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Witness encryption with updatable ciphertexts

Science China(Information Sciences) 2025年第3期68卷 181-196页

作者： Yuzhu WANG Mingwu ZHANG School of Computer Science and Information Security Guilin University of Electronic Technology School of Computer Science Hubei University of Technology

Witness encryption(WE) is a novel type of cryptographic primitive that enables a message to be encrypted via an NP instance. Anyone who possesses a solution to this instance(i.e., a witness) can then recover the message from the *** introduce a variant of WE that allows ciphertext updates, referred to as ciphertext updateable WE(CUWE). With CUWE,a user can encrypt a message using an instance x and a tag t, and those who possess a valid witness w for x and match the access policy defined by tag t can decrypt the message. Furthermore, CUWE allows for the use of an update token to change the tag t of ciphertext to a different tag. This feature enables fine-grained access control, even after the ciphertext has been created, thereby significantly increasing the usefulness of the WE scheme. We demonstrate that such a WE framework with an updatable ciphertext scheme can be constructed using our puncturable instance-based deterministic encryption(PIDE) and indistinguishability obfuscation(iO). We also propose an instantiation of PIDE utilizing puncturable pseudorandom functions(PRFs) that provide(selectively) indistinguishable security. Finally, we expand our CUWE to ciphertext-updatable functional WE(CUFWE), which offers enhanced data access control.

关键词： witness encryption NP relation updatable ciphertext access control indistinguishable obfuscation

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Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

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computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

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A Blockchain-Based Efficient Cross-Domain Authentication Scheme for Internet of Vehicles

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computers, Materials & Continua 2024年第7期80卷 567-585页

作者： Feng Zhao Hongtao Ding Chunhai Li Zhaoyu Su Guoling Liang Changsong Yang Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China School of Information and Communication Guilin University of Electronic TechnologyGuilin541004China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China

The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the ***,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain *** such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication ***,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency *** mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for *** scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree *** divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and ***,we evaluate the performance of *** results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%.

关键词： Blockchain cross-domain authentication internet of vehicle zero-knowledge proof

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A new intelligent cross-domain routing method in SDN based on a proposed multiagent reinforcement learning algorithm

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International Journal of Intelligent Computing and Cybernetics 2024年第2期17卷 330-362页

作者： Miao Ye Lin Qiang Huang Xiao Li Wang Yong Wang Qiu Xiang Jiang Hong Bing Qiu School of Information and Communication Guilin University of Electronic TechnologyGuilinChina School of Computer and Information Security Guilin University of Electronic TechnologyGuilinChina School of Computer Science and Technology Xidian UniversityXianChina School of Optoelectronic Egineering Guilin University of Electronic TechnologyGuilinChina

Purpose–A cross-domain intelligent software-defined network(SDN)routing method based on a proposed multiagent deep reinforcement learning(MDRL)method is ***/methodology/approach–First,the network is divided into multiple subdomains managed by multiple local controllers,and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement ***,a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers,and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real ***,after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers,a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real ***–Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first(OSPF)routing methods Originality/value–Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds,coupled with the shortcomings of traditional interdomain routing methods,such as cumbersome configuration and inflexible acquisition of network state *** drawbacks make it difficult to obtain global state information about the network,and the optimal routing decision cannot be made in real time,affecting network *** paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL ***,the network

关键词： Reinforcement learning Cross-domain intelligent routing Network traffic state prediction Software-defined network

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Super-resolution reconstruction of single image for latent features

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Computational Visual Media 2024年第6期10卷 1219-1239页

作者： Xin Wang Jing-Ke Yan Jing-Ye Cai Jian-Hua Deng Qin Qin Yao Cheng School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610000 China State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong UniversityChengdu 610000China School of Marine Engineering Guilin University of Electronic TechnologyGuilin 541000China School of Computer and Information Security Guilin University of Electronic TechnologyGuilin 541000China

