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Provably Secure Efficient key-Exchange Protocol for Intelligent Supply Line Surveillance in Smart Grids

IEEE Internet of Things Journal 2025年

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Alenazi, Mohammed J.F. Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu12599 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security China Shandong Fundamental Research Center for Computer Science Jinan 250353 China

Intelligent supply line surveillance is critical for modern smart grids. Smart sensors and gateway nodes are strategically deployed along supply lines to achieve intelligent surveillance. They collect data continuously and transmit it to the control centre in real-time. It enables real-time monitoring, fault detection, and efficient energy management across distribution networks. This advanced surveillance system ensures continuous monitoring of supply lines, detecting anomalies, and optimizing operations to maintain the stability and reliability of the smart grid. However, the reliance of all participating nodes on public communication channels to transmit supply line surveillance data exposes these systems to critical cyber attacks. These cyber attacks include impersonation, physical tampering, ephemeral secret leakage, and desynchronization attacks. To address these issues, existing key-exchange protocols often fail to ensure robust security while imposing high computation and communication overheads, limiting their practicality for resource-constrained environments. Therefore, we propose a secure and efficient key exchange and tamper-resistant authentication protocol using Elliptic Curve Cryptography (ECC) and Physical Unclonable Functions (PUFs). The PUF mechanism provides robust resistance against physical tampering and cloning attacks, ensuring enhanced physical security for supply line devices. We validate the security robustness of the devised protocol using the Random or Real (ROR) model. Furthermore, informal security analysis demonstrates the protocol's robustness in rigorously resisting various attacks, including physical tampering, impersonation, ephemeral secret leakage and desynchronization. Moreover, we determine the performance evaluation that reveals the protocol's superior efficiency compared to competing protocols, achieving significant reductions of 28.64% in computation overhead and 9.96% in communication overhead. © 2014 IEEE.

关键词： Authentication Protocol

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Saturated Adaptive Output-Constrained Control of Cooperative Spacecraft Rendezvous and Docking

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1462-1470页

作者： Liang Sun IEEE the Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation and Electrical Engineering and also with the Institute of Artificial Intelligence University of Science and Technology Beijing

This paper investigates the robust relative pose control for spacecraft rendezvous and docking with constrained relative pose and saturated control inputs.A barrier Lyapunov function is used to ensure the constraints of states,so that the computational singularity of the inverse matrix in control command can be avoided,while a linear auxiliary system is introduced to handle with the adverse effect of actuator *** tuning rules for designing parameters in control command and auxiliary system are derived based on the stability analysis of the closed-loop *** is proved that all closed-loop signals always keep bounded,the prescribed constraints of relative pose tracking errors are never violated,and the pose tracking errors ultimately converge to small neighborhoods of *** experiments validate the performance of the proposed robust saturated control strategy.

关键词： Output-constrained control pose tracking control rendezvous and docking saturated control singularity-free control spacecraft control

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FlexTable: Using a Dynamic Relation Model to Store RDF data

FlexTable: Using a Dynamic Relation Model to Store RDF Data

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15th International Conference on database Systems for Advanced Applications

作者： Wang, Yan Du, Xiaoyong Lu, Jiaheng Wang, Xiaofang Key Labs of Data Engineering and Knowledge Engineering Ministry of Education China Information School Renmin University of China China

ISBN: (纸本)9783642120251

Efficient management of RDF data is an important factor in realizing the Semantic Web vision. The existing approaches store RDF data based on triples instead of a relation model. In this paper, we propose a system called FlexTable, where all triples of an instance are coalesced into one tuple and all tuples are stored in relation schemas. The main technical challenge is how to partition all the triples into several tables, i.e. it is needed to design an effective and dynamic schema structure to store RDF triples. To deal with this challenge, we firstly propose a schema evolution method called LBA, which is based on a lattice structure to automatically evolve schemas while new triples are inserted. Secondly, we propose a novel page layout with an interpreted storage format to reduce the physical adjustment cost during schema evolution. Finally we perform comprehensive experiments on two practical RDF data sets to demonstrate that FlexTable is superior to the state-of-the-art approaches.

关键词： FlexTable RDF data dynamic relational model Lattice

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A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy

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Journal of Bionic engineering 2008年第3期5卷 215-223页

作者： Shu-xue Zou Yan-xin Huang Yan Wang Chun-guang Zhou Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 P. R. China

Detecting the boundaries of protein domains is an important and challenging task in both experimental and computational structural biology. In this paper, a promising method for detecting the domain structure of a protein from sequence information alone is presented. The method is based on analyzing multiple sequence alignments derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence. Then they are combined into a single predictor using support vector machine. What is more important, the domain detection is first taken as an imbal- anced data learning problem. A novel undersampling method is proposed on distance-based maximal entropy in the feature space of Support Vector Machine （SVM）. The overall precision is about 80%. Simulation results demonstrate that the method can help not only in predicting the complete 3D structure of a protein but also in the machine learning system on general im- balanced datasets.

