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distributed Fusion Estimation for Nonlinear systems under Denial-of-Service Attacks using the Try-Once-Discard Protocol

Distributed Fusion Estimation for Nonlinear Systems under De...

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Robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Guangyuan Zhu Xin Chen College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

this paper tackles the challenge of distributed state fusion estimation in nonlinear, time-varying systems subjected to external denial-of-service (DoS) attacks. Given the susceptibility of network channels to such attacks, a transmission strategy employing the try-once-discard (TOD) protocol was introduced to reduce their impact. In this approach, each sensor in the network is linked to local estimators through multiple channels, with the TOD protocol determining the transmission priority. Data transmitted via the highest priority channel is retained, while data from other channels are discarded. A local estimator was constructed using the cubature Kalman filter (CKF), and a consensus-based approach was utilized to merge the local estimates, forming a distributed fusion estimation algorithm. the algorithm’s convergence was analyzed, and sufficient conditions for maintaining bounded filter error covariance were established, accounting for network disruptions and random nonlinearity. the proposed algorithm’s performance was demonstrated through numerical simulations.

关键词： Sufficient conditions Protocols Denial-of-service attack Robot sensing systems Numerical simulation Stability analysis Kalman filters State estimation Time-varying systems Numerical stability

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Load Redistribution Attack in Optimal Power Flow with Phase Shifting Transformers

Load Redistribution Attack in Optimal Power Flow with Phase ...

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Industrial Cyber-Physical systems (ICPS)

作者： Hongcheng Zhu Chensheng Liu Min Zhou Yang Tang Wenli Du School of Information Science and Engineering East China University of Science and Technology Shanghai China

With the increasing integration of distributed energy resources (DER) and corresponding fluctuations, phase shifting transformers (PSTs) have been considered as important electrical components to increase transmission capacity by integrating PST with optimal power flow (OPF). However, due to vulnerabilities of supervisory control and data acquisition (SCADA) systems, applications in power systems may be subject to various cyber-attacks. In this paper, we discuss the feasibility of load redistri-bution (LR) attacks against OPF with PST, and quantitatively evaluate the effect of LR attacks on power systems. Specifically, the interaction between LR attacker and OPF with PST is formulated as a Stackelberg game, where the attacker and power system, acting as the leader and follower, attempt to maximize and minimize the operation cost of power system, respectively. By replacing the lower OPF optimization with its Karush-Kuhn-Tucker (KKT) condition, the Stackelberg game is simplified into a single-level mixed integer programming, which can be easily solved. Simulations in the PJM 5-bus, ieee 14-bus and ieee 30-bus test systems verify the feasibility of LR attacks and quantitatively evaluate the effect of LR attacks on the operation cost of power systems.

关键词： Integer programming Costs Fluctuations SCADA systems Games Power systems distributed power generation

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Proceedings of ESPM2 2021: 6th international ieee Workshop on Extreme Scale Programming Models and Middleware, Held in conjunction with SC 2021: the international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of ESPM2 2021: 6th International IEEE Workshop o...

引用

6th international ieee/ACM Workshop on Extreme Scale Programming Models and Middleware, ESPM2 2021

ISBN: (纸本)9781665411400

the proceedings contain 6 papers. the topics discussed include: scalable parallel algorithm for fast computation of transitive closure of graphs on shared memory architectures;accelerating messages by avoiding copies in an asynchronous task-based programming model;parallel SIMD - a policy based solution for free speed-up using C++ data-parallel types;Taskflow-San: sanitizing erroneous control flow in taskflow graphs;performance evaluation of python parallel programming models: Charm4py and mpi4py;and evaluation of distributed tasks in stencil-based application on GPUs.

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Aspects of Security for Accelerating Artificial Intelligence inside Internet of things Centric distributed Storage Network 6

Aspects of Security for Accelerating Artificial Intelligence...

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6th international Multi-Topic ICT conference, IMTIC 2021

作者： Mustafa, Fawad Shaikh, Murtaza Hussain Kyungsung University Busan48434 Korea Republic of

ISBN: (纸本)9781665482943

the centricity of in-network storage is a methodology that allows the generated sensor data readings to be stored in slices, known as data fragments. Within the sensor network, fragments are stored at various storage nodes. As a result, the data is more secure. the IoT network shows failures and unauthorized admittance to the users. the role played, herein, by the storage nodes make them prone to various security attacks. In this research work, the preliminary investigation and the methods to employ to provide the solution for security and privacy problems in distributed sensor network storage. Deep learning technologies that are already in use in ioT contexts cannot assign compute tasks reasonably which leads to resources wasting. Artificial intelligence is made up of capabilities that assist gadgets in learning and processing information in the same way that people do. A quantifiable blend of artificial intelligence with the internet of things, popularly known as AAIoT, is something that is holding a promise of a more connected future. this article proposes an AAIoT based method for allocating each network layer's inference computation in a multi-layer internet of things system to each device this is, to the best of my knowledge, the first attempt to track down this criminal. When considering the cost of computing and communication, the design of this study effort is a programming algorithm to lower the response time. the simulation findings demonstrate that a method could improve the system's response time significantly. © 2021 ieee.

