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IEEE Transactions on Sustainable computing 2024年第03期10卷 547-561页

作者： Xiao, Ziheng Zhu, Chenlu Feng, Wei Liu, Shenghao Deng, Xianjun Lu, Hongwei Yang, Laurence T. Park, Jong Hyuk Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China Artificial Intelligence and Intelligent Transportation Joint Technical Center of HUST and Hubei Chutian Intelligent Transportation Company Ltd United States Network and Industrial Control Information Security Technology Department China Nuclear Power Operation Technology Company Ltd. 1011 Xiongchu Avenue Hubei Wuhan430070 China The Department of Computer Science and Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of

Internet of Things (IoT) reliability evaluation contributes to the sustainable computing and enhanced stability of the network. Previous algorithms usually evaluate the reliability of IoT by enumenating the states of nodes and networks, which are difficult to handle IoT with hundreds of nodes because the computational cost. In this paper, a novel algorithm, TMCRA, is proposed to evaluate the reliability of IoT in complex network environment, which consider both coverage and connectivity. For coverage, TMCRA employs the Confident information Coverage (CIC) model to divide the target area into independent grids and calculates the coverage rate. In terms of connectivity, TMCRA forming the Virtual Backbone network (VBN) based on two proposed methods: TMA and MGIN, and evaluate connectivity by analyzing the VBN rather than the whole network. The TMA and MGIN are two algorithms for constructing Minimum Connected Dominant Sets (MCDS), which are suitable for different scale networks. Finally, based on the data of coverage and connectivity, TMCRA utilizes tensors for the unified modeling and representation of network structure, and calculates IoT reliability based on the tensors. Simulations are carried out for various sizes of IoT to show the advantages and effectiveness of the proposed approach in reliability evaluation. © 2016 IEEE.

关键词： Data reliability

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HTtext: A TextCNN-based pre-silicon detection for hardware Trojans

HTtext: A TextCNN-based pre-silicon detection for hardware T...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yi Xu Zhenyi Chen Binhong Huang Ximeng Liu Chen Dong College of Computer and Data Science Fuzhou University Fuzhou China University of South Floride Tampa USA Key Lab of Information Security of Network Systems (Fuzhou University) Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University)

With the advent of the intelligence era, the usage and investment for chips have risen year by year, causing the demand for chip security. Machine learning (ML) analysis has made progress as a pre-silicon hardware Trojan (HT) detection technology. Whereas the performance of existing methods almost relies on the accuracy of multi-feature representation, moreover, it is difficult to extract features manually and easily cause unstable classifier performance (namely uncertainty). In this paper, an automatic feature extraction detecting model is first proposed, named HTtext, which generates simple path sentences from chip netlists and employs TextCNN, a deep learning algorithm, to distinguish HT circuits. The pre-training for TextCNN only uses the automatic single-feature calculation to avoid the uncertainty problem. Additionally, the model can obtain non-repetitive HT component information expression, which satisfies the stable detection performance. To measure the efficiency and balance of the model, the paper proposes the concept of the Stability Efficiency Index (SEI). In the experimental results for the benchmark netlists, not only the average accuracy (ACC) in TextCNN is as high as 99.26%, but also its SEI value ranks first in all comparison classifiers, which proves that the proposed HTtext model has high stability in generality.

关键词： Ports (computers) Semiconductor device measurement Uncertainty Stability criteria Feature extraction Hardware Circuit stability

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Research on security Protection Technology of Intelligent Terminal of Electricity Internet of Things 5

Research on Security Protection Technology of Intelligent Te...

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5th IEEE information Technology, networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Zou, Zhenwan Li, Feng Hou, Yingsa Fei, Jiaxuan Yang, Ruxia Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. Urumqi China Maintenance Company of State Grid Xinjiang Electric Power Co. Ltd. Urumqi China Global Energy Interconnection Research Institute Co. Ltd. Nanjing210003 China State Grid Key Laboratory of Information and Network Security Nanjing210003 China

ISBN: (纸本)9781665415989

With the rapid development of the electricity Internet of Things, intelligent terminals in the power system are widely interconnected and ubiquitously connected. The intelligent terminals have become the main target and springboard for attacking the power grid. In this context, researches are carried out on the security protection of the intelligent terminals of electricity Internet of Things. First, combined with the architecture of the electricity Internet of Things, the connotation and basic characteristics of the intelligent terminals are summarized. Then the risk characteristics of the intelligent terminals are summarized based on the security risks it faced, and finally the corresponding security protection countermeasures are proposed from four aspects, namely encryption authentication, data privacy protection, illegal wireless communication link risk, and equipment security. © 2021 IEEE.

