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Game Theory based Optimal Defensive Resources Allocation with Incomplete information in Cyber-physical Power Systems against False Data Injection Attacks

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Protection and Control of Modern Power Systems 2024年第2期9卷 115-127页

作者： Bingjing Yan Zhenze Jiang Pengchao Yao Qiang Yang Wei Li Albert Y.Zomaya College of Electrical Engineering Zhejiang University College of Control Science and Engineering Zhejiang University College of Electrical Engineering Zhejiang UniversityHangzhou 310027China School of information technologies at The University of Sydney School of information technologies

Modern power grid is fast emerging as a complex cyber-physical power system(CPPS)integrating physical current-carrying components and processes with cyber-embedded computing,which faces increasing cy-berspace security threats and *** this paper,the state(i.e.,voltage)offsets resulting from false data injection(FDI)attacks and the bus safety characterization are applied to quantify the attack *** state offsets are obtained by the state estimation method,and the bus safety characterization considers the power net-work topology as well as the vulnerability and connection relationship of *** the indeterminacy of attacker’s resource consumption and reward,a zero-sum game-theoretical model from the defender’s perspective with incomplete information is explored for the optimal allocation of limited defensive *** attacker aims to falsify measurements without triggering threshold alarms to break through the protection,leading to load shedding,over-voltage or *** defender attempts to ensure the estimation results to be as close to the actual states as possible,and guarantee the system’s safety and efficient defensive resource *** proposed solution is extensively evaluated through simu-lations using the IEEE 33-bus test network and real-time digital simulator(RTDS)based testbed experiments of the IEEE 14-bus *** results demonstrate the effec-tiveness of the proposed game-theoretical approach for optimal defensive resource allocation in CPPS when lim-ited resources are available when under FDI *** Terms—Optimal strategy,game theory,Nash equilibrium,CPPS,FDI attack.

关键词： Optimal strategy game theory Nash equilibrium CPPS FDI attack

Multispectral point cloud superpoint segmentation

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Science China(Technological Sciences) 2024年第4期67卷 1270-1281页

作者： WANG QingWang WANG MingYe ZHANG ZiFeng SONG Jian ZENG Kai SHEN Tao GU YanFeng Faculty of information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key Laboratory of Computer technologies Application Kunming 650500China School of Electronics and information Engineering Harbin Institute of TechnologyHarbin 150001China

The multitude of airborne point clouds limits the point cloud processing *** are grouped based on similar points,which can effectively alleviate the demand for computing resources and improve processing ***,existing superpoint segmentation methods focus only on local geometric structures,resulting in inconsistent spectral features of points within a *** feature inconsistencies degrade the performance of subsequent ***,this study proposes a novel Superpoint Segmentation method that jointly utilizes spatial Geometric and Spectral information for multispectral point cloud superpoint segmentation(GSI-SS).Specifically,a similarity metric that combines spatial geometry and spectral information is proposed to facilitate the consistency of geometric structures and object attributes within segmented *** the formation of the primary superpoints,an intersuperpoint pointexchange mechanism that maximizes feature consistency within the final superpoints is *** are conducted on two real multispectral point cloud datasets,and the proposed method achieved higher recall,precision,F score,and lower global consistency and feature classification *** experimental results demonstrate the superiority of the proposed GSI-SS over several state-of-the-art methods.

关键词： multispectral point cloud superpoint segmentation over-segmentation spatial-spectral joint metric

Effective integration of highly-efficient focusing apodized grating and quantum dots on a solid substrate for scalable quantum photonic circuits

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Science China(Physics,Mechanics & Astronomy) 2024年第9期67卷 99-107页

作者： Beimeng Yao Rongbin Su Shunfa Liu Changkun Song Ying Yu Jin Liu Xuehua Wang State Key Laboratory of Optoelectronic Materials and technologies School of PhysicsSun Yat-sen UniversityGuangzhou 510275China State Key Laboratory of Optoelectronic Materials and technologies School of Electronics and Information TechnologySun Yat-sen UniversityGuangzhou 510275China