关键词： protein domain boundary SVM imbalanced data learning distance-based maximal entropy

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An Efficient Method for Calculating Qualitative Spatial Relations

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电子学报(英文版) 2009年第1期18卷 42-46页

作者： WANG Shengsheng LIU Dayou College of Computer Science and Technology Key Laboratory of Symbolic Computing and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Qualitative spatial relations are widely used in geospatial ontologies, geospatial (semantic) web services, spatial description logics etc. Methodology to obtain qualitative spatial relations (especially complex spatial relations) from Geographical information system (GIS) has not been studied in previous literatures. An efficient method for calculating complex qualitative spatial relations is discussed here. First, the multi-granularities approximate representation of spatial objects is proposed, it is designed for GIS object types (such as polygon), and requires less process time. Then some algorithms for calculating complex spatial relations based on the multi-granularities approximate representation are given. Finally, this method is implemented and used to obtain topology and direction relations from world map. The analysis and test results show that this method supports complex and integrated spatial relations and requires less process time than traditional method. This method is suitable for obtaining spatial relations for geospatial ontologies and other applications.

关键词：空间关系计算地理信息系统地理本体信息系统设计网络服务描述逻辑空间对象

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An Algorithm for the Discretization of an Ideal Projector

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Journal of Systems Science & Complexity 2016年第5期29卷 1400-1410页

作者： JIANG Xue ZHANG Shugong LI Zhe Institute of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering (Ministry of Education) Jilin University Department of Applied Mathematics School of Science Changchun University of Science and Technology

Ideal interpolation is a generalization of the univariate Hermite interpolation. It is well known that every univariate Hermite interpolant is a pointwise limit of some Lagrange ***, a counterexample provided by Shekhtman Boris shows that, for more than two variables,there exist ideal interpolants that are not the limit of any Lagrange interpolants. So it is natural to consider: Given an ideal interpolant, how to find a sequence of Lagrange interpolants(if any) that converge to it. The authors call this problem the discretization for ideal interpolation. This paper presents an algorithm to solve the discretization problem. If the algorithm returns "True", the authors get a set of pairwise distinct points such that the corresponding Lagrange interpolants converge to the given ideal interpolant.

关键词： Discretization ideal interpolation Lagrange interpolation.

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Aleatoric-Uncertainty-Aware Maximum Intensity Projection-Based GAN for 7T-Like Generation from 3T TOF-MRA

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Tang, Wei Dai, Yuxiang Zhang, Boyu Shi, Zhang Chu, Ying-Hua Zhuang, Peixian Shen, Dinggang Wang, Chengyan Wang, He Fudan University Institute of Science and Technology for Brain-Inspired Intelligence Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Shanghai 200433 China Fudan University Department of Radiology Zhongshan Hospital Shanghai200031 China Siemens Healthineers Ltd. MR Research Collaboration Team Shanghai310000 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education the School of Automation and Electrical Engineering Beijing100083 China ShanghaiTech University School of Biomedical Engineering State Key Laboratory of Advanced Medical Materials and Devices Shanghai201210 China Shanghai United Imaging Intelligence Co. Ltd. Shanghai200232 China Shanghai Clinical Research and Trial Center Shanghai201210 China Fudan University Human Phenome Institute Shanghai200437 China Shanghai Fourth People's Hospital Affiliated to Tongji University School of Medicine Department of Radiology Shanghai200434 China

Time-of-flight magnetic resonance angiography (TOF-MRA) is a prevalent vascular imaging technique for assessing cerebrovascular diseases. Compared to routine 3T TOF-MRA, 7T TOF-MRA provides vascular structures with a higher signal-to-noise ratio (SNR) and better vessel contrast, revealing greater vascular details. However, the inaccessibility of 7T scanners and specific physiological and technical concerns limit its clinical application. Therefore, we aimed to generate high-quality 7T-like TOF-MRA from 3T TOF-MRA. Considering the spatial sparsity of vessel signals, the visibility discrepancy of distal and small vessels between 3T and 7T images, and the subtle spatial misalignment between paired data, we proposed a novel aleatoric-uncertainty-aware maximum intensity projection-based generative adversarial network (AU-MIPGAN). In our method, we employed a knowledge distillation (KD) framework to incorporate multi-directional MIP information into the 3T-to-7T learning process to strengthen the learning of vessels and provide three-dimensional (3D) vascular morphological knowledge for the student model, facilitating accurate generation of vascular structures. Furthermore, we exploited AU modeling to compensate for the spatial misalignment between paired 3T and 7T images during the training procedure, which helped the model concentrate more on learning the intrinsic gap between 3T and 7T images. Qualitative and quantitative results demonstrated that the proposed AU-MIPGAN can achieve promising performance for 7T-like TOF-MRA generation. © 2013 IEEE.

