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7th International Conference on Intelligent, Interactive Systems and Applications, IISA2022

作者： Qiao, Junfeng Pan, Sen Yang, Pei State Grid Key Laboratory of Information and Network Security State Grid Smart Grid Research Institute Co.Ltd Nanjing210003 China

The information system of low-voltage distribution network correctly records the topological structure of distribution network, which is the premise of fine management and safe operation of electric power *** the topology, the most important element is the household change relationship [1].At present, the low-voltage distribution network topology data in the information system is manually entered, so the correctness of the information can not be *** the continuous expansion of the scale of power grid, the structure of low-voltage distribution network is complex, the amount of data of marketing measurement [2], GIS and other information systems is increasing rapidly, each information system operates independently, and the data circulation is poor, which makes it difficult to identify the topology data, so it is urgent to carry out topology *** method proposed in this paper effectively solves the problem of electric data verification, and carries out corresponding experiments and demonstrations on the results, with high accuracy. © 2022 The Authors. Published by Elsevier B.V.

关键词： information systems

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Fair and Verifiable Identity-Based Broadcast Proxy Re-Encryption With Designated Sender Feasible for Medical Internet of Things

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IEEE Transactions on information Forensics and security 2025年 20卷 6033-6045页

作者： Liqing Chen Shiyu Chen Hao Zhang Jian Weng Faculty of Computer and Software Engineering Huaiyin Institute of Technology Huai’an Jiangsu China Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou Fujian China College of Information Science and Technology Jinan University Guangzhou Guangdong China

With the development of big data, cloud computing is widely used by individual and enterprise users due to its powerful computing and storage capabilities. How to share the encrypted data stored in cloud servers flexibly to a group of users and provide effective access control to the users is a hot topic in current research. For that, this paper proposes fair and verifiable identity-based broadcast proxy re-encryption with designated sender (FV-IBBPRE-DS) for Medical Internet of Things (MIoT), which gives the system model, formal definition, and security model of FV-IBBPRE-DS, and constructs a concrete FV-IBBPRE-DS scheme. The data owner in the FV-IBBPRE-DS scheme is able to designate a sender, which is given the decryption privilege of the encrypted data to a set of receivers. The scheme ensures that the participating entities perform the process of data sharing fairly and are able to verify the consistency of the ciphertexts. The FV-IBBPRE-DS scheme achieves chosen ciphertext attack security. The performance analysis demonstrates that the scheme in this paper has significant advantages in re-encrypted ciphertext generation and decryption phase, and can be applied to resource-constrained MIoT devices.

关键词： Receivers Encryption Hospitals Cryptography Cloud computing Genetics Servers Access control Sun Software engineering

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A New Joint Source-Channel Coding Scheme with Overlay Spread Spectrum Transmission 15

A New Joint Source-Channel Coding Scheme with Overlay Spread...

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15th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2023

作者： Chen, Yanzhi Liang, Jifan Wang, Qianfan Ma, Xiao School of Computer Science and Engineering Sun Yat-sen University Guangzhou 510006 China Guangdong Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou 510006 China

ISBN: (纸本)9798350324662

In this paper, we propose a new joint source-channel coding (JSCC) scheme, especially in conjunction with overlay spread spectrum transmission. At the transmitter, a source sequence is redescribed by classified enumerative (CE) coding, resulting in a two-stage description consisting of the index of its type-class and its rank in the associated type-class. The variable-length rank is encoded by a multiple-rate random code, while the fixed-length index of the type-class is encoded into a Walsh-Hadamard sequence, which is then overlaid (in the real field) on the coded signal corresponding to the index for transmission. In particular, to improve energy efficiency, the lower-rate component code is allocated with lower energy. At the receiver, the source can be decoded by searching for type-classes. To predict the performance of the proposed JSCC scheme, we present the estimated bound based on the performance of each type-class. Simulation results show that the performance matches well with the estimate, validating our analysis. Simulation results also show that the proposed JSCC scheme (without source statistics) can approach the JSCC bounds and outperform the double polar JSCC scheme (with perfect source statistics). © 2023 IEEE.

关键词： Direct-sequence spread spectrum (DSSS) enumerative coding joint source-channel coding (JSCC) locally constrained ordered statistic decoding (LC-OSD) random codes

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Improving Performance of LDPC-Coded Links via Partial Superposition Retransmission

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Journal of Communications and information networks 2022年第3期7卷 259-268页

作者： Yinchu Wang Qianfan Wang Ming Jiang Xiao Ma School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China Guangdong Key Laboratory of Information Security Technology Sun Yat-sen UniversityGuangzhou 510006China School of Electronics and Information Technology Sun Yat-sen UniversityGuangzhou 510006China

In this paper,we propose a transmission scheme for uplink and downlink transmissions,where the fifth generation(5G)low-density parity-check(LDPC)codes are implemented for error *** the proposed scheme,the acknowledgment(ACK)or negative acknowledgment(NACK)feedback information is transmitted along with the payload data by cyclically shifting coded sequence,while the re-transmitted codewords are superimposed(XORed)partially on the current *** distinguished feature of the proposed transmission scheme is that it requires neither extra transmission bandwidth nor extra transmission *** also propose to truncate the error patterns for the purpose of reducing the implementation complexity and reducing the error *** results show that the proposed scheme significantly outperforms conventional LDPC-coded *** the 5G LDPC code with length 1920 at the signal-to-noise ratio(SNR)of 1.3 dB,the word error rate(WER)of the data transmitted by the proposed scheme is about 10^(−4),while that of the conventional LDPC-coded transmission is about 10^(−2).

