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A blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social internet of vehicles

Digital Communications and Networks 2022年第6期8卷 976-983页

作者： Ziming Liu Yang Xu Cheng Zhang Haroon Elahi Xiaokang Zhou College of Information Science and Engineering Northeastern UniversityShenyang110819China College of Computer Science and Electronic Engineering Hunan UniversityChangsha410082China Key Laboratory of Blockchain and Cyberspace Governance of Zhejiang Province Zhejiang UniversityHangzhou310058China Department of Computing Science Umea UniversityUmea90187Sweden Faculty of Data Science Shiga UniversityHikone522-8522Japan RIKEN Center for Advanced Intelligence Project RIKENTokyo103-0027Japan

Social Internet of Vehicles(SIoV)falls under the umbrella of social Internet of Things(IoT),where vehicles are socially connected to other vehicles and roadside units that can reliably share information and services with other social entities by leveraging the capabilities of 5G technology,which brings new opportunities and challenges,e.g.,collaborative power trading can address the mileage anxiety of electric ***,it relies on a trusted central party for scheduling,which introduces performance bottlenecks and cannot be set up in a distributed network,in addition,the lack of transparency in state-of-the-art Vehicle-to-Vehicle(V2V)power trading schemes can introduce further trust *** this paper,we propose a blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social vehicular networks that uses a distributed market mechanism to introduce trusted power trading and avoids the dependence on a centralized dispatch *** on the game theory,we design the pricing and trading matching mechanism for V2V power trading to obtain maximum social *** use blockchain to record power trading data for trusted pricing and use smart contracts for transaction *** simulation results verify the effectiveness of the proposed scheme in improving social welfare and reducing the load on the grid.

关键词： Social internet of vehicles Bl ockchain Collaborative power trading Vehicle-to-vehicle charging 5G

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Vehicle Collision Prediction from visual Sizes of Objects via Car Dash Camera

Vehicle Collision Prediction from Visual Sizes of Objects vi...

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International Conference on Information Technology (INCIT)

作者： Siwakorn Sairung Pongporn Yasotarin Sasipa Panthuwadeethorn Suphakant Phimoltares Department of Mathematics and Computer Science Advanced Virtual and Intelligent Computing (AVIC) Center Faculty of Science Chulalongkorn University Bangkok Thailand

The purpose of this research is to develop a method for vehicle collision prediction from visual sizes of objects. There are three main stages in the proposed method. The first stage is object detection and classification using You Only Look Once version 7 (YOLOv7) and object tracking using Simple Online and Realtime Tracking with a deep association metric (DeepSORT). Then, linear regression is applied with the data gathered from the first stage to predict the shape of the bounding box and the coordinates of the centroid of the bounding box of the object at various time intervals. The last stage is vehicle collision prediction along with the time interval in which the collision may occur. If the predicted bounding box of the object overlaps with the defined area in the video, the proposed method predicts that the collision will occur. From the experimental results, the proposed method can trigger collision warning and help reduce the risk of road accidents with car dash camera.

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The Rise of Ransomware: A Review of Attacks, Detection Techniques, and Future Challenges

The Rise of Ransomware: A Review of Attacks, Detection Techn...

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2022 International Conference on Business Analytics for Technology and Security, ICBATS 2022

作者： Kamil, Samar Siti Norul, Huda Sheikh Abdullah Firdaus, Ahmad Usman, Opeyemi Lateef Al-Mansour University College Department of Computer Science and Information Systems Baghdad Iraq Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia University Malaysia Pahang Faculty of Computing College of Computing and Applied Sciences Pahang Darul Pekan Malaysia Tai Solarin University of Education Department of Computer Science Ogun State Nigeria

ISBN: (纸本)9781665409209

Cybersecurity is important in the field of information technology. One most recent pressing issue is information security. When we think of cybersecurity, the first thing that comes to mind is cyber-attacks, which are on the rise, such as Ransomware. Various governments and businesses take a variety of measures to combat cybercrime. People are still concerned about ransomware, despite numerous cybersecurity precautions. In ransomware, the attacker encrypts the victim's files/data and demands payment to unlock the data. Cybersecurity is a collection of tools, regulations, security guards, security ideas, guidelines, risk management, activities, training, insurance, best practices, and technology used to secure the cyber environment, organization, and user assets. This paper analyses ransomware attacks, techniques for dealing with these attacks, and future challenges. © 2022 IEEE.

