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检索条件"任意字段=19th International Conference on Control Systems and Computer Science"

共 42758 条记录，以下是31-40 订阅

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POP-HIT: Partially Order-Preserving Hash-Induced Transformation for Privacy Protection in Face Recognition Access control 19th

POP-HIT: Partially Order-Preserving Hash-Induced Transformat...

引用

19th international conference on Security and Privacy in Communication Networks

作者： Dubasi, Yatish Li, Qinghua Luu, Khoa Univ Arkansas Fayetteville AR 72701 USA

ISBN: (纸本)9783031649530;9783031649547

Server-based face recognition access control (SFRAC) is a widely used biometric authentication method where a camera captures a user's face image and sends the face information to a backend server to determine an authentication result. In existing systems, user face images or raw facial features are sent to the backend server, which induces privacy concerns. this paper proposes a method to protect user face privacy in SFRAC systems, such that user face images or raw facial features are never sent to the server, but the system can still do face-based access control. the method uses a novel partially order-preserving hash-induced transformation (POP-HIT) to perform feature transformation on facial embeddings. POP-HIT maps a user's facial features to a transformed space in order to preserve privacy. Authentication is performed by checking the transformed facial embedding of the user's face image captured at the time of authentication against the user's pre-stored transformed facial embeddings at the server, based on similarity metrics or machine learning methods. Since the server only sees transformed facial embeddings, which cannot be used to recover the facial image, facial privacy is protected. Analysis and experimental evaluations show that our method has a high authentication accuracy, and it achieves privacy protection without being vulnerable to impersonation attacks.

关键词： Facial recognition Access control Privacy

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Monitoring Real-Time systems Under Parametric Delay 19th

Monitoring Real-Time Systems Under Parametric Delay

引用

19th international conference on Integrated Formal Methods

作者： Fraenzle, Martin Grosen, thomas M. Larsen, Kim G. Zimmermann, Martin Carl von Ossietzky Univ Oldenburg Oldenburg Germany Aalborg Univ Aalborg Denmark

ISBN: (纸本)9783031765537;9783031765544

Timed Buchi automata provide a very expressive formalism for expressing requirements of real-time systems. Online monitoring of embedded real-time systems can then be achieved by symbolic execution of such automata on the trace observed from the system. this direct construction however only is faithful if observation of the trace is immediate in the sense that the monitor can assign exact time stamps to the actions it observes, which is rarely true in practice due to the substantial and fluctuating parametric delays introduced by the circuitry connecting the observed system to its monitoring device. We present a purely zone-based online monitoring algorithm, which handles such parametric delays exactly without recurrence to costly verification procedures for parametric timed automata. We have implemented our monitoring algorithm on top of the real-time model checking tool UPPAAL, and report on encouraging initial results.

关键词： Monitoring Timing uncertainty Timed Buchi Automata

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Recognition of Remakes and Fake Facial Images 19th

Recognition of Remakes and Fake Facial Images

引用

19th international Workshop on Data Privacy Management, DPM 2024, 8th international Workshop on Cryptocurrencies and Blockchain Technology, CBT 2024 and 10th Workshop on the Security of Industrial control systems and of Cyber-Physical systems, CyberICPS 2024 which were held in conjunction with the 29th European Symposium on Research in computer Security, ESORICS 2024

作者： Bobulski, Janusz Kubanek, Mariusz Department of Computer Sciences Czestochowa University of Technology Czestochowa42-201 Poland

ISBN: (纸本)9783031823619

computer Vision techniques are extensively utilised in entertainment, enhancing realism in games and movies. Within video games, these techniques enable the recognition of objects, characters, and player movements, thereby enabling more intelligent game responses to player actions, resulting in more prosperous and more immersive experiences. Moreover, integrating deep learning methodologies with computer vision facilitates the automatic generalisation of special effects and enhances live broadcasts with interactive elements. However, such approaches also present challenges, as they can be exploited to manipulate and fabricate information, such as swapping faces in images or videos. this phenomenon is particularly evident in social media, where various forms of counterfeit or manipulated content proliferate, commonly called fake news. Our article proposes a novel convolutional neural network-based method for detecting alterations in real facial images and distinguishing them from artificially generated ones. Our technique, with its potential to revolutionise the field, enables the classification of facial photos into three categories: authentic faces, authentic faces with applied modifications (e.g., through photo editing software), and artificially generated facial images. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Proceedings - 2023 24th international conference on control systems and computer science, CSCS 2023

Proceedings - 2023 24th International Conference on Control ...

