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Knowledge Graph Model for computing Continuum Over Smart grid 15

Knowledge Graph Model for Computing Continuum Over Smart Gri...

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15th international conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Martin, Ioana Ramona Cioara, Tudor Arcas, Gabriel Ioan Anghel, Ionut Bertoncini, Massimo Bosch Engineering Center Cluj-Napoca Romania Technical University of Cluj-Napoca Computer Science Department Cluj-Napoca Romania Engineering Ingegneria Informatica Rome Italy

ISBN: (纸本)9798350368833

The evolution of the smart grid has been driven by the emergence of Internet of Things devices, coupled with advancements in powerful Information and Communications Technology and the integration of distributed energy sources at the edge. However, as the amount of collected data grows, there's a strong need to shift the computational load of energy management services as close as possible to the data generation source to be able to meet the time and latency constraints. To support the offloading and orchestration of computation workload in a smart grid, we propose a knowledge graph model designed to semantically represent relevant information and knowledge about the types of resources available from edge devices to cloud servers that can be further utilized for processing tasks. each model layer comprises specialized nodes interlinked through a hierarchical structure and provides context-rich information on the components of the electrical grid infrastructure, such as substations, renewable energy sources, and consumers at the intersection of the data with energy networks. For evaluation, we have defined rules covering a broad spectrum of energy applications, showing that the model serves as a foundation for enhancing the management of smart grid systems by also considering edge computation requirements. © 2024 ieee.

关键词： Knowledge graph

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MISA: UNVeILING THe VULNeRABILITIeS IN SPLIT FeDeRATeD LeARNING 49

MISA: UNVEILING THE VULNERABILITIES IN SPLIT FEDERATED LEARN...

引用

49th ieee international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Wan, Wei Ning, Yuxuan Hu, Shengshan Xue, Lulu Li, Minghui Zhang, Leo Yu Jin, Hai Huazhong Univ Sci & Technol Sch Cyber Sci & Engn Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Software Engn Wuhan Peoples R China Griffith Univ Sch Informat & Commun Technol Nathan Australia Natl Engn Res Ctr Big Data Technol & Syst Beijing Peoples R China Serv Comp Technol & Syst Lab Wuhan Peoples R China Hubei Key Lab Distributed Syst Secur Wuhan Peoples R China Hubei Engn Res Ctr Big Data Secur Wuhan Peoples R China Cluster & Grid Comp Lab Wuhan Peoples R China

ISBN: (纸本)9798350344868;9798350344851

Federated learning (FL) and split learning (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users' devices. The former excels in parallel execution capabilities, while the latter enjoys low dependence on edge computing resources and strong privacy protection. Split federated learning (SFL) combines the strengths of both FL and SL, making it one of the most popular distributed architectures. Furthermore, a recent study has claimed that SFL exhibits robustness against poisoning attacks, with a fivefold improvement compared to FL in terms of robustness. In this paper, we present a novel poisoning attack known as MISA. It poisons both the top and bottom models, causing a misalignment in the global model, ultimately leading to a drastic accuracy collapse. This attack unveils the vulnerabilities in SFL, challenging the conventional belief that SFL is robust against poisoning attacks. extensive experiments demonstrate that our proposed MISA poses a significant threat to the availability of SFL, underscoring the imperative for academia and industry to accord this matter due attention.

关键词： Split Federated Learning Poisoning Attack Robustness

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enhancing Blockchain-Based Access Control in Cloud computing with Machine Learning Techniques 2

Enhancing Blockchain-Based Access Control in Cloud Computing...

引用

2nd ieee international conference on emerging Research in Computational science, ICeRCS 2024

作者： Suji Prasad, S.J. Ramprasad, S.R. Sivaraman, P. Reddy, Karumuru Venkat Battula, Bhanu Prakash Manikandan, R. Kongu Engineering College Dept. E&I Engineering TN Erode India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology School of Computing Dept. of CSE India Bannari Amman Institute of Technology Dept. of EEE TN Erode India St. Martin's Engineering College Dept. of IT Telangana Secunderabad India KKR & KSR Institute of Technology and Sciences Dept. of CSD AP Guntur India Panimalar Engineering College Dept. of ECE TN Chennai India

ISBN: (纸本)9798331534950

As cloud computing continues to expand, the importance of robust access control mechanisms to ensure security and privacy is paramount. Traditional access control systems often struggle with scalability, adaptability, and security vulnerabilities. This paper proposes a novel integration of blockchain technology with machine learning techniques to address these challenges. By harnessing the decentralized and immutable nature of blockchain and the predictive power of machine learning, our framework enhances the security and efficiency of access control systems in cloud environments. We developed a model that uses neural networks to automate and optimize access decisions and deployed it on a simulated cloud platform. Our results demonstrate significant improvements in threat detection and system adaptability compared to conventional methods. This research not only strengthens access control in cloud computing but also sets a foundational approach for future security enhancements in the field. © 2024 ieee.