关键词： Cybersecurity

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A Practical Multi-Protocol Collaborative Quantum Key Distribution Networking Scheme for Consumer Electronics Devices

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IEEE Transactions on Consumer Electronics 2024年

作者： Yao, Jia-Meng Li, Qiong Mao, Hao-Kun El-Latif, Ahmed A. Abd Harbin Institute of Technology Department of the School of Computer Science and Technology Harbin150001 China Prince Sultan University Center of Excellence in Quantum and Intelligent Computing Riyadh11586 Saudi Arabia Menoufia University Faculty of Science Department of Mathematics and Computer Science Shibin El Kom6132501 Egypt

The development of emerging consumer technologies such as the Internet of Things (IoT), artificial intelligence (AI), and cloud computing brings convenience but also raises critical concerns about securing communication data. Quantum computing threatens the security of classical public key cryptography, making post-quantum data protection essential. Quantum Key Distribution (QKD) networks offer a solution, but the dependence on trusted relays raises security concerns. The existing QKD networks mainly consist of two types: measurement-device-dependent protocol based QKD networks which have a high dependence on trusted relays, and measurement-device-independent protocol based QKD networks which have a weak dependence on trusted relays but communication capability is limited. This paper proposes a Multi-Protocol Collaborative (MPC) networking cell combining both types of QKD protocol, which can reduce the dependence on trusted relays while maintaining a high communication capacity, and consequently has an enhanced practicality. An optimal topology method is also designed to further enhance the performance of the networks. Results show that communication capacity is improved 37 times compared to measurement-device-independent protocol based QKD networks. In addition, 23% reduction in the dependence on trusted relays compared to measurement-device-dependent protocol based QKD networks. By overcoming the trade-off between trust and capacity, this work significantly advances the practicalization of QKD networks in consumer electronics. © 1975-2011 IEEE.

关键词： Quantum computers

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Neural Network-Based Safety Optimization Control for Constrained Discrete-Time Systems 49

Neural Network-Based Safety Optimization Control for Constra...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wang, Xueli Zhao, Shangwei Yang, Ming Wu, Xiaoming Wang, Xin Xu, Shuo Hu, Xu Qilu University of Technology Key Laboratory of Computing Power Network and Information Security Shandong Computer Science Center Jinan China Shanghai Jiao Tong University Department of Automation Shanghai China Public Security Bureau of Jinan Jinan China

ISBN: (纸本)9798350331820

This paper proposes a constraint-aware safety control approach via adaptive dynamic programming (ADP) to address the control optimization issues for discrete-time systems subjected to state constraints. First, the constrained control framework is established via the primal-dual approach with the modified Lagrangian based on the relaxed barrier function. Herein, the Lagrangian multiplier is designed to achieve the trade-off between optimization performance and state constraints. In addition, the sub optimality of the dual method is built by proving that the dual gap can be arbitrarily small. And the value iteration algorithm is utilized to implement the constraint-aware ADP controller. Furthermore, the weight estimation error is proved to be bounded when the learning rate satisfies a given sufficient condition. Finally, numerical simulation proves the effectiveness and superiority of the proposed method. © 2023 IEEE.

关键词： Iterative methods

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Towards Semantic Web of Things: Reference Architecture and Gap Analysis

Towards Semantic Web of Things: Reference Architecture and G...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social computing (CPSCom) Green computing and Communications (GreenCom)

作者： Xiang Su Ekaterina Gilman Xiaoli Liu Department of Computer Science Norwegian University of Science and Technology Gjøvik Norway Center for Ubiquitous Computing University of Oulu Oulu Finland Department of Computer Science University of Helsinki Helsinki Finland

Internet of Things (IoT) connects objects and allows data exchange between smart things and the Internet. Web of Things (WoT) further integrates smart things into the Web architecture by leveraging existing standardized Web technologies. In this paper, we envision Semantic Web of Things (SWoT), aiming to exchange semantically rich and machine understandable information with smart things. This article discusses the landscape of IoT and WoT through the past and its future prospects, presents a SWoT reference architecture, and conducts a gap analysis. Aiming to highlight the deficiencies of existing solutions, we carry out a gap analysis with respect to (i) extension of WoT, (ii) semantic knowledge base, (iii) semantic reasoning, (iv) semantic interoperability, and (v) semantic service composition. Based on the results of our analysis, we conclude this article with a list of recommendations in order to fill the gaps. The main contributions pertain to a SWoT reference architecture with key SWoT building blocks and an analysis of technologies to support SWoT.

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A hybrid blockchain and AI-based approach for attack protection to secure internet of medical things networks

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Alexandria Engineering Journal 2025年 128卷 223-230页

作者： Hadeel Alsolai Fahd N. Al-Wesabi Ali M. Al-Sharafi Asma Alshuhail Abdulbasit A. Darem Bandar M. Alghamdi Fouad Shoie Alallah Abdulrahman Alzahrani Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia Department of Computer Science Applied College at Mahayil King Khalid University Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computing and Information Technology University of Bisha Bisha 67714 Saudi Arabia Department of Information Systems College of Computer Sciences & Information Technology King Faisal University Saudi Arabia Center for Scientific Research and Entrepreneurship Northern Border University Arar 73213 Saudi Arabia Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah 21589 Saudi Arabia Department of Computer Science and Engineering College of Computer Science and Engineering University of Hafr Al Batin Saudi Arabia