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24th international conference on control systems and computer science, CSCS 2023

ISBN: (纸本)9798350313390

the proceedings contain 103 papers. the topics discussed include: evolutionary hyper-heuristics for improving global optimization algorithms;multi-objective decision making system based on spatial -temporal logics;analysis of trajectory optimization for solving tower of Hanoi problem using industrial manipulator;achievements regarding the optimal control of refinery processes;experimental study of pressure variation in a constant volume enclosure;velocity computation for vehicle trajectory tracking: a comparative analysis of performance and efficiency;smart digital-twin hub concept for rice yield prediction and monitoring from multivariate time series data;enhanced cyber-physical system with semantic technologies and machine learning to support smart farming;qualified remote signature through a hybrid cloud architecture;and an industry 4.0 oriented predictive maintenance solution deployed in real-world automotive manufacturing facilities.

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A Framework for Applying Artificial Intelligence Algorithms in Command and control systems 24

A Framework for Applying Artificial Intelligence Algorithms ...

引用

8th international conference on computer science and Artificial Intelligence, CSAI 2024

作者： Xiao, Bo Zhou, Xuan National Defence University Beijing China

ISBN: (纸本)9798400718182

the rapid development of artificial intelligence (AI) technology has driven substantial transformations across various sectors of commercial society. However, the successful application of AI System in the command and control (C2) domain remains relatively limited. therefore, this paper presents a viable analytical framework aimed at establishing a mapping relationship between the characteristics of C2 problems and the required AI capabilities. this framework utilizes a structured approach to quantitatively evaluate how AI algorithms can be effectively applied in different C2 domains. © 2024 Copyright held by the owner/author(s).

关键词： Command and control systems

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A Novel Method of Improving Intrusion Detection systems Robustness Against Adversarial Attacks, through Feature Omission and a Committee of Classifiers 19th

A Novel Method of Improving Intrusion Detection Systems Rob...

引用

作者： Pawlicki, Marek Uccello, Federica D’Antonio, Salvatore Kozik, Rafal Choraś, Michal Bydgoszcz University of Science and Technology PBS Bydgoszcz Poland University of Naples ‘Parthenope’ Centro Direzionale Isola C4 Napoli80133 Italy

ISBN: (纸本)9783031823619

Intrusion Detection systems play an important role in network security. With the advent of Machine Learning and Artificial Intelligence, ML-based IDS have been gaining increasing popularity in comparison with traditional anomaly-based and signature-based ones. While bringing several advantages, these systems are vulnerable to so-called adversarial attacks, where a malicious user tampers with testing data to compromise the performance and reliability of the ML-based IDS. this research presents a novel approach to enhance the robustness of IDS against adversarial evasion attacks using a committee of Neural Network classifiers. Each model in the committee is trained on different feature subsets, specifically omitting features of high importance, which are prone to be the subject of adversarial attacks, enabling a more resilient detection mechanism. Experimental results using the CICIoT2023 dataset Mirai attack samples, as an example of malware that could use adversarial attacks to hide its presence from AI-based detectors, demonstrate the effectiveness of the proposed method. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Research on control Strategies for Partially Observable Discrete Event systems Based on Normal State Tree Structure 24

Research on Control Strategies for Partially Observable Disc...

引用

5th international conference on computer science and Management Technology, ICCSMT 2024

作者： Gu, Chan Tang, Bo Chi, Encheng School of Electrical and Control Engineering Shaanxi University of Science and Technology Shaanxi Xi'an China

ISBN: (纸本)9798400709999

In the process of modeling and solving large-scale complex systems, issues with complex state structures and low computational efficiency are often *** partially observable discrete event systems, this paper proposes a method that utilizes state tree structures for modeling and analyzes global behavior through local *** demonstrates the existence of non-blocking, weakly controllable coreachable and observable (WCCO) subpredicates and their solving *** order to effectively represent these complex system states, the paper employs the use of Binary Decision Diagrams (BDD), which are capable of compactly and efficiently representing state tree *** feasibility of the proposed algorithm is verified through practical examples, showing that the algorithm exhibits higher fault tolerance and flexibility in handling complex systems, enabling the development of more forgiving control *** not only enhances the stability and reliability of the system but also provides new solutions for supervisory control in practical engineering applications. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Binary decision diagrams

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Best-Practices-Based Training for Improving Cybersecurity in Power Grids 19th

Best-Practices-Based Training for Improving Cybersecurity i...

