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检索条件"任意字段=6th IEEE International Conference on Distributed Computing in Sensor Systems"

共 6276 条记录，以下是191-200 订阅

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Study on distributed Multi-Level Security Scheme For Cloud computing 6

Study on Distributed Multi-Level Security Scheme For Cloud C...

引用

6th international conference on Inventive Computation Technologies, ICICT 2023

作者： Sathishkumar, G. Siva, P. Anto Maria Joseph, D. Santhosh, R. Reshma, R. Department of Computer Science and Engineering Faculty of Engineering Karpagam Academy of Higher Education Tamil Nadu Coimbatore India

ISBN: (纸本)9798350398496

Cloud computing seems to be a scalable and realistic distributed computing platform that delivers resources as a service. One of the major difficulties impeding cloud computing development is data security in the cloud. the security vulnerabilities in cloud computing and other cloud services slow down cloud computing growth and difficulties with data protection and privacy. In this newcontext, cloud service customers must be cautious about data breaches. this article studies a solution to current diverse security challenges that have arisen as a result of the service demonstrating that the offered methods are provably safe and very efficient. the solution comprises a distributed multi-level security scheme for processing the information involved in cloud computing. the proposed scheme evaluates the most significant encryption techniques generally used in various industries like AES (Advanced Encryption Standard), Blowfish, 3DES (Data Encryption Standard), CAST128, and RC4 (Rivest Cipher 4). the proposed model with these encryption techniques ensure minimal energy consumption in cloud computing with maximum speed. Moreover, to increase the security of the data, various cryptographical algorithms are applied, analyzed, and compared in an OpenStack environment. © 2023 ieee.

关键词： Energy utilization

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Publishing Asynchronous Event Times with Pufferfish Privacy 18

Publishing Asynchronous Event Times with Pufferfish Privacy

引用

18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Ding, Jiaxin Ghosh, Abhirup Sarkar, Rik Gao, Jie Shanghai Jiao Tong Univ Shanghai Peoples R China Univ Cambridge Cambridge England Univ Edinburgh Edinburgh Midlothian Scotland Rutgers State Univ New Brunswick NJ USA

ISBN: (纸本)9781665495127

Publishing data from IoT devices raises concerns of leaking sensitive information. In this paper we consider the scenario of publishing data on events with timestamps. We formulate three privacy issues, namely, whether one can tell if an event happened or not;whether one can nail down the timestamp of an event within a given time interval;and whether one can infer the relative order of any two nearby events. We show that perturbation of event timestamps or adding fake events following carefully chosen distributions can address these privacy concerns. We present a rigorous study of privately publishing discrete event timestamps with privacy guarantees under the Pufferfish privacy framework. We also conduct extensive experiments to evaluate utility of the modified time series with real world location checkin and app usage data. Our mechanisms preserve the statistical utility of event data which are suitable for aggregate queries.

关键词： Privacy Differential privacy Publishing Perturbation methods Time series analysis Nails sensor systems

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Foundations of In-Network Quantum computing for Future Communication Networks 33

Foundations of In-Network Quantum Computing for Future Commu...

引用

33rd ieee international conference on Computer Communications and Networks (ICCCN)

作者： Boeck, Yannik Boche, Holger Bassoli, Riccardo Fitzek, Frank H. P. Tech Univ Munich Chair Theoret Informat Technol D-80333 Munich Germany Munich Ctr Quantum Sci & Technol MCQST Munich Germany MQV Munich Germany Tech Univ Dresden CeTI Deutsch Telekom Chair Commun Networks Dresden Germany Tech Univ Dresden BMBF Res Hub 6G Life TU Dresden Dresden Germany

ISBN: (纸本)9798350348439;9798350384611

In-Network computing has brought computing and communication together at every communication node in the digital world, this work lays the foundations for doing the same in the quantum world, improving communication properties in the process - a combination of quantum computing and quantum communication. Full network softwarization, in-network intelligence, and massive connectivity will create an unprecedented demand for computing resources in the digital world. Accordingly, the scientific and industrial communities have begun to explore technologies such as quantum computing and have made significant efforts to demonstrate an algorithmic advantage for various problems. However, practical quantum computers are resource-inefficient and difficult to build. this article introduces a new communication paradigm leading to the concept of quantum in-network computing in the context of entanglement-assisted communication and computing for inherent distributed resilience and sensing. We review the fundamentals of digital hardware as characterized by Turing's computability theory and demonstrate their relevance to mathematically rigorous characterizations of gate-based quantum computing. We then provide such a characterization using methods from effective analysis, leading to significant results that reveal the inherent theoretical limitations of universal gate-based quantum computers. these results support our assessment that gate-based quantum in-network computing is only possible through specialized, non-universal solutions that are seamlessly integrated with high-performance digital computing.