关键词： Internet of things

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The Adaptive Fault-tolerant Routing Based on an Improved Local security information Model of the Exchanged Hypercube

The Adaptive Fault-tolerant Routing Based on an Improved Loc...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yazhi Zhang Chuanwen Luo Guijuan Wang Li Zhang Mengjie Lv Jiguo Yu School of Computer Science and Technology Qilu University of Technology Jinan China School of Information Science and Technology Beijing Forestry University Beijing 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 Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China College of Computer Nanjing University of Posts and Telecommunications Nanjing China Big Data Research Institute Qilu University of Technology (Shandong Academy of Sciences) Jinan China

With the increasing amount of computation in high-performance computing, the scale of interconnection networks is becoming larger and larger. It is inevitable that processors or links in the network become faulty. Therefore, it is very important for a processor to understand the security status of itself and neighbors, and then adaptively and reliably communicate. However, the existing security information models consider faulty processors or faulty links separately, and do not consider the situation where both processors and links fail simultaneously. The Exchanged Hypercube is an excellent interconnection network structure which achieves a balance between network functionality and hardware overhead while preserving many excellent properties of the Hypercube. In this paper, we propose an adaptive fault-tolerant routing algorithm of the Exchanged Hypercube based on an improved local security information model, which considers the faulty processors and faulty links simultaneously. This algorithm always can select suitable processors for routing based on the local security information and unsafe coefficients of processors, which greatly reduces the impact of the faulty of networks. The adaptive fault-tolerant routing algorithm of the Exchanged Hypercube network is not only suitable for regular networks but also for heterogeneous networks since the Exchanged Hypercube is a semi regular network. Sufficient experimental results show that the algorithm proposed in this paper has a lower packet loss rate, a higher success rate, and a shorter average path length.

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Verifiable Privacy Preservation Scheme for Outsourcing Medi-cal Image to Cloud Through ROI Based Crypto-Watermarking

Verifiable Privacy Preservation Scheme for Outsourcing Medi-...

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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： Chuan Zhou Yi Zhou XingHan An Yan Liu Min Wang XiangZhi Liu Tianjin University Tianjin 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 College of Environmental Science and Engineering Beijing Forestry University Beijing China Inspur Software Co. Ltd. Jinan China The Party School of cpc Jinan Municipal Committee Jinan China

A novel verifiable privacy preservation scheme for outsourcing medical image to cloud through ROI based crypto-watermarking is proposed in the paper. In the proposed scheme, data owner firstly carries out substitution of S-box for the region of interest (ROI) of medical image, and then separates the image into 4 most significant bits (MSBs) plane and 4 least significant bits (LSBs) plane images. Secondly, the hash value of ROI is embedded into the two separated bit plane images using reversible watermarking algorithm. Lastly, some selected hash values are transformed into the initial parameters of chaotic maps, and the two sharing secrets, which are produced through chaos based encryption algorithm, are finally outsourced to two different cloud servers. For authorized users, they can get shares from different cloud servers, and then can losslessly recover the original medical image through a series of decryption operations and extraction of watermarking. Furthermore, the users can verify whether the original image is completely reconstructed or not, they even can locate the tampered parts inside ROI if anyone of the sharing secrets is damaged. Some experiments analyses and comparisons are given to show the security and effectiveness of proposed scheme.

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Research on equipment identification technology of power monitoring system

Research on equipment identification technology of power mon...