关键词： block Markov superposition transmission(BMST) 5G LDPC codes free-ride coding hybrid automatic repeat request(HARQ) partial superposition

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Stackelberg Game-Based Pricing and Offloading for the DVFS-Enabled MEC Systems

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IEEE Transactions on network and Service Management 2025年第3期22卷 2502-2515页

作者： Mei, Jing Zeng, Cuibin Tong, Zhao Yang, Zhibang Li, Keqin Hunan Normal University College of Information Science and Engineering Changsha410081 China Changsha University in Changsha Hunan Province Key Laboratory of Industrial Internet Technology and Security Hunan 410022 China Hunan University College of Information Science and Engineering Changsha410012 China National Supercomputing Center Hunan Changsha410082 China State University of New York Department of Computer Science New YorkNY12561 United States

Due to the limited computing resources of both mobile devices (MDs) and the mobile edge computing (MEC) server, devising reasonable strategies for MD task offloading, MEC server resource pricing, and resource allocation is crucial. In this paper, a scenario is considered, comprising multiple MDs and a single MEC server. Each MD has a divisible task in each time slot, allowing for partial offloading and the option to discard parts of the task. The MEC server contains multiple computing units with the same computing power, and its computing resources can be dynamically adjusted through dynamic voltage and frequency scaling (DVFS) according to the size of tasks offloaded by MDs. At any given time slice, a Stackelberg game is formulated based on the strategies of the MDs and the strategy of the MEC server. An iterative evolution algorithm is employed to explore the optimal strategies for MDs and the MEC server. Simulation results demonstrate that both parties can reach an equilibrium state through the game, and these experiments confirm that the algorithm effectively enhances system efficiency. © 2004-2012 IEEE.

关键词： Mobile edge computing

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A Blockchain-based PHR Sharing Scheme with Attribute Privacy Protection

A Blockchain-based PHR Sharing Scheme with Attribute Privacy...

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IEEE International Conference on Trust, security and Privacy in Computing and Communications (TrustCom)

作者： Chaohe Lu Zhongyuan Yu Guijuan Wang Anming Dong Xiang Tian School of Computer Science Qufu Normal University Rizhao China School of Information Science and Engineering Lanzhou University Lanzhou China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

With the rapid advancement and application of the Internet of Medical Things (IoMT), personal health records (PHRs) are now increasingly comprised of data collected by Internet of Things (IoT) devices and medical records documented by healthcare professionals. Personal health record (PHR) sharing demonstrates great potential in improving the accuracy of disease diagnosis. However, PHR sharing also brings risks such as illegal access and personal information leakage. Some works explored using blockchain or attribute-based encryption (ABE) to solve these privacy leakage problems, but those solutions did not pay attention to the user’s attribute privacy. In this work, we combine a linear secret sharing scheme (LSSS) and zero-knowledge succinct non-interactive argument of knowledge (zkSNARK) scheme to design an efficient zero-knowledge proof protocol called zk-AHSNARK. It can verify the user’s attribute permissions while also hiding attribute information. Based on zk-AHSNARK, we propose a novel PHR sharing scheme that protects attribute privacy. Data security is ensured by storing encrypted data in the interplanetary file system (IPFS). In addition, we introduce keyword ciphertext search to achieve fast data retrieval, and we implement the search and verification algorithms via a smart contract, ensuring the trustworthiness and integrity of the execution. Finally, through a large number of simulations, we demonstrated the suggested scheme’s viability and security.

关键词： Access control Privacy Smart contracts Blockchains Encryption InterPlanetary File System Medical diagnosis Protection Secure storage Medical diagnostic imaging

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Age of information Analysis for CR-NOMA Aided Uplink Systems with Randomly Arrived Packets

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IEEE Transactions on Communications 2024年

作者： Sun, Yanshi Ye, Yanglin Ding, Zhiguo Zhou, Momiao Liu, Lei Hefei University of Technology School of Computer Science and Information Engineering Hefei230009 China Khalifa University Department of Computer and Information Engineering Abu Dhabi United Arab Emirates Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China

This paper studies the application of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) to reduce age of information (AoI) for uplink transmission. In particular, a time division multiple access (TDMA) based legacy network is considered, where each user is allocated with a dedicated time slot to transmit its status update information. The CR-NOMA is implemented as an add-on to the TDMA legacy network, which enables each user to have more opportunities to transmit by sharing other user's time slots. A rigorous analytical framework is developed to obtain the expressions for AoIs achieved by CR-NOMA with and without re-transmission, by taking the randomness of the status update generating process into consideration. Numerical results are presented to verify the accuracy of the developed analysis. It is shown that the AoI can be significantly reduced by applying CR-NOMA compared to TDMA. Moreover, the use of re-transmission is helpful to reduce AoI, especially when the status arrival rate is low. © 1972-2012 IEEE.