关键词： In-network quantum computing universal quantum computing Turing machines network as a sensor entanglement-assisted communications network resilience

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An novel integrated optimization approach for reconfiguring distribution network with distributed generation 6

An novel integrated optimization approach for reconfiguring ...

引用

6th ieee international Electrical and Energy conference, CIEEC 2023

作者： Bai, Chunyan Wang, Fei School of Electrical Engineering and Automation Jiangsu Normal University Xuzhou China

ISBN: (纸本)9798350346671

this paper presents a modified immune particle swarm optimization (MIPSO) algorithm and a new voltage stability difference index (VSDI) to solve distribution network reconfiguration (DNR) and distributed generation (DG) allocation problems, whose objectives are to reduce total real power loss, enhance the voltage stability and improve the voltage profile of a distribution system. the VSDI is put forward to determine the most sensitive buses to voltage collapse as candidate installation buses of DG allocation. the proposed MIPSO algorithm and VSDI are applied to ieee 33- and 69-bus distribution systems considering eight different scenarios, and the obtained results demonstrate the effectiveness of the proposed MIPSO algorithm and VSDI on solving DNR and DG allocation problems of the distribution system. © 2023 ieee.

关键词： distributed power generation

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Enhancing Energy Efficiency and Security in Wireless sensor Networks: A Survey and Proposed Methodology Integrating Prediction Algorithms and Deep Neural Networks 6

Enhancing Energy Efficiency and Security in Wireless Sensor ...

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6th international conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Shafiuddin, Shaik Krishna, Konda Hari Mohan Babu University School of Computing Department of Computer Science and Engineering Andhra Pradesh Tirupati India

ISBN: (纸本)9798331505790

this research study provides a complete assessment of energy- and trust-aware techniques in IoT-WSNs, emphasizing the significant problems and limits of current methodologies. Traditional methodologies frequently face challenges such as excessive processing overhead, difficulty reaching real-time optimal solutions, and increased delay, especially in large-scale or resource-constrained contexts. To solve these issues, the paper suggests a new approach that combines powerful prediction algorithms, deep neural networks, and strong security frameworks. the process entails initializing exact inputs and simulation settings, modeling advanced prediction algorithms, developing deep neural networks, and constructing resilient sensor nodes, all while implementing extensive security measures. the suggested approach seeks to considerably improve energy efficiency, network lifetime, and security by focusing on mobile sink movement prediction and network operation optimization. this study not only covers existing methodologies, but also shows the promise of the proposed methodology through extensive analysis and preliminary results, demonstrating its ability to overcome the limits of present WSN deployments. © 2024 ieee.

关键词： Prediction models

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distributed Nash Equilibrium Seeking of Second-Order Multi-Agent systems Under Unknown False Data Injection Attacks 6

Distributed Nash Equilibrium Seeking of Second-Order Multi-A...

引用

6th international conference on Industrial Artificial Intelligence, IAI 2024

作者： Feng, Zhi Hu, Guoqiang Dong, Xiwang Lu, Jinhu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore

ISBN: (纸本)9798350356618

this paper investigates resilient adaptively distributed Nash Equilibrium (NE) seeking problems for noncooperative games of double-integrator players under malicious attacks, i.e., false data injection (FDI) attacks. Different from distributed NE seeking in many existing literature under ideal environments, it is challenging to achieve the NE seeking under unknown and unbounded FDI attacks. An attack-resilient NE seeking architecture that is distributed, is established by means of the consensus-based gradient play together with an attack identifier to deal with the impacts of FDI attacks. Another key characteristic is that malicious FDI attacks are allowed to be completely unknown and unbounded. the global asymptotic convergence of the proposed distributed NE seeking algorithm to-ward the NE is guaranteed. Lastly, numerical simulation results are provided to illustrate the effectiveness of the proposed algorithms. © 2024 ieee.

关键词： Multi agent systems

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Exploration of Use-Case-Dependent Modeling Approach for distributed DC-Grids 6

Exploration of Use-Case-Dependent Modeling Approach for Dist...

引用

ieee 6th international conference on Direct Current Microgrids (ICDCM)

作者： Lavery, Melanie Schwanninger, Raffael Marz, Martin Friedrich Alexander Univ Inst Power Elect Erlangen Germany

ISBN: (纸本)9798350363647;9798350363630

In this paper, the previously described Use-Case-Dependent Modeling Approach is evaluated and its usefulness for grid simulation is explored. One of the main merits of the approach is its application in automated system analysis. Previous results also suggest a reduced usage of computing resources. this however has not yet been systematically tested and properly verified. therefore, to inspect the validity of this approach, the methodology is explained and simulation results are compared to measurements of the modeled DC system. It is shown that the grid models adequately represent the system's behavior and the simulation results can therefore be used for system analysis. Discrepancies can be explained by an insufficient modeling of the measured system's damping elements. these differences are however small enough to be mitigated by usually applied error margins, especially for system stability analysis. Although more work is required for full verification, the validity and versatility of the approach is demonstrated.