Recent advancements in quantum photonic circuits have significantly influenced the field of quantum information *** pursuit of an integrated quantum photonic circuit that offers an active,stable platform for large-scale integration and high processing efficiency remains a key *** grating coupler,as a crucial element for an efficient transformation output interface in the integrated quantum photonic circuits,presents significant potential for practical ***,we demonstrate the integration block of a highly efficient shallow-etched focusing apodized grating coupler with indium arsenide(InAs)quantum dots(QDs)in gallium arsenide(GaAs)on a SiO2substrate for active quantum photonic *** designed grating couplers possess a high efficiency over 90% in the broadband(900-930 nm)from the circuit to free space,and a nearly-perfect match with the fiber ***,the efficiency to free space reaches 81.8%,and the match degree with the fiber mode is high up to 92.1%.The proposed integration block offers the potential for large-scale integration of active quantum photonic circuits due to its stable solid substrate and highly performant output for quantum measurements.

关键词： quantum dot grating coupler wafer bonding quantum photonic circuit

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Energy-Efficient Implementation of BCD to Excess-3 Code Converter for Nano-Communication Using QCA Technology

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China Communications 2024年第6期21卷 103-111页

作者： Nuriddin Safoev Angshuman Khan Khudoykulov Zarif Turakulovich Rajeev Arya Department of Cybersecurity&Criminology Tashkent University of Information TechnologiesTashkent 100084Uzbekistan Department of Electronics and Communication Engineering University of Engineering and ManagementJaipurRajasthan 303807India Department of Cryptology Tashkent University of Information TechnologiesTashkent 100084Uzbekistan Department of Electronics and Communication Engineering National Institute of Technology PatnaBihar 800005India

Code converters are essential in digital nano communication;therefore,a low-complexity optimal QCA layout for a BCD to Excess-3 code converter has been proposed in this paper.A QCA clockphase-based design technique was adopted to investigate integration with other complicated *** a unique XOR gate,the recommended circuit’s cell complexity has been *** findings produced using the QCADesigner-2.0.3,a reliable simulation tool,prove the effectiveness of the current structure over earlier designs by considering the number of cells deployed,the area occupied,and the latency as design *** addition,the popular tool QCAPro was used to estimate the energy dissipation of the proposed *** proposed technique reduces the occupied space by∼40%,improves cell complexity by∼20%,and reduces energy dissipation by∼1.8 times(atγ=1.5EK)compared to the current scalable *** paper also studied the suggested structure’s energy dissipation and compared it to existing works for a better performance evaluation.

关键词： BCD code converter Excess-3 nano communication QCA circuits

Path signature-based XAI-enabled network time series classification

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Science China(information Sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA Department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

Distributed IRS-Aided DF Relaying Systems:Performance Analysis and Optimization

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China Communications 2024年第6期21卷 129-145页

作者： Sun Qiang Qian Panpan Chen Xiaomin Ju Jinjuan Wang Jue Zhang Jiayi School of information Science and Technology Nantong UniversityNantong 226019China Nantong Research Institute for Advanced Communication technologies Nantong 226019China School of Electronic and information Engineering Nantong Vocational UniversityNantong 226007China School of Electronic and information Engineering Beijing Jiaotong UniversityBeijing 100044China

Intelligent reflecting surface(IRS)is a newly emerged and promising paradigm to substantially improve the performance of wireless communications by constructing favorable communication channels via properly tuning massive reflecting *** paper considers a distributed IRS aided decode-and-forward(DF)relaying system over Nakagami-m fading *** on a tight approximation for the distribution of the received signalto-noise ratio(SNR),we first derive exact closed-form expressions of the outage probability,ergodic capacity,and energy efficiency for the considered ***,we propose the optimal IRS configuration considering the energy efficiency and pilot ***,we compare the performance between the distributed IRS-aided DF relaying and multi-IRS-only systems,and verify the analytical results by using monte carlo simulations.