关键词： Cloud platforms

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ON SeCURITY SUPPORTING IN eDGe computing-BASeD SMART grid 6

ON SECURITY SUPPORTING IN EDGE COMPUTING-BASED SMART GRID

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6th international Scientific and Technical conference Relay Protection and Automation, RPA 2023

作者： Shakhov, Vladimir Koo, Insoo Department of Electrical and Computer Engineering University of Ulsan Ulsan44610 Korea Republic of

ISBN: (纸本)9798350382334

In smart grid systems, there are intrusions that are difficult to detect using traditional surveillance based approaches. Despite the degradation of the quality of service, the statistical characteristics of the system may not differ from the normal situation. However, such intrusions can be identified by analyzing the nature of the change in quality of experience. Random fluctuations can lead to false alarms, the number of those cases is desirable to minimize. This paper discusses intelligent methods for smart grid security supporting. The proposed MeC-enabled approach does not require heavy calculations and can be adapted to various practical situations. The results of an experimental study are also presented. © 2023 ieee.

关键词： Smart power grids

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Strategies and Impact Analysis of Coordinated Cyber-Physical Attack on SG Considering False Data Injection 7

Strategies and Impact Analysis of Coordinated Cyber-Physical...

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7th ieee international conference on energy Internet, ICeI 2023

作者： Chu, Tianfeng Wang, Tong Shi, Zhuofan Hou, Min Gong, Xiangdong College of Information Science and Engineering Northeastern University Shenyang110819 China Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. Shenyang110006 China

ISBN: (纸本)9798350386684

With the development of information and communication technology and the continuous improvement of power network automation, the traditional power grid has developed into a smart grid(SG) that integrates the communication network, computing system and the physical environment of the power system. The risk of SG attacks has also growd from simple physical attacks to cyber-physical coordination, which is called Coordinated Cyber-Physical Attacks (CCPAs). CCPAs will seriously endanger the safe and stable operation of SG. Therefore, it is of great significance to establish a Coordinated Cyber-Physical Attack model and analyze the impact of coordinated attacks on the SG. The main research contents of this thesis are as below: aiming at the load loss caused by CCPAs, a Coordinated Cyber-Physical Attack effect model for transmission lines and generators is established from the perspective of attackers and defenders on the basis of the bi-rank optimization theory. Using Karush-Kuhn-Tucker(KKT) conditions and the Fortuny-Amat-McCarl (FAM) method, the bi-rank optimization model is converted into a single-rank mixed integer linear programming model for solution. Finally, the ieee-14 node test system is used to simulate the simulation,which results illusrate that the CCPAs can effectively cause load loss on the power system and affect the operating state of the power system. © 2023 ieee.

关键词： Integer programming

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Blockchain-based Zero Trust on the edge

Blockchain-based Zero Trust on the Edge

引用

international conference on Computational science and Computational Intelligence (CSCI)

作者： Bicer, Cem Murturi, Ilir Donta, Praveen Kumar Dustdar, Schahram TU Wien Distributed Syst Grp A-1040 Vienna Austria

ISBN: (纸本)9798350361513;9798350372304

Internet of Things (IoT) devices pose significant security challenges due to their heterogeneity (i.e., hardware and software) and vulnerability to extensive attack surfaces. Today's conventional perimeter-based systems use credential-based authentication (e.g., username/password, certificates, etc.) to decide whether an actor can access a network. However, the verification process occurs only at the system's perimeter because most loT devices lack robust security measures due to their limited hardware and software capabilities, making them highly vulnerable. Therefore, this paper proposes a novel approach based on Zero Trust Architecture (ZTA) extended with blockchain to further enhance security. The blockchain component serves as an immutable database for storing users' requests and is used to verify trustworthiness by analyzing and identifying potentially malicious user activities. We discuss the framework, processes of the approach, and the experiments carried out on a testbed to validate its feasibility and applicability in the smart city context. Lastly, the evaluation focuses on non-functional properties such as performance, scalability, and complexity.

关键词： Zero Trust Blockchain edge computing edge Cloud computing Security

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Task Allocation Optimization Strategy in UAV-enabled Mobile edge computing System

Task Allocation Optimization Strategy in UAV-enabled Mobile ...

