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检索条件"任意字段=23th IEEE International Conference on Distributed Computing Systems"

共 11469 条记录，以下是81-90 订阅

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A Column Sparse Controller Design for distributed Networked Control systems 8th

A Column Sparse Controller Design for Distributed Networked...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Guan, Yanpeng Yin, Hongjie Sun, Chao Yao, Qingsheng Shanxi University Taiyuan030013 China Kunming Shipborne Equipment Research and Test Center Kunming650216 China

ISBN: (纸本)9789819602933

this paper presents a distributed structured controller design method in the case of finite number of subsystems with sensor failures. the constraint on the number of sensor failures is represented by a cardinality constraint on the controller gain matrix. A mixed integer programming method is employed to deal with this type of column cardinality constraint. By using the Lyapunov functional method, we present a sufficient condition that guarantees the H∞ asymptotic stability of the closed-loop system. And a column sparse controller design method is presented in the form of linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness of the developed approach. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Lyapunov functions

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Intrusion Detection at the Edge computing: A Deep Learning Approach Using the UNSW-NB15 Dataset

Intrusion Detection at the Edge Computing: A Deep Learning A...

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international conference on Communication systems and Network Technologies (CSNT)

作者： Vipin Kumar Vivek Kumar Abhay Pratap Singh Bhadauria Jay Dixit Amit Kumar Department of Computer Science Gurukula Kangri (Deemed to be University) Haridwar India Department of Computer Engineering & Applications GLA University Mathura Department of Computer Engineering & Applications GLA University Mathura UP

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Edge computing has transformed technology by enabling seamless connections between IoT devices, but it also introduces significant security challenges. EC is crucial for providing minimal latency processing and reducing the load on centralized servers, ensuring timely and scalable intrusion detection for IoT environments. the findings underscore the potential of combining edge computing, IoT, and deep learning to address evolving security challenges in distributed systems. To mitigate these risks, efficient models for detecting malicious activities are crucial. this study investigates the application of edge computing, Internet of things (IoT), and deep learning to improve the performance of Intrusion Detection systems (IDS). By leveraging the UNSW-NB15 dataset, the research assesses the capability of deep learning models to identify and mitigate cyber threats effectively. the results demonstrate better performance, showing their suitability for real-time security applications. these findings highlight the potential of intelligent intrusion detection systems powered by robust datasets and deep learning for addressing evolving security threats in edge computing environments.

关键词： Deep learning Image edge detection Computational modeling Intrusion detection Real-time systems Internet of things Security Servers Long short term memory Edge computing

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Enhancing Scalability: A Complete Tree Sharding Architecture Towards IoT 18th

Enhancing Scalability: A Complete Tree Sharding Architecture...

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18th international conference on Wireless Artificial Intelligent computing systems and Applications, WASA 2024

作者： Zhang, Luyi Wang, Yujue Ding, Yong Liang, Hai Yang, Changsong Zheng, Haibin Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China Hangzhou Innovation Institute of Beihang University Hangzhou310052 China Institute of Cyberspace Technology HKCT Institute for Higher Education Hong Kong Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies Shenzhen518055 China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9783031714665

With the rapid proliferation of integration of blockchain and IoT, traditional centralized architectures and single-node processing have been effectively solved, but scalability of blockchain have become inadequate to meet the demands of high-load environments. Sharded blockchain brings an innovative approach to tackle the scalability of blockchain and has the potential to greatly enhance the performance of IoT based on blockchain. this paper introduces CTS towards IoT – complete tree sharding that overlaps shards to enable a little shards to retain records of other shards, facilitating the validation of cross-shard transactions as intra-shard transactions. A tree sharding consensus mechanism that relies on the complete tree architecture is proposed to ensure consistency among interconnected shards during the execution of cross-shard transactions. A prototype for CTS towards IoT is simulated and the findings demonstrate that CTS can enhance transaction throughput by a factor of 1.3 when compared to state of the art layered sharding systems observed in a system consisting of 15 shards and 1500 nodes. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： distributed ledger

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distributed Event-Triggering Secondary Frequency Control of Islanded Microgrids Under DoS Attacks 8th

Distributed Event-Triggering Secondary Frequency Control of...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Zhou, Lihua Zhang, Changda Du, Dajun Fei, Minrui Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai China School of Electrical Engineering Hebei University of Science and Technology Hebei China

ISBN: (纸本)9789819602247

High reliability and efficiency of microgrids are being threatened by cyber attacks. this paper investigates a Secondary Frequency Control Scheme (SFCS) for an islanded microgrid with Event-Triggering Mechanism (ETM) under Denial of Service (DoS) attacks. Firstly, the microgrid dynamic model is reviewed and control objectives are formulated. Secondly, a cooperative frequency control scheme combined with distributed event-triggering mechanism is presented to achieve the desired frequency control under DoS attacks. thirdly, the stability and Zeno Behaviour of the closed-loop system are analysed by Lyapunov theory. Finally, simulation results of the microgrid are explored to verify the effectiveness of the proposed frequency control scheme. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cyber attacks