关键词： configuration energy efficiency ergodic capacity intelligent reflecting surface IRS outage probability

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

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Computers, Materials & Continua 2024年第8期80卷 2897-2915页

作者： Fang Hu Siyi Qiu Xiaolian Yang ChaoleiWu Miguel Baptista Nunes Hui Chen College of information Engineering Hubei University of Chinese MedicineWuhan430065China College of information Engineering Zhongnan University of Economics and LawWuhan430073China School of Advanced technologies Xi’an Jiaotong-Liverpool UniversitySuzhou215400China School of information Management Central China Normal UniversityWuhan430079China

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,*** guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed *** system is composed of three layers:Data extraction and storage,data management,and data *** on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and *** improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training ***,healthcare and medical data collaboration services in real-world scenarios have been discussed and *** further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image *** model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),***,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

关键词： Blockchain technique federated learning healthcare and medical data collaboration service privacy preservation

Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

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Computers, Materials & Continua 2024年第1期78卷 1461-1479页

作者： Sarah Mustafa Eljack Mahdi Jemmali Mohsen Denden Mutasim Al Sadig Abdullah M.Algashami Sadok Turki Department of Computer Science and information College of Science at ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computing and InformaticsUniversity of SharjahSharjahUnited Arab Emirates Higher Institute of Computer Science and Mathematics University of MonastirMonastir5000Tunisia Mars Laboratory University of SousseSousseTunisia Department of Logistic and Maintenance UFR MIM at MetzUniversity of LorraineMetzFrance Department of Computer and information technologies College of Telecommunicationand Information Riyadh CTITechnical and Vocational Training Corporation TVTCRiyadh12464Saudi Arabia Department of Computer Science Higher Institute of Applied Sciences of SousseSousse UniversitySousse4000Tunisia

In the cloud environment,ensuring a high level of data security is in high *** planning storage optimization is part of the whole security process in the cloud *** enables data security by avoiding the risk of data loss and data *** development of data flow scheduling approaches in the cloud environment taking security parameters into account is *** our work,we propose a data scheduling model for the cloud *** is made up of three parts that together help dispatch user data flow to the appropriate *** first component is the Collector Agent whichmust periodically collect information on the state of the network *** second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the *** third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable *** should be noted that each part of the proposedmodel requires the development of its *** this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link *** algorithms are based on the grouping of transmitted files and the iterative *** proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)*** experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

关键词： Cyber-security cloud computing cloud security algorithms heuristics

A Transformer-Assisted Cascade Learning Network for Choroidal Vessel Segmentation

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Journal of Computer Science & Technology 2024年第2期39卷 286-304页

作者：温阳吴依林毕磊石武祯刘潇骁许毓鹏许迅曹文明冯大淦 Guangdong Provincial Key Laboratory of Intelligent information Processing School of Electronics and Information EngineeringShenzhen UniversityShenzhen 518060China Institute of Translational Medicine Shanghai Jiao Tong UniversityShanghai 200240China Department of Ophthalmology Shanghai General HospitalShanghai Jiao Tong University School of MedicineShanghai 200080China School of information technologies The University of SydneySydney 2006Australia

As a highly vascular eye part,the choroid is crucial in various eye disease ***,limited research has focused on the inner structure of the choroid due to the challenges in obtaining sufficient accurate label data,particularly for the choroidal ***,the existing direct choroidal vessel segmentation methods for the intelligent diagnosis of vascular assisted ophthalmic diseases are still unsatisfactory due to noise data,while the synergistic segmentation methods compromise vessel segmentation performance for the choroid layer segmentation *** cascaded structures grapple with error propagation during *** address these challenges,we propose a cascade learning segmentation method for the inner vessel structures of the choroid in this ***,we propose TransformerAssisted Cascade Learning Network(TACLNet)for choroidal vessel segmentation,which comprises a two-stage training strategy:pre-training for choroid layer segmentation and joint training for choroid layer and choroidal vessel *** also enhance the skip connection structures by introducing a multi-scale subtraction connection module designated as MSC,capturing differential and detailed information ***,we implement an auxiliary Transformer branch named ATB to integrate global features into the segmentation *** results exhibit that our method achieves the state-of-the-art performance for choroidal vessel ***,we further validate the significant superiority of the proposed method for retinal fluid segmentation in optical coherence tomography(OCT)scans on a publicly available *** these fully prove that our TACLNet contributes to the advancement of choroidal vessel segmentation and is of great significance for ophthalmic research and clinical application.

关键词： choroidal vessel segmentation optical coherence tomography(OCT) Transformer-assisted cascade learning retinal fluid segmentation multi-scale feature extraction