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2023 ieee international conference on Metaverse computing, Networking and Applications, MetaCom 2023

作者： Yang, Sanhuan Su, Zhou Xu, Qichao Xing, Rui Fang, Dongfeng Shanghai University School of Mechatronic Engineering and Automation Shanghai China Xi'an Jiaotong University School of Cyber Science and Engineering Xi'an China California Polytechnic State University San Luis Obispo Department of Computer Science and Software Engineering United States

ISBN: (纸本)9798350333336

Unmanned Aerial Vehicles (UAVs) have been widely used as aerial computing devices in Internet of Things (IoT) to support time-sensitive and compute-intensive applications and services, e.g. automatic driving, data analysis, etc. In this paper, a UAV-enabled mobile edge computing (MeC) system is considered for computing offloading services, in which the offloaded tasks from ground devices are processed by UAVs. However, when multiple computing tasks exist, the task allocation for devices should be carried out at the lowest computing cost. To this end, we first propose a non-cooperative game model-based power allocation (NGPA) scheme, and the optimal power allocation strategy of devices is determined to minimize transmission energy consumption. Next, we model the problem of task allocation as a bilateral matching between devices and UAVs to minimize the overall computing cost. Then, a bilateral matching mechanism based on improved Hungarian algorithm is provided to obtain the optimal solution. Finally, the simulation results show that the proposed scheme outperforms the benchmark schemes on computing cost. © 2023 ieee.

关键词： Mobile edge computing

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Time-series Forecasting Coding: A New Processing Method Developed from Predictive Coding for Recurrent Neural Networks

Time-series Forecasting Coding: A New Processing Method Deve...

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international Joint conference on Neural Networks (IJCNN)

作者： Wakui, Yuto Kato, Junya Natsuaki, Ryo Hirose, Akira Univ Tokyo Dept Elect Engn & Informat Syst Bunkyo Japan

ISBN: (纸本)9798350359329;9798350359312

Recently, recurrent neural networks (RNNs) and the free energy principle (FeP) have been attracting much attention. FeP includes the so-called predictive coding (PC), in which the RNN input signals are coded as the difference between the RNN prediction output signals and original input signals. This paper proposes a new method for processing time-series data in RNNs, namely, time-series forecasting coding (TFC), developed by being based on the idea of PC. We consider multi-step ahead forecasting task with the following two schemes in our proposed TFC, i.e., smallest-delay feedback TFC and synchronous (temporally matching) feedback TFC. The latter is a natural extension of conventional PC. experimental results show that the smallest-delay TFC presents the highest performance, while synchronous TFC shows comparable or lower performance, and then the conventional method indicates the lowest. This result suggests that the concept of PC is important even in timeseries data processing, and that small delay is more important than synchronicity. This may have significant implications to the conceptual fundamentals of the PC and thus of the FeP.

关键词： Reservoir computing free-energy principle predictive coding

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Role of Quantum Computation (QC) in Addressing Computational Challenges of electrical Systems: A Review

Role of Quantum Computation (QC) in Addressing Computational...

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2023 international conference on Power energy, environment and Intelligent Control, PeeIC 2023

作者： Mishra, Rahul Centre for Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350357769

Quantum mechanics (QM) forms the basis for quantum computation (QC), a paradigm that provides distinctive problem-solving abilities. Although quantum computing (QC) has demonstrated potential in theoretical physics and computer science, its practical applications, particularly in power systems, have not been thoroughly studied. The objective of this work is to highlight the use of quantum computing (QC) as a solution for addressing the rising computational difficulties in power systems. The text provides an introduction to the historical history and essential concepts of QC, and then explores its modern applications in solving intricate power system problems. The aforementioned subjects comprise the study of alternating current (AC) and direct current (DC)' power flow, contingency analysis, state estimation, modeling of electromagnetic transients, fault diagnostics, unit commitment, and challenges related to facility location-allocation.' Despite the existing limits of noisy intermediate-scale quantum (NISQ) devices, the potential of quantum computing to address significant power system concerns on a wide scale holds promise, mostly driven by anticipated advancements in technology and increased research endeavors. © 2023 ieee.

关键词： Big data grid analytics grid optimization Quantum computation

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empowering Smart Homes with Fog computing for IoT Connectivity

Empowering Smart Homes with Fog Computing for IoT Connectivi...

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2024 international conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Mahdi, Ali Jafer Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq AI-Zahraa University for Women Department of Scientific Affairs Bangi43600 Malaysia College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Innovative grid technology leverages Information and Communication Technology (ICT) to enhance energy efficiency and mitigate losses. This paper introduces a 'novel three-tier hierarchical framework for smart homes within the Internet of Things (IoT)' ecosystem, addressing the current shortage of intelligent solutions that underutilize IoT advantages. Our framework's primary objective is to elevate smart homes to the microgrid level, enabling the seamless integration from the microgrid's renewable distributed energy sources and attaining maximum energy efficiency. In addition to traditional data processing, we propose the application of fog computing in smart homes. Through a rigorous simulation using real smart meter datasets, our study demonstrates that fog computing, mainly when using predictive filtering, may drastically cut down on the amount of data being sent and the load on the home's network. This innovation holds immense potential for revolutionizing energy management and resource allocation in the context of smart homes, thus contributing to a sustainable and efficient future. This research represents a critical step towards harnessing the power of IoT and fog computing in smart grids and homes, offering a promising path towards more intelligent, eco-friendly, and energy-efficient living spaces. © 2024 ieee.

关键词： Smart homes

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