关键词： Internet of things

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Happy Hypoxia Early Detection Tool in IoT Based for COVID-19 Patients Using SpO2 sensor, Body Temperature and Electrocardiogram (ECG) 6

Happy Hypoxia Early Detection Tool in IoT Based for COVID-19...

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6th international conference on Informatics and computing, ICIC 2021

作者： Vernandhes, Wanda Salahuddin, N.S Sari, R.R Sri Poernomo Saptariani, Trini Universitas Gunadarma Master of Electro Information Technology Jakarta Indonesia Universitas Gunadarma Faculty of Computer Science and Technology Dept. Computer System Jakarta Indonesia Universitas Gunadarma Faculty of Industrial Technology Dept. Mechanical Engineering Jakarta Indonesia

ISBN: (纸本)9781665421553

this research was aims to design a prototype and application for early detection of Happy Hypoxia symptoms in COVID-19 patients based on the Internet of things (IoT). the experimental board consists of a microcontroller integrated with a pulse oximetry sensor, a heart rate sensor and a body temperature sensor. To determine the feasibility of the tool, an accuracy test is carried out. Accuracy shows the value of the proximity of the measurement results to the reference value or standard value. Accuracy is obtained by calculating the error value. the accuracy of the sensors used in this study refers to standard medical equipment that has been calibrated. In this study, the accuracy value was obtained by referring to the mean of error rate of each sensor. the sensor reading value is sent from the microcontroller to firebase as a cloud database and then displayed on the application dashboard as a user interface. From this data, it is hoped that it can help COVID-19 sufferers to detect the symptoms of Happy Hypoxia and help medical experts for prognostic or therapeutic purposes. © 2021 ieee.

关键词： COVID-19

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distributed Spatial-Temporal Demand and Topology Aware Resource Provisioning for Edge Cloud Services 6

Distributed Spatial-Temporal Demand and Topology Aware Resou...

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6th international conference on Fog and Mobile Edge computing(FMEC)

作者： Vu San Ha Huynh Radenkovic, Milena Wang, Ning Univ Nottingham Nottingham NG8 1BB England Univ Surrey Inst Commun Syst ICS 5GIC & 6GIC Guildford GU2 7XH Surrey England

ISBN: (纸本)9781665458702

Current edge cloud providers offer a wide range of on-demand private and public cloud services for customers. Predictive demand monitoring and supply optimisation are necessary to deliver truly elastic distributed edge cloud services with resizable resource and compute capacity to adapt to dynamically changing customer requirements. However, current state-of-the-art monitoring and provisioning systems remain reactive which often results in over or under service provisioning, incurring unnecessary costs for customers or deterioration in the quality of service for the end-user. this paper proposes an adaptive protocol, ARPP, that enables distributed real-time demand monitoring and automatic resource provision based on the dynamically changing spatial-temporal workload patterns. ARPP leverages distributed predictive analytics and deep reinforcement learning at the edges to predict the dynamically changing spatial-temporal demand and allocate the appropriate amount of resources at the right times and right locations. We show that ARPP outperforms benchmark and state of the art algorithms across a range of criteria in the face of dynamically changing mobile real-world topologies and user interest patterns.

关键词： Elastic edge cloud services network resource supply-demand

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Parallelizing Image Encryption Algorithm for Wireless sensor Networks 6

Parallelizing Image Encryption Algorithm for Wireless Sensor...

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6th international conference for Convergence in Technology (I2CT)

作者： Mohan, Prajval Vemparala, Rohit Anto, S. Vellore Inst Technol Sch Comp Sci & Engn Vellore Tamil Nadu India

ISBN: (纸本)9781728188768

In this paper, techniques to improve the overall efficiency of an image encoding algorithm that is specifically designed to be used in Wireless sensor Networks (WSN) are proposed. the inherent nature of WSN, which contains numerous network nodes each having its computational resources, makes the algorithm is being underutilized due to its sequential nature and hence there is a scope to improve speedup by applying the concepts of parallelization on it. the other avenues which are pertinent to the task are the usage of GPU for computation of large arrays as well as the concept of cluster computing to run the algorithm on a cluster of nodes. Another point of importance for such an algorithm is the utilization of memory and how to make its usage more efficient. Hence, the concept of pre-allocation is also applied to the algorithm to make it run faster. An in-depth study of the algorithm is conducted by considering various parameters such as the size and complexity of the key, histogram analysis, correlation values, etc.