The Internet of Medical Things (IoMT) has revolutionized healthcare by enabling real-time monitoring, remote diagnosis, and seamless data exchange among medical devices and providers. However, the interconnected and distributed nature of IoMT systems exposes them to significant cybersecurity threats, including data breaches and unauthorized access. This study aims to develop a secure and scalable framework to safeguard IoMT environments using blockchain technology, federated learning, and dynamic consensus algorithms. The proposed approach integrates artificial intelligence to detect threats and employs federated learning to maintain patient privacy while training models collaboratively. Experimental evaluation of the framework shows improved data security, reduced response times, and enhanced system trustworthiness. The results suggest that the integration of blockchain and AI-driven mechanisms offers a robust solution to IoMT cybersecurity challenges, paving the way for more reliable and efficient healthcare systems.

关键词： Internet of medical things (IoMT) Blockchain security Federated learning AI-driven anomaly detection Cyber threat mitigation

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Frequency-noise-insensitive universal control of Kerr-cat qubits

arXiv

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arXiv 2025年

作者： Seifert, Lennart Maximilian Hann, Connor T. Noh, Kyungjoo Department of Computer Science University of Chicago ChicagoIL60637 United States AWS Center for Quantum Computing PasadenaCA91125 United States

We theoretically study the influence of frequency uncertainties on the operation of a Kerr-cat qubit. As the mean photon number increases, Kerr-cat qubits provide an increasing level of protection against phase errors induced by unknown frequency shifts during idling and X rotations. However, realizing rotations about the other principal axes (e.g., Y and Z axes) while preserving robustness is nontrivial. To address this challenge, we propose a universal set of gate schemes which circumvents the tradeoff between protection and controllability in Kerr-cat qubits and retains robustness to unknown frequency shifts to at least first order. Assuming an effective Kerr oscillator model, we theoretically and numerically analyze the robustness of elementary gates on Kerr-cat qubits, with special focus on gates along nontrivial rotation axes. An appealing application of this qubit design would include tunable superconducting platforms, where the induced protection against frequency noise would allow for a more flexible choice of operating point and thus the potential mitigation of the impact of spurious two-level systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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OneBit: towards extremely low-bit large language models 24

OneBit: towards extremely low-bit large language models

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Yuzhuang Xu Xu Han Zonghan Yang Shuo Wang Qingfu Zhu Zhiyuan Liu Weidong Liu Wanxiang Che Research Center for Social Computing and Information Retrieval Harbin Institute of Technology Harbin China Department of Computer Science & Technology Tsinghua University Beijing China

ISBN: (纸本)9798331314385

Model quantification uses low bit-width values to represent the weight matrices of existing models to be quantized, which is a promising approach to reduce both storage and computational overheads of deploying highly anticipated LLMs. However, current quantization methods suffer severe performance degradation when the bit-width is extremely reduced, and thus focus on utilizing 4-bit or 8-bit values to quantize models. This paper boldly quantizes the weight matrices of LLMs to 1-bit, paving the way for the extremely low bit-width deployment of LLMs. For this target, we introduce a 1-bit model compressing framework named OneBit, including a novel 1-bit parameter representation method to better quantize LLMs as well as an effective parameter initialization method based on matrix decomposition to improve the convergence speed of the quantization framework. Sufficient experimental results indicate that OneBit achieves good performance (at least 81% of the non-quantized performance on LLaMA models) with robust training processes when only using 1-bit weight matrices. Code and checkpoints are available at https://***/xuyuzhuang11/OneBit

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Neural Machine Translation for Kashmiri to English and Hindi using Pre-trained Embeddings 20

Neural Machine Translation for Kashmiri to English and Hindi...

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20th OITS International Conference on Information Technology, OCIT 2022

作者： Sheshadri, Shailashree K Gupta, Deepa Costa-Jussa, Marta R. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India Universitat Politecnica de Catalunya - Upc Talp Research Center Barcelona Spain

ISBN: (纸本)9781665493482

Neural Machine Translation (NMT) is one of the advanced approaches of Machine Translation (MT) that has recently gained popularity. A significant amount of parallel corpus is required to achieve a sound translation system, but most languages have a deficit worldwide. Many SoTA NMT systems are available for low-resource langauges that are developed using transfer learning, knowledge transfer, and zero-shot learning mechanisms. Most Indic languages fall into low-resource and zero-resource due to the non-availability of rich parallel and monolingual corpora. Though many Indian border languages have social and economic significance, they lack resources and automated machine translation systems. Kashmiri, one such Indian border language, belongs to the zero-resource category with limited corpora and no significant translation system. This paper uses pre-trained word embeddings to create the first NMT system specifically for Kashmiri-English and Kashmiri-Hindi translation. mBPE pre-trained word embeddings for Kashmiri language are used to develop the NMT system. A pre-trained word embedding model shows +2.58 BLEU improvisation in comparison to Vanilla NMT. © 2022 IEEE.

关键词： Embeddings

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