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检索条件"任意字段=International Conference on Security in Computer Networks and Distributed Systems, SNDS 2012"

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15th international conference on Emerging Ubiquitous systems and Pervasive networks / 14th international conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2024

15th International Conference on Emerging Ubiquitous Systems...

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15th international conference on Emerging Ubiquitous systems and Pervasive networks / 14th international conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2024

The proceedings contain 115 papers. The topics discussed include: receding horizon and optimization-based control for UAV path planning with collision avoidance;application of machine learning in technological forecasting;unbiased text categorization in IoT-based digital content using a word-to-graph model;multimodal sentiment analysis based on video and audio inputs;asynchronous inter-class project collaboration adaptation method to agile practices in university context;resource consumption analysis of distributed machine learning for the security of future networks;modeling Wazuh rules with weighted timed automata;evaluating safe region sizes for accuracy in approximate continuous nearest neighbor queries;and intrusion detection systems in IoT based on machine learning: a state of the art.

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Load Balancing Methods for distributed Data Storage: Challenges and Opportunities

Load Balancing Methods for Distributed Data Storage: Challen...

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international conference on Current Problems of Applied Mathematics and computer systems, CPAMCS 2023

作者： Shiriaev, Egor North Caucasus Federal University Stavropol Russia

ISBN: (纸本)9783031640094

The increased demand for big data processing has led to the development of distributed computing and data storage technologies. However, building an efficient distributed system is a rather difficult task and has a few problems. The problems of building a distributed system are related to its security and reliability. In this paper, research is carried out related to increasing the reliability of a distributed storage system. During the study, an analysis of load balancing methods was carried out. Based on the analysis, a hybrid load balancing method was compiled. The hybrid method is based on the Least Connection and Weighted Round Robin methods. This method allows you to effectively balance the load in distributed storage systems, which increases their reliability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Big Data distributed Computing systems distributed Storage systems Least Connection Load Balancing Weighted Round Robin

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Group authentication algorithm based on region grouping and aggregate signcryption 4

Group authentication algorithm based on region grouping and ...

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4th international conference on Network Communication and Information security, ICNCIS 2024

作者： Li, Yong Gu, Jian Qiu, Jinyi He, Wenbo Zuo, Jiashuo State Grid Shaoxing Power Supply Company Zhejiang Shaoxing312000 China Department of Electronic and Communication Engineering North China Electric Power University Hebei Baoding071003 China

ISBN: (数字)9781510688261

ISBN: (纸本)9781510688254

With the rapid development of the power Internet of Things and the increasing number of IoT devices and application scenarios, new requirements are put forward for the reliability and efficiency of equipment access certification. Aiming at the problems of low efficiency and malicious attack of traditional authentication methods, this paper proposes a group authentication algorithm based on regional grouping and aggregate signcryption. Firstly, according to the characteristics of IoT devices, a distributed authentication scheme based on regional grouping is designed. Then each group relies on aggregation signcryption technology for group authentication of IoT devices. Finally, the calculation and communication cost of the algorithm are compared and analyzed. The results show that the proposed algorithm can improve the authentication efficiency. © 2025 SPIE.

关键词： Network security computer security Internet of things Local area networks Data transmission Information security Telecommunications Zinc Computing systems Fiber optic gyroscopes

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Methods of increasing data reliability based on distributed and parallel technologies based on blockchain

Methods of increasing data reliability based on distributed ...

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international conference on Artificial Intelligence, Blockchain, Computing and security, ICABCS 2023

作者： Makhmadiyarovich, Nazarov Fayzullo Sherzodjon, Yarmatov Samarkand State University named after Sharof Rashidov Samarkand Uzbekistan

ISBN: (纸本)9781032669663

This article examines directions and mechanisms for increasing data reliability in computer networks. Currently, the rapid development of information technologies, the rapid growth of data flow, high-quality data processing carried out in network technologies, and the increase in the volume of data lead to an increase in the problem of data reliability. It is an urgent issue to find solutions based on the use of modern technologies to solve these problems. The simultaneous processing of various types of data in information systems, video, audio, text and digital data, creates big data. The variety of data types in bigdata creates the problem of quality data processing, which greatly affects the reliability of the data. Research shows that breaches of data integrity mainly manifest in three directions. In this case, there is a violation of the reliability of interrelated data in data transmission and storage, in the processing of large volumes of data and in the transcription of video data. It is created due to errors created during data transmission based on artificial and natural redundancy. To solve the mentioned problems, increasing data reliability based on blockchain mechanisms for payment systems in data transmission, increasing data reliability based on error minimization mechanisms in video information systems, and distributed computing and parallel mechanisms in large-scale information systems based on methods of increasing data reliability are researched. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Information systems

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DDoS Mitigation Dilemma Exposed: A Two-Wave Attack with Collateral Damage of Millions 19th

DDoS Mitigation Dilemma Exposed: A Two-Wave Attack with Coll...