Single-image super-resolution(SISR)typically focuses on restoring various degraded low-resolution(LR)images to a single high-resolution(HR)***,during SISR tasks,it is often challenging for models to simultaneously maintain high quality and rapid sampling while preserving diversity in details and texture *** challenge can lead to issues such as model collapse,lack of rich details and texture features in the reconstructed HR images,and excessive time consumption for model *** address these problems,this paper proposes a Latent Feature-oriented Diffusion Probability Model(LDDPM).First,we designed a conditional encoder capable of effectively encoding LR images,reducing the solution space for model image reconstruction and thereby improving the quality of the reconstructed *** then employed a normalized flow and multimodal adversarial training,learning from complex multimodal distributions,to model the denoising *** so boosts the generative modeling capabilities within a minimal number of sampling *** comparisons of our proposed model with existing SISR methods on mainstream datasets demonstrate that our model reconstructs more realistic HR images and achieves better performance on multiple evaluation metrics,providing a fresh perspective for tackling SISR tasks.

关键词： image superresolution reconstruction denoising diffusion probabilistic model normalized flow adversarial neural network variational auto-encoder

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Image Super-Resolution Reconstruction Based on the DSSTU-Net Model

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computers, Materials & Continua 2025年第4期83卷 1057-1078页

作者： Bonan Yu Taiping Mo Qi Ma Qiumei Li Peng Sun School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China School of Architecture and Transportation Engineering Guilin University of Electronic TechnologyGuilin541004China Key Laboratory of Intelligence Integrated Automation in Guangxi Universities Guilin541004China

Super-resolution(SR)reconstruction addresses the challenge of enhancing image resolution,which is critical in domains such as medical imaging,remote sensing,and computational ***-quality image reconstruction is essential for enhancing visual details and improving the accuracy of subsequent *** methods,including interpolation techniques and basic CNNs,often fail to recover fine textures and detailed structures,particularly in complex or high-frequency *** this paper,we present Deep Supervised Swin Transformer U-Net(DSSTU-Net),a novel architecture designed to improve image SR by integrating Residual Swin Transformer Blocks(RSTB)and Deep Supervision(DS)mechanisms into the U-Net ***-Net leverages the Swin Transformer’s multi-scale attention capabilities for robust feature extraction,while DS at various stages of the network ensures better gradient propagation and refined feature *** ST block introduces a hierarchical self-attention mechanism,allowing the model to capture both local and global context,which is crucial for high-quality SR ***,DS applied at multiple layers in the decoder enables direct supervision on intermediate feature maps,accelerating convergence and improving *** DSSTU-Net architecture was rigorously evaluated on the DIV2K,LSDIR,SET5,and SET14 datasets,demonstrating its superior ability to generate high-quality ***,the potential applications of this model extend beyond image enhancement,with promising use cases in medical imaging,satellite imagery,and industrial inspection,where high-quality image reconstruction plays a crucial role in accurate diagnostics and operational *** work provides a reference method for future research on advanced image restoration techniques.

关键词： SR DSSTU-Net RSTB DS

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Distributed dynamic event-based finite-time dissipative synchronization control for semi-Markov switched fuzzy cyber-physical systems against random packet losses

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Chinese Physics B 2023年第10期32卷 328-342页

作者：伍锡如张煜翀张畑畑张斌磊 School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin 541004China

This paper is concerned with the finite-time dissipative synchronization control problem of semi-Markov switched cyber-physical systems in the presence of packet losses, which is constructed by the Takagi–Sugeno fuzzy model. To save the network communication burden, a distributed dynamic event-triggered mechanism is developed to restrain the information update. Besides, random packet dropouts following the Bernoulli distribution are assumed to occur in sensor to controller channels, where the triggered control input is analyzed via an equivalent method containing a new stochastic variable. By establishing the mode-dependent Lyapunov–Krasovskii functional with augmented terms, the finite-time boundness of the error system limited to strict dissipativity is studied. As a result of the help of an extended reciprocally convex matrix inequality technique, less conservative criteria in terms of linear matrix inequalities are deduced to calculate the desired control gains. Finally, two examples in regard to practical systems are provided to display the effectiveness of the proposed theory.