关键词： Markov chains

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Asynchronous Deep Reinforcement Learning for Collaborative Task Computing and On-Demand Resource Allocation in Vehicular Edge Computing

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IEEE Transactions on Intelligent Transportation Systems 2023年第12期24卷 15513-15526页

作者： Liu, Lei Feng, Jie Mu, Xuanyu Pei, Qingqi Lan, Dapeng Xiao, Ming Xidian University Guangzhou Institute of Technology Guangzhou510555 China Ministry of Education Shanghai201804 China Xidian University State Key Laboratory of Integrated Services Networks School of Telecommunication Engineering Shaanxi Xi'an710071 China Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Shaanxi Xi'an710121 China Xidian University State Key Laboratory of Integrated Services Networks Xi'an710071 China University of Oslo Department of Informatics Oslo0373 Norway Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm10044 Sweden

Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the ever-growing service applications in VEC, how to effectively aggregate and flexibly schedule ubiquitous network resources for implementing diverse tasks and meeting differentiated demands from numerous vehicular users remains haunting. Toward this end, we investigate collaborative task computing and on-demand resource allocation. The collaborative computing framework in VEC is provided to support deep collaboration and intelligent management of heterogeneous resources widely distributed in vehicles, edge servers and cloud. Based on this framework, the joint optimization problem of distributed task offloading and multi-resource management is formulated with the aim to maximize the system utility by making the optimal task and resource scheduling policy, the novelty of which lies in the exploration of available vehicle resources and the consideration of service migration. In view of the dynamics, randomness and time-variant of vehicular networks, the asynchronous deep reinforcement algorithm is leveraged to find the optimal solution. Extensive simulation experiments are implemented to demonstrate the superiority of our proposed algorithm in terms of response latency compared with full offloading and random offloading. © 2000-2011 IEEE.

关键词： Reinforcement learning

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Neural network Driven by Density and Parallel Features for Field-Road Mode Mining

Neural Network Driven by Density and Parallel Features for F...

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International Conference on computer Supported Cooperative Work in Design

作者： Fengqi Hao Xiyuan Zhao Cunxiang Bian Jinqiang Bai Qingyan Ding Faculty of Data Science City University of Macau Macau China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

Field-road mode mining (FRMM) has gained increasing attention because of its crucial role in machinery management. As the Global Navigation Satellite System (GNSS) is widely applied in agricultural machinery, many methods based on motion and spatial-temporal features of GNSS trajectory data have been proposed for FRMM. However, these methods ignore the density and parallel features of GNSS points. The two features are useful for FRMM because field points usually have a higher density and more parallel points than road points. Therefore, a neural network driven by density and parallel features is proposed for accurate FRMM. Firstly, a statistical method is designed to extract the density feature (i.e., the number of its neighbor points) and parallel feature (i.e., the number of approximately parallel points in its neighbors) of each point. Then, the two features and eight motion features (e.g., speed, direction, etc.) are fed into a neural network to extract valuable latent features. Finally, a linear classifier is used to identify the field and road categories of GNSS points based on the latent features. Experimental results show that our method outperforms state-of-the-art methods and achieves the accuracy of 91.69% and 86.44% on public Wheat and Paddy datasets, respectively.

关键词： Global navigation satellite system Accuracy Statistical analysis Federated learning Roads Neural networks Time series analysis Feature extraction Trajectory Data mining

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JPEG Compression-Resistant Generative Image Hiding Utilizing Cascaded Invertible networks

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IEEE Transactions on information Forensics and security 2025年 20卷 6019-6032页

作者： Tiewei Qin Bingwen Feng Bingbing Zhou Jilian Zhang Zhihua Xia Jian Weng Wei Lu College of Cyber Security Jinan University Guangzhou China College of Cyber Security Engineering Research Center for Trustworthy AI Ministry of Education Jinan University Guangzhou China School of Computer Science and Engineering Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University Guangzhou China

Generative steganography is renowned for its exceptional undetectability. However, prevalent generative methods often have insufficient capacity for concealing secret images. Furthermore, the sensitivity of commonly utilized generative models exacerbates the challenge of ensuring robustness against channel distortions such as JPEG compression. In this paper, we introduce a generative image hiding network that employs two invertible generators to transform secret images into stego images within a disparate image domain. Additionally, we seamlessly integrate an up-and-down sampling module (UDM) within these generators to facilitate efficient decoupling of the intermediate representations obtained by each generator. The UDM serves multiple purposes: preserving coherence between the intermediate representations, enhancing resilience against JPEG compression, and safeguarding the confidentiality of the concealed images. To address the complexity of mapping both uncompressed and compressed stego images to a unified intermediary representation, we implement two distinct flows for the forward and backward processes of the generator associated with the stego images. The experimental results show that our scheme offers concurrent advantages in terms of full-size image hiding ability, undetectability, confidentiality, and robustness.

关键词： Robustness Steganography Image coding Generators Translation Transform coding Training Gaussian distribution Transforms Standards

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