关键词： Wireless sensor Network Parallelization GPU Preallocation Clustering Correlation coefficient Histogram Image Encryption Algorithm Keyspace NPCR UACI

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Exploiting Spatial and Temporal Features for Deep Learning Based Human Activity Recognition

Exploiting Spatial and Temporal Features for Deep Learning B...

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international conference on Parallel and distributed systems (ICPADS)

作者： Wenying Cao Gaotao Shi Tieguan Zhang International Engineering Institute Tianjin University Tianjin China College of Intelligence and Computing Tianjin University Tianjin China

Human activity recognition using inertial sensors has gained significant popularity and widespread adoption in various fields, while deep learning has emerged as the dominant approach, playing a pivotal role in enhancing performance. Nevertheless, existing algorithms often neglect the heterogeneity of sensors and fail to effectively extract contextual features from long-term time series data, resulting in low accuracy in activity recognition, especially for complex activities. this paper proposes a novel method called FUsion Transformer hUman activity REcognition(FUTURE). FUTURE exploits the feature fusion mechanism and designs a multi-scaled DenseNet to extract the spatial features so that the relationship between heterogeneous sensors can be captured. Furthermore, a customized multi-head attention model with less computational complexity is employed in FUTURE to capture global dependencies within the sensor data. Experimental results on multiple datasets validate that FUTURE achieves an average recognition accuracy of 95% for complex activities and the evaluation against the state-of-the-art demonstrates the superior performance of the FUTURE model in accurately classifying complex activities.

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distributed State Estimation for Fractional-Order Linear systems Based on A Network of Reduced-Order Centralized Observers

Distributed State Estimation for Fractional-Order Linear Sys...

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international conference on systems and Control (ICSC)

作者： Yu-Qing Zhang Da-Yan Liu Driss Boutat Yan-Qiao Wei INSA Centre Val de Loire Université d'Orléans PRISME EA 4229 Bourges Cedex France School of Electrical Engineering Yanshan University Qinhuangdao Hebei China

this paper considers a 6-dimensional fractional-order linear system equipped with a sensor network digraph containing 4 sensors. the objective is to develop a method for distributed state estimation. First, based on the assumption of strong connectivity, a compensation set is introduced to construct the transformation matrix. then, the relationship between the transformed state at each node and the transformed observable states of the 4 nodes is established. In the light of this relationship, 4 centralized fractional-order observers with dimensions smaller than 6, are employed to estimate the 4 observable states, thereby realizing distributed estimation. In the end, a numerical example is presented to verify the availability of the proposed method.

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Comparative E-Voting Security Evaluation: Multi-Modal Authentication Approaches

Comparative E-Voting Security Evaluation: Multi-Modal Authen...

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Blockchain computing and Applications (BCCA), international conference on

作者： Elsi Ahmadieh Nour El Madhoun Department Communications and Computer Networks Engineering Faculty of Technology Lebanese University Beirut Lebanon ISEP LISITE Laboratory France CNRS LIP6 Sorbonne Université Paris France

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

the decentralized, distributed ledger, a fundamental aspect of blockchain technology, plays a pivotal role in various sectors, including electronic voting (e-voting) systems. When considering e-voting, the significance of blockchain technology in boosting the security, transparency, and integrity of the entire process is evident. this ranges from the initial steps of user registration and authentication to the final stages of voting and result validation. Unlike conventional voting systems, which are plagued by issues such as fraud, tampering, and a lack of transparency in the result tallying and viewing processes, not to mention the delays, blockchain-enabled e-voting mitigates these challenges within government frameworks. It ensures a secure, tamper-proof, and transparent procedure, where each vote is recorded as an immutable transaction, thereby enhancing the process’s reliability. this paper explores the integration of voice recognition and fingerprinting using blockchain technology for enhancing the security of e-voting systems, comparing alternative authentication methods, and emphasizing the need for a multimodal approach to achieve better security and reliability of the voting systems.

关键词： Multi-factor authentication Government Speech recognition Fingerprint recognition Blockchains Registers Fraud Security Reliability Electronic voting

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