关键词： DC grids component modeling system analysis

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distributed Attacks Classification Based on Radical Basis Function and Particle Swarm Optimization In Hypervisor Layer 6

Distributed Attacks Classification Based on Radical Basis Fu...

引用

6th international conference on Information systems and Computer Networks, ISCON 2023

作者： Shukla, Aditya Kumar Sharma, Ashish GLA University Department of Computer Engineering and Applications UP Mathura India

ISBN: (纸本)9798350346961

the term 'cloud computing' refers to a concept for on-demand provisioning of computer resources (including hardware and software) through the Internet. Cloud computing's primary benefits lie in the time and money savings it may provide to IT departments. While cloud computing offers many benefits It also raises many safety considerations. these include data privacy, data availability, data placement, data security credential, license, access management, network security, web data protection, virtual devices protection, etc. Recently, machine learning has shown to be an effective tool for safeguarding the cloud. In order to automate the process of identifying cloud assaults with better accuracy than any other technology, machine learning algorithms are trained on numerous legitimate datasets to develop models. To mitigate the effects of DDoS invasions, our research suggests implementing a detection method at the hypervisor layer. As a means of detecting and categorizing DDoS attacks in the communication between virtual computers, the suggested detection method combines the particle swarm optimization (PSO) with radial basis function (RBF). High classification accuracy against DDoS attacks is the focus of our investigation and recommended method.. © 2023 ieee.

关键词： Data privacy

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sensor Data Augmentation from Skeleton Pose Sequences for Improving Human Activity Recognition

Sensor Data Augmentation from Skeleton Pose Sequences for Im...

引用

6th international conference on Activity and Behavior computing (ABC)

作者： Zolfaghari, Parham Rey, Vitor Fortes Ray, Lala Kim, Hyun Suh, Sungho Lukowicz, Paul Saarland Univ Dept Comp Sci Saarbrucken Germany German Res Ctr Artificial Intelligence DFKI Kaiserslautern Germany RPTU Kaiserslautern Landau Dept Comp Sci Kaiserslautern Germany Seoul Natl Univ Sci & Technol Dept Elect & Informat Engn Seoul South Korea

ISBN: (纸本)9798350375510;9798350375503

the proliferation of deep learning has significantly advanced various fields, yet Human Activity Recognition (HAR) has not fully capitalized on these developments, primarily due to the scarcity of labeled datasets. Despite the integration of advanced Inertial Measurement Units (IMUs) in ubiquitous wearable devices like smartwatches and fitness trackers, which offer self-labeled activity data from users, the volume of labeled data remains insufficient compared to domains where deep learning has achieved remarkable success. Addressing this gap, in this paper, we propose a novel approach to improve wearable sensor-based HAR by introducing a pose-to-sensor network model that generates sensor data directly from 3D skeleton pose sequences. our method simultaneously trains the pose-to-sensor network and a human activity classifier, optimizing both data reconstruction and activity recognition. Our contributions include the integration of simultaneous training, direct pose-to-sensor generation, and a comprehensive evaluation on the MM-Fit dataset. Experimental results demonstrate the superiority of our framework with significant performance improvements over baseline methods.

关键词： Human activity recognition data augmentation pose estimation multi-modal learning

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VDCM-based distributed secondary regulation research strategy for DC microgrids 6

VDCM-based distributed secondary regulation research strateg...

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6th ieee international conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Liu, Hongyu Wang, Zhicheng Liu, Feifei Xinjiang University School of Electrical Engineering Urumqi China Shenyang Agricultural University College of Information and Electrical Engineering Shenyang China Northeast Electric Power University School of Electrical Engineering Jilin China

ISBN: (纸本)9798350389418

Compared to AC microgrids, DC microgrids do not need to consider frequency, phase, reactive power, etc., but the fluctuation of loads will adversely affect the DC bus voltage. Nonetheless, the conventional MPC (Model Predictive Control) control approaches have been found inadequate in directly modulating the voltage, underscoring the imperative for an innovative control paradigm. To address this, the present study introduces a novel, distributed secondary regulation control strategy grounded in VDCM, meticulously designed to preserve the stability of the DC bus voltage by dynamically responding to load fluctuations and system disturbances. In this paper, the virtual DC generator is used as the underlying control strategy, so that the converter in the microgrid can simulate the dynamic characteristics of the DC generator, which can reduce the impact of power fluctuations on the bus voltage. On this basis, a distributed communication network, combined with a dynamic consistency algorithm, is used to propose a distributed secondary voltage regulation method based on VDCM, which further maintains the stability of the DC bus voltage under disturbances. Conclusively, a robust simulation platform, developed within the MATLAB/Simulink environment, demonstrates that the proposed strategy adeptly sustains the average system voltage stability, even amidst fluctuating conditions, thereby validating its efficacy and robustness. © 2024 ieee.

关键词： Predictive control systems

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