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作者： Kavallieratos, Georgios Amro, Ahmed Gkioulos, Vasileios Stamatescu, Grigore Rantos, Kostantinos Lagkas, thomas Demertzis, Konstantinos Paterakis, Fotis Lekidis, Alexios Dalamagkas, Christos Kotsiuba, Igor Katsikas, Sokratis Norwegian University of Science and Technology Gjøvik Norway TÜV Austria Romania 139B Calea Plevnei Bucharest060011 Romania Department of Automation and Industrial Informatics University Politehnica of Bucharest 313 Splaiul Independentei Bucharest060042 Romania Department of Informatics Democritus University of Thrace Kavala65404 Greece School of Science Department of Computer Science Kavala Campus International Hellenic University Kavala65404 Greece Athens Greece Innovation Hub of Public Power Corporation S.A. Attica Greece Durham University Durham United Kingdom

ISBN: (纸本)9783031823619

the increased financial value of the power grids and the multitude of potential attackers, including such with advanced capabilities, makes the enhancement of cybersecurity in power grids very important. In order to strengthen the cybersecurity posture of the power grids, it is necessary to foster the development of cybersecurity skills and knowledge of the personnel working in them. To this end, this work proposes a systematic process that leverages cybersecurity best practices to define training content for personnel employed in power grids. To illustrate the workings of the proposed approach, best practices against phishing, spoofing, denial of service, and unauthorized activities are presented. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Phishing

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Dynamic k-Anonymity for Electronic Health Records: A Topological Framework 19th

Dynamic k-Anonymity for Electronic Health Records: A Topolo...

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作者： Swaminathan, Arjhun Akgün, Mete Medical Data Privacy and Privacy Preserving Machine Learning Department of Computer Science University of Tübingen Tübingen Germany Institute for Bioinformatics and Medical Informatics Tübingen Germany

ISBN: (纸本)9783031823480

With the rapid digitization of Electronic Health Records (EHRs), fast and adaptive data anonymization methods have become increasingly important. While tools from topological data analysis (TDA) have been proposed to anonymize static datasets—allowing the creation of multiple generalizations for different anonymization needs from a single computation—the application to dynamic datasets remains unexplored. To address this, our work adapts existing methodologies to the dynamic setting. We develop an improved version of weighted persistence barcodes that track higher-dimensional holes in data, allowing us to edit persistence information on the fly. Additionally, we introduce filtration trimming, a novel technique designed to update persistence data quickly with minimal computing effort when data is added. Our work represents a significant advancement in healthcare data privacy, offering a refined approach to protecting highly sensitive and evolving patient data through dynamic k-anonymity. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Electronic health record

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controlled Multi-client Functional Encryption for Flexible Access control 19th

Controlled Multi-client Functional Encryption for Flexible A...

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19th international conference on Information Security Practice and Experience

作者： Zhang, Mingwu Zhong, Yulu Wang, Yifei Wang, Yuntao Guilin Univ Elect Technol Sch Comp Sci & Informat Secur Guilin Peoples R China Hubei Univ Technol Sch Comp Wuhan Peoples R China Univ Edinburgh Sch Math Edinburgh Midlothian Scotland Univ Electrocommun Sch Informat & Engn Chofu Tokyo Japan

ISBN: (纸本)9789819790524;9789819790531

In controlled Functional Encryption (C-FE), a policy parameter is introduced during encryption to restrict how the decryptor can decrypt and compute the ciphertext, but C-FE shows certain limitations in complex scenarios involving multiple encryptors participating with their data remaining confidential from each other. To overcome these limitations and leverage the advantages of Multi-Client Functional Encryption (MCFE) and Attribute-Based Encryption (ABE), we extend C-FE, introducing a new primitive termed controlled Multi-Client Functional Encryption for Flexible Access control (CMCFE-FAC). this primitive introduces several key innovations: firstly, our CMCFE-FAC scheme combines MCFE to support multiple encryptors, enabling independent encryption and ensuring data privacy and security. Secondly, CMCFE-FAC combines attribute-based mechanisms to support dynamic access control, expanding traditional access control policies and enhancing their flexibility. thirdly, we formalize the definition and security model for CMCFE-FAC, propose a CMCFE-FAC scheme tailored for the inner product function, and demonstrate the scheme's security based on the DBDH assumption. Finally, theoretical analysis and experimental results are provided to illustrate its effectiveness and security.

关键词： Functional Encryption Inner Product Multi-Client Access control

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