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19th international conference on security and Privacy in Communication networks

作者： Shi, Lumin Li, Jun Sisodia, Devkishen Zhang, Mingwei Dainotti, Alberto Reiher, Peter Univ Oregon Eugene OR 97403 USA Georgia Inst Technol Atlanta GA USA UCLA Los Angeles CA USA

ISBN: (纸本)9783031649530;9783031649547

While mitigating link-flooding attacks on the Internet has become an essential task, little research has been done on how an attacker can further attack and abuse the mitigation solutions themselves. In this paper, we propose a two-wave attack with collateral damage of millions (or Carom), a new link-flooding attack that poses a mitigation dilemma for multiple simultaneously attacked networks, which must either endure the flooding attack or suffer unwanted side effects in mitigating the attack. Composed of practical components, the Carom attack aims to maximize the burden on attack mitigation systems and the collateral damage to defending networks, thereby wreaking havoc on large swaths of the Internet. After modeling real-world mitigation solutions, we evaluated the attack against the mitigation solutions with real-world datasets, showing the feasibility of the attack and quantifying the amount of damage it can inflict on today's Internet. We hope that this work can motivate the improvement of existing link-flooding mitigation solutions.

关键词： Link-flooding attack distributed denial-of-Service (DDoS) Collateral damage

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Evaluation of Microcontroller-Based SRAM PUF and the Authentication Scheme 24

Evaluation of Microcontroller-Based SRAM PUF and the Authent...

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4th international conference on computer, Internet of Things and Control Engineering

作者： Zhang, Yuting Ge, Yunfei Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China

ISBN: (纸本)9798400711848

This paper tackles the security challenges of the Internet of Things (IoT) and introduces Physical Unclonable Functions (PUFs) as a low-cost, hardware-based security solution for resource-constrained IoT devices. Traditional password systems and centralized key management are difficult to implement in distributed IoT networks. PUFs leverage inherent fabrication variances to provide unique, non-replicable identities for devices. This study focuses on Static Random Access Memory (SRAM) PUFs, exploiting power-up values to generate device-specific keys or identifiers. Through experiment on the SRAM chip of an STM32F407ZGT6 microcontroller, we show microcontroller-based SRAM PUF can have 94.18% reliability, 48.09% uniqueness and 50.40% uniformity. It passes most of the National Institute of States and Technology (NIST) statistical tests, exhibiting good randomness. It can realize similar performance in terms of security, compared with other implementations and thus can be used as an equally qualified alternative for authentication and potentially other security applications. In addition, we propose mathematical models to compute False Rejection Rate (FRR) and False Acceptance Rate (FAR) of PUF-based authentication scheme and a threshold determination approach to mostly satisfy given FAR and FRR. The authentication scheme using the implemented SRAM PUF can realize 8.05 x 10(-10) FRR and 2.36 x 10(-10) FAR, for the case of 128-bit key length.

关键词： Hardware security SRAM PUF microcontroller authentication

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Advanced ARP Attack Protection in SDNs Using Deep Learning Approach 3

Advanced ARP Attack Protection in SDNs Using Deep Learning A...

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3rd IEEE international conference on Blockchain and distributed systems security, ICBDS 2024

作者： Kumar, M. Anand Purohit, Kamelsh Chandra Bhatt, Jaishankar Semuwal, Girija Shankar Presidency University School of Information Science Bengaluru India Graphic Era Deemed to be University Department of Computer Science Dehradun India Graphic Era Hill University Department of Media and Mass Communication Dehradun India

ISBN: (纸本)9798350354348

Software Defined networks have developed as a transformative standard in network architecture, providing centralized control, and dynamic supervision of network resources. In recent past several advancements have been made to enhance the capabilities and efficiency of SDN models. A prominent development involves the incorporation of Software-Defined Networking with emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to facilitate smarter and more adaptive network management. Additionally, advancements in SDN security have been a focal point, with the exploration of new techniques to detect and mitigate various types of cyber threats, including those specific to SDN environments However, the openness and flexibility of SDNs also expose them to security vulnerabilities, with Address Resolution Protocol (ARP) attacks being a prominent threat. This research paper investigates the critical challenges posed by most common ARP Protocol attacks such as spoofing attack and Denial-of-Service attacks in contemporary network environments. As these attacks persist as serious threats to network integrity and availability. This research paper explores the use of Deep Learning algorithms for the detection and mitigation of ARP assaults in SDN networks. This research paper presents an in-depth analysis of the challenges posed by ARP attacks in SDNs and propose a novel approach leveraging deep learning techniques for enhanced security. The proposed framework is evaluated through extensive simulations and real-world scenarios, demonstrating its effectiveness in preventing ARP spoofing and DoS attacks. © 2024 IEEE.