关键词： cyber-physical systems finite-time synchronization distributed dynamic event-triggered mechanism random packet losses

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Learning attention characterization based on head pose sight estimation

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Multimedia Tools and Applications 2024年第38期83卷 85917-85937页

作者： Mo, Jianwen Liang, Haochang Yuan, Hua Shou, Zhaoyu Zhang, Huibing School of Information and Communication Guilin University of Electronic Technology Guilin541001 China School of Computer and Information Security Guilin University of Electronic Technology Guilin541001 China

The degree of students’ attentiveness in the classroom is known as learning attention and is the main indicator used to portray students’ learning status in the classroom. Studying smart classroom time-series image data and analyzing students’ attention to learning are important tools for improving student learning effects. To this end, this paper proposes a learning attention analysis algorithm based on the head pose sight *** algorithm first employs multi-scale hourglass attention to enable the head pose estimation model to capture more spatial pose *** is also proposed that the multi-classification multi-regression losses guide the model to learn different granularity of pose features, making the model more sensitive to subtle inter-class distinction of the data;Second, a sight estimation algorithm on 3D space is innovatively adopted to compute the coordinates of the student’s sight landing point through the head pose;Finally, a model of sight analysis over the duration of a knowledge point is constructed to characterize students’ attention to learning. Experiments show that the algorithm in this paper can effectively reduce the head pose estimation error, accurately characterize students’ learning attention, and provide strong technical support for the analysis of students’ learning effect. The algorithm demonstrates its potential application value and can be deployed in smart classrooms in schools. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Contrastive Learning

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Preparation of NiTip/Al composites with controllable phase transformation and damping behavior by friction stir processing

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Science China(Technological Sciences) 2024年第2期67卷 597-607页

作者： WU Xiao JIANG HongJie LI WangYun LIU ChongYu HUANG HongFeng LIU ShuHui WEI LiLi School of Material Science and Engineering Guilin University of Technology Guilin 541004China Key Laboratory of New Processing Technology for Nonferrous Metal&Materials Ministry of EducationGuilin University of Technology Guilin 541004China School of Mechanical and Electrical Engineering Guilin University of Electronic TechnologyGuilin 541004China

The NiTip/1060Al composites were prepared using a pre-aging and friction stir method(FSP)to enhance the low-temperature damping performance of the aluminum alloy and accommodate various service *** bonding between NiTi particles and the 1060Al matrix is well established after FSP,and no new phases are formed in the *** phasetransformation peak temperature of NiTip/1060Al composites gradually shifts to lower temperatures with increased aging temperature of NiTi *** room temperature,the 550℃-NiTip/1060Al composite exhibits superior damping performance,with an internal friction value 144%higher than that of the FSP-1060Al ***,at-91℃,the 650℃-NiTip/1060Al composite demonstrates better damping performance,with an internal friction value 158%higher than that of the FSP-1060Al *** NiTip/1060Al composites exhibit the internal friction peak of NiTi phase-transformation in the temperature range from-91℃to 60℃.This characteristic results in significantly better damping performance compared to the FSP-1060Al alloy and other high-damping aluminum matrix composites.

关键词： NiTi particle aluminum matrix composites phase transformation damping behavior friction stir processing

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A Novel Directional Pilot Protection Method for EHV Transmission Lines Considering Fault Factors

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engineering Letters 2025年第3期33卷 678-687页

作者： Guo, Zhenwei Deng, Yingcai Zhao, Ruiqiang Zhang, Tong School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin541000 China

The traveling wave directional protection offers the advantage of ultra-high-speed action and high sensitivity, meeting the urgent demand for high-speed protection in extra-high-voltage (EHV) transmission systems. However, conventional traveling wave directional protection exhibits insufficient reliability during weak faults, i.e., large fault resistance and small fault angles, making it challenging to implement in reality. Based on the energy difference between reverse and forward traveling waves, this paper proposes a novel traveling wave directional pilot protection method considering fault factors. The method identifies the fault direction using the Normalised Directional Energy Difference (NED). The NED is greater than the threshold for forward faults and less than the threshold for reverse faults. The NED contains information about the fault resistance and the fault angle, effectively eliminating their influence. Based on the engineering parameters of the Central China Power Grid, a 500 kV transmission system is simulated in EMTP-RV. Extensive test results demonstrate that the proposed method can swiftly and reliably identify fault directions under different fault conditions. © 2025, International Association of Engineers. All rights reserved.

关键词： EHV power transmission

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