Zhu, Peng Jiang, Shaorui Song
{"title":"HSchain: Anonymous Permissioned Blockchain with Enhanced Auditability","authors":"Jipeng Hou, Lei Xu, Liehuang Zhu, Peng Jiang, Shaorui Song","doi":"10.1109/CSR57506.2023.10225006","DOIUrl":"https://doi.org/10.1109/CSR57506.2023.10225006","url":null,"abstract":"Anonymity and auditability of transactions are two important but conflicting requirements for many blockchain-based applications. Technologies proposed to realize anonymous transactions, such as coin mixing and ring signature, make it hard to identify the participants of transactions. In this paper, we propose a system called HSchain, which enables the regulator to identify the participants while keeping the identity information hidden from nodes in the blockchain network. The proposed system uses the ring signature and the one-time public key to hide the sender and the receiver of a transaction respectively. By running a secret handshake protocol with the regulator, the sender/receiver generates a tag which is attached to the transaction to make it auditable. We carefully design the structure of the tag so that only the regulator can determine if a user has participated in a specific transaction. Simulation results demonstrate that adding such a tag to an anonymous transaction does not incur much overhead.","PeriodicalId":354918,"journal":{"name":"2023 IEEE International Conference on Cyber Security and Resilience (CSR)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123611884","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
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