关键词： Cyber attacks

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Analysis on the consensus algorithms with reputation-based incentives in the healthcare blockchain networks

Analysis on the consensus algorithms with reputation-based i...

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2024 IEEE international conference on Signal Processing, Informatics, Communication and Energy systems, SPICES 2024

作者： Sajna, S. Pillai, Manu J TKM College of Engineering Affiliated to APJ Abdul Kalam Technological University Dept of Computer Science and Engineering Kerala India

ISBN: (纸本)9798350376135

Blockchain technology has gained significant attention in the healthcare sector due to its potential to address challenges related to data security, integrity, and interoperability. One critical aspect of blockchain networks is the consensus mechanism, which ensures agreement among distributed nodes on the validity and ordering of transactions. In healthcare blockchain networks, achieving consensus is particularly challenging due to the sensitive nature of healthcare data and the diverse interests of stakeholders. Traditional consensus mechanisms may not suffice to incentivize participation and ensure trust in such environments. This paper presents an analysis of reputation-based incentives as a mechanism to facilitate consensus in healthcare blockchain networks. Reputation systems assign scores or ratings to network participants based on their past behaviour, contributions, and reliability. By incorporating reputation-based incentives into the consensus process, healthcare blockchain networks can incentivize honest behaviour, discourage malicious actors, and improve the overall reliability and trustworthiness of the network. © 2024 IEEE.

关键词： Consensus healthcare blockchain incentives reputation

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RAPID-AV: Realtime Adaptive and Intelligent Detection For AV's Against DDoS Attacks 18

RAPID-AV: Realtime Adaptive and Intelligent Detection For AV...

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18th IEEE international conference on Advanced networks and Telecommunications systems, ANTS 2024

作者： Kotha, Aditya Venkanna, U. International Institute of Information Technology Department of Computer Science and Engineering Naya Raipur India National Institute of Technology Department of Computer Science and Engineering Warangal India

ISBN: (纸本)9798350391725

Autonomous vehicles (AVs) increasingly rely on vehicle-to-everything (V2X) networks for communication. However, due to the devices' heterogeneity, they are more susceptible to attacks like distributed denial of service (DDoS), resulting in packet loss and transmission delays. Existing solutions to these issues often create bottlenecks and lack post-attack recovery mechanisms. To solve these problems, this paper proposes RAPID-AV, an ML-based approach that uses programmable P4 switches for real-time detection and mitigation of DDoS attacks in AV networks. The proposed system uses a threefold strategy: collect traffic statistics from AV, use P4-based programmable packet processing for anomaly detection, and use majority voting to mitigate attacks. In our experiments, we found that the decision tree algorithm achieves an accuracy of 94.33% in distinguishing traffic from DDoS traffic. In addition, RAPID-AV demonstrated a nearly 10% reduction in CPU load during attacks and maintained consistent communication between AV and RSU. This approach can help improve AV network security while addressing the limitations of existing solutions. © 2024 IEEE.

关键词： Network security

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Affinity and Class Probability based Fuzzy Support Vector Machine for Path Loss Prediction in 5G Communication System

Affinity and Class Probability based Fuzzy Support Vector Ma...

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2024 international conference on distributed systems, computer networks and Cybersecurity, ICDSCNC 2024

作者： Cong, Zhiru Wang, Shuqing Inner Mongolia Electronic Information Vocational and Technical College Department of Electronics and Automation Hohhot China China United Network Communications Co. Ltd Department of Office/Security Supervision Hohhot China

ISBN: (纸本)9798350375442

Wireless propagation channel is a primary factor for optimizing and planning 5G communication system. Predicting path loss in 5G plays a vital role in optimizing performance of network and ensure appropriate communication by determining signals over distance. However, path loss remains a challenge in 5G system because of signal propagation in different environment which results in minimized and unreliable network performance. This research proposes Affinity and Class Probability based Fuzzy Support Vector Machine (ACPFSVM) to predict the path loss in 5G communication system. In the traditional SVM, the ACPF is involved for prediction to handle uncertainties efficiently in data which results in more robust and accurate performance. The Gaussian filter is applied to remove a noise by smoothening the images which minimize high-frequency noise while conserving significant structural features. Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) are applied to extract the features by capturing local texture patterns effectively. The proposed ACPFSVM obtains a less Mean Average Error (MAE) of 0.083 compared to existing methods like Random Forest (RF), Linear Regression (LR), and SVM respectively. © 2024 IEEE.

关键词： 5G mobile communication systems

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