关键词： Blood vessels

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Diversifying Question Generation over knowledge Base via External Natural Questions 30

Diversifying Question Generation over Knowledge Base via Ext...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Guo, Shasha Zhang, Jing Ke, Xirui Li, Cuiping Chen, Hong School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education China

ISBN: (纸本)9782493814104

Previous methods on knowledge base question generation (KBQG) primarily focus on refining the quality of a single generated question. However, considering the remarkable paraphrasing ability of humans, we believe that diverse texts can express identical semantics through varied expressions. The above insights make diversifying question generation an intriguing task, where the first challenge is evaluation metrics for diversity. Current metrics inadequately assess the aforementioned diversity. They calculate the ratio of unique n-grams in the generated question, which tends to measure duplication rather than true diversity. Accordingly, we devise a new diversity evaluation metric, which measures the diversity among top-k generated questions for each instance while ensuring their relevance to the ground truth. Clearly, the second challenge is how to enhance diversifying question generation. To address this challenge, we introduce a dual model framework interwoven by two selection strategies to generate diverse questions leveraging external natural questions. The main idea of our dual framework is to extract more diverse expressions and integrate them into the generation model to enhance diversifying question generation. Extensive experiments on widely used benchmarks for KBQG show that our approach can outperform pre-trained language model baselines and text-davinci-003 in diversity while achieving comparable performance with ChatGPT. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Semantics

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DSM: Question Generation over knowledge Base via Modeling Diverse Subgraphs with Meta-learner

DSM: Question Generation over Knowledge Base via Modeling Di...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Guo, Shasha Zhang, Jing Wang, Yanling Zhang, Qianyi Li, Cuiping Chen, Hong School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education China

Existing methods on knowledge base question generation (KBQG) learn a one-size-fits-all model by training together all subgraphs without distinguishing the diverse semantics of subgraphs. In this work, we show that making use of the past experience on semantically similar subgraphs can reduce the learning difficulty and promote the performance of KBQG models. To achieve this, we propose a novel approach to model diverse subgraphs with meta-learner (DSM). Specifically, we devise a graph contrastive learning-based retriever to identify semantically similar subgraphs, so that we can construct the semantics-aware learning tasks for the meta-learner to learn semantics-specific and semantics-agnostic knowledge on and across these tasks. Extensive experiments on two widely-adopted benchmarks for KBQG show that DSM derives new state-of-the-art performance and benefits the question answering tasks as a means of data augmentation. Codes and datasets are available online. © 2022 Association for Computational Linguistics.

关键词： Semantics

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WATuning:A Workload-Aware Tuning System with Attention-Based Deep Reinforcement Learning

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Journal of Computer Science & Technology 2021年第4期36卷 741-761页

作者： Jia-Ke Ge Yan-Feng Chai Yun-Peng Chai Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of China Beijing 100872China School of Information Renmin University of ChinaBeijing 100872China College of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030027China

Configuration tuning is essential to optimize the performance of systems(e.g.,databases,key-value stores).High performance usually indicates high throughput and low *** present,most of the tuning tasks of systems are performed artificially(e.g.,by database administrators),but it is hard for them to achieve high performance through tuning in various types of systems and in various *** recent years,there have been some studies on tuning traditional database systems,but all these methods have some *** this article,we put forward a tuning system based on attention-based deep reinforcement learning named WATuning,which can adapt to the changes of workload characteristics and optimize the system performance efficiently and ***,we design the core algorithm named ATT-Tune for WATuning to achieve the tuning task of *** algorithm uses workload characteristics to generate a weight matrix and acts on the internal metrics of systems,and then ATT-Tune uses the internal metrics with weight values assigned to select the appropriate ***,WATuning can generate multiple instance models according to the change of the workload so that it can complete targeted recommendation services for different types of ***,WATuning can also dynamically fine-tune itself according to the constantly changing workload in practical applications so that it can better fit to the actual environment to make *** experimental results show that the throughput and the latency of WATuning are improved by 52.6%and decreased by 31%,respectively,compared with the throughput and the latency of CDBTune which is an existing optimal tuning method.

关键词： attention mechanism auto-tuning system reinforcement learning(RL) workload-aware

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