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602933

the proceedings contain 158 papers. the special focus in this conference is on Life System Modeling and Simulation and Intelligent computing for Sustainable Energy and Environment. the topics include: A Method for Evaluating the Operating Health of Wind Turbines Under Wake Effect;toward Next-Generation Buildings: A Review of Renewable Energy Integration and Intelligent Building Energy Management Technologies;improving the Construction of a Multi-modal Underwater Image Recognition System for Anomaly Detection in Nuclear Power Plant Cooling Source Areas;A Novel Anti-noise Fault Diagnosis Method for Nuclear Energy Steam Turbine Based on VCformer;Short-Term Photovoltaic Power Forecasting Using Multi-timescale Information Based FFTformer Model;wind Power Forecasting Model Based on Feature Processing and Deep Hybrid Kernel Extreme Learning Machine;optimal User-Side Energy Arbitrage Strategy in Electricity Market with Accurate Battery Model Using Benders Decomposition;a Novel distributed Economic Dispatch Method for Smart Grid with Time-Varying Feedback Gain;benefits, Barriers, and Human Factors of V2X Implementation – A Brief Review;a General Pattern of Permanent Magnet Arrangement for Design Optimization of a Reluctance Magnetic Gear with Enhanced Torque Density for Electric Vehicles;wind Power Scheduling Deviation Compensation Based on Dual-Frequency Pulse Control;a Comprehensive Simulation and Validation of Single Particle Aging Mechanism Model for Lithium-Ion Batteries;semi-supervised State of Health Estimation for Lithium-Ion Batteries via Dynamical Self-encoding;a Reduce-Order Model to Understand the Multiscale Coupling of Battery Electrochemical-thermal Performance;RUL Prediction for Lithium-Ion Batteries Based on Sequence Decomposition and Transformer Networks;An Estimation Method of State of Health of Sodium-Ion Batteries Based on TCN.

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602315

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Scalable Peer-to-Peer Energy Trading System With Microgrid Coalitions

Scalable Peer-to-Peer Energy Trading System With Microgrid C...

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Smart Grid and Green Energy (ICSGGE), international conference on

作者： Jianheng Lan Fengji Luo Xiangyu Li School of Civil Engineering The University of Sydney Sydney Australia Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

ISBN: (数字)9798331542139

ISBN: (纸本)9798331542146

Widespread deployment of distributed renewable energy sources fosters the research and development of peer-topeer (P2P) energy trading systems. Despite the benefits this energy-sharing paradigm can bring to the stakeholders in modern energy systems, how to effectively facilitate energy trading among a large number of energy prosumers (producers-and-consumers) remains a non-trivial challenge. this paper proposes a new P2P energy trading system to support energy trading among prosumers located in geographically distributed microgrids. Backboned by a clustering mechanism that dynamically organizes the microgrids into multiple coalitions, the system can enable energy trading within a microgrid and among different microgrids, making it scalable to cater for the energy trading needs of widearea prosumers. Numerical simulation is conducted on an ieee 33-bus benchmark distribution system to validate the proposed method.

关键词： Green energy Microgrids Benchmark testing Numerical simulation throughput Peer-to-peer computing Smart grids Computational efficiency Stakeholders Research and development

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602247

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Generative AI for Automated Security Operations in Cloud computing

Generative AI for Automated Security Operations in Cloud Com...

引用

AI in Cybersecurity (ICAIC), international conference on

作者： Advait Patel Pravin Pandey Hariharan Ragothaman Ramasankar Molleti Diwakar Reddy Peddinti Broadcom Tiffany Co Athenahealth Options Clearing Corporation Independent Researcher

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

New opportunities in cloud computing have brought many new risks that require effective protection of dynamic distributed environments. Introducing a new formative technology, generative AI, to cloud security has far-reaching benefits for automating threat detection, real-time incident addressing, and vulnerability management. this paper focuses on extending generative AI with cloud security tools like AWS GuardDuty and Google Cloud Security Command Center; the contemplation of accuracy enhancement and response efficiency highlights its aim. Concerning actual applications such as SOAR systems, the study demonstrates how media industry giants, such as Netflix and JPMorgan Chase, have used AI to minimize risk factors while increasing operational efficiency. the paper also discusses the significant increase in response time, enhanced detection accuracy, and the shift to proactive security strategies brought by generative AI. Drawing attention to AI systems’ opportunities, the study examines the subsequent issues connected with AI applications, including over-dependence on AI tools, adversarial risk to models, and the complex nature of decisionmaking in the context of AI systems. the present study also highlights the importance of generative AI in strengthening the defense of the cloud environment, but, at the same time, it recognizes the significance of preventive efforts and planned action plans to manage these technologies efficiently.

关键词： Technological innovation Accuracy Generative AI Cloud computing security Organizations Real-time systems threat assessment Time factors Protection Monitoring

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Quantum Long Sort-Term Memory-based Identification of distributed Denial of Service Attacks

Quantum Long Sort-Term Memory-based Identification of Distri...

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AI in Cybersecurity (ICAIC), international conference on

作者： Sarvapriya Tripathi Himanshu Upadhyay Jayesh Soni Electrical and Computer Engineering Florida International University Miami USA

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

distributed Denial of Service (DDoS) is defined as an attack targeting a server, where the server is overwhelmed by an overflow of traffic, leading to a computer system being compromised. To prevent these attacks from happening, thus allowing the computer systems to maintain their normal behavior, a long short-term memory (LSTM) Time-Series model can recognize sequential characteristics in the data in order to predict whether a DDoS attack is occurring. Our approach leverages various aspects of network traffic such as Flow ID, Source IP, Destination IP, and Destination Port, and analyzes the accuracy and reliability using LSTMs to improve DDoS attack prediction accuracy. In this study we analyzed the relative efficiency of Quantum LSTM (QLSTM) over that of Classical LSTM, and found that both Quantum and Classical LSTM models train quickly and within a few epochs the accuracy increases to 0.99 and above. the validation of the models proved that QLSTM achieved better Recall, Accuracy, Precision, and F1 scores as compared to classical LSTM, making it an ideal candidate for DDoS attack predictions. this study proves the potential of applying deep learning techniques to strengthen network security, which has become increasingly important with the rise of complex cybersecurity threats.

关键词： Accuracy Quantum computing Telecommunication traffic Predictive models Denial-of-service attack Servers IP networks Reliability Computer crime Long short term memory

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