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International Conference on Mechanical Engineering, Measurement Control, and Instrumentation 2021

作者： Zhang, Hongjie Wang, Qi Zheng, Tiejun He, Jianwei Yong, Shaohua State Grid Ningxia Electric Power Co. Ltd Yinchuan Ningxia750004 China Global Energy Interconnection Research Institute Co. Ltd Nanjing Jiangsu210003 China State Grid Key Laboratory of Information and Network Security Nanjing Jiangsu210003 China State Grid Zhongwei Electric Power Supply Company Zhongwei Ningxia755000 China

ISBN: (数字)9781510647299

ISBN: (纸本)9781510647282

With the rapid development of network technology, a large number of diversified network equipment are applied to the power monitoring system, which not only greatly improves the production efficiency of the power system, but also challenges its own security management. Accurate and comprehensive identification of network equipment is the premise of effective management of network equipment, and also the basis of security threat analysis. In this paper, an equipment identification method based on traffic analysis is proposed. By passively monitoring the traffic in the network, the representative features of the data flow are extracted from multiple dimensions and analyzed. The C4.5 decision tree algorithm is used to generate the identification model, and the equipment in the network is identified by this model, The accuracy rate of equipment identification can reach 94%. © 2021 SPIE.

关键词： Machine learning

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Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision

arXiv

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arXiv 2025年

作者： Han, Xiaofeng Chen, Shunpeng Fu, Zenghuang Feng, Zhe Fan, Lue An, Dong Wang, Changwei Guo, Li Meng, Weiliang Zhang, Xiaopeng Xu, Rongtao Xu, Shibiao The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence Beijing University of Posts and Telecommunications China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center China

Robot vision has greatly benefited from advancements in multimodal fusion techniques and vision-language models (VLMs). We systematically review the applications of multimodal fusion in key robotic vision tasks, including semantic scene understanding, simultaneous localization and mapping (SLAM), 3D object detection, navigation and localization, and robot manipulation. We compare VLMs based on large language models (LLMs) with traditional multimodal fusion methods, analyzing their advantages, limitations, and synergies. Additionally, we conduct an in-depth analysis of commonly used datasets, evaluating their applicability and challenges in real-world robotic scenarios. Furthermore, we identify critical research challenges such as cross-modal alignment, efficient fusion strategies, real-time deployment, and domain adaptation, and propose future research directions, including self-supervised learning for robust multimodal representations, transformer-based fusion architectures, and scalable multimodal frameworks. Through a comprehensive review, comparative analysis, and forward-looking discussion, we provide a valuable reference for advancing multimodal perception and interaction in robotic vision. A comprehensive list of studies in this survey is available at https://***/Xiaofeng-Han-Res/MF-RV. Copyright © 2025, The Authors. All rights reserved.

关键词： Supervised learning

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BCE-PPDS: Blockchain-based cloud–edge collaborative privacy-preserving data sharing scheme for IoT

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Future Generation Computer Systems 2026年 174卷

作者： Guijuan Wang Qi Liu Zhongyuan Yu Hongliang Zhang Anming Dong 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 Shandong 250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan Shandong 250353 China China University of Petroleum Qingdao Shandong 266000 China

Internet of Things (IoT) devices generate large amounts of data every day that can be combined with intelligent platforms for predictive analytics and scientific research. However, concerns about privacy and security hinder the willingness of individuals to share data. Blockchain emerged as a promising infrastructure for facilitating secure data sharing due to its decentralized, immutability, and auditable benefits. In this paper, we propose a blockchain-based cloud–edge collaborative privacy protection data sharing scheme (BCE-PPDS), which is decentralized and enables data requesters (DRs) to search data resources using smart contracts to efficiently obtain target data. To protect the identity privacy of data owners (DOs), we propose a novel certificateless linkable ring signature algorithm with efficient performance. This algorithm is not only suitable for deployment on resource-limited IoT devices, so that DOs can realize anonymous identity authentication, but also can aggregate the generated ring signatures for batch verification, so as to improve the efficiency of signature verification. In addition, we designed a key distribution algorithm using the Asmuth–Bloom secret sharing scheme to ensure the security of the key. Under the random oracle model, BCE-PPDS is provably secure. The experimental results verify that BCE-PPDS is efficient and practical.

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A Dynamic Demand-driven Smart Manufacturing for Mass Individualization Production

A Dynamic Demand-driven Smart Manufacturing for Mass Individ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Qiyu Hong Zhenyi Chen Chen Dong Qiancheng Xiong College of Computer and Data Science Fuzhou University Fuzhou China Key Lab of Information Security of Network Systems Fuzhou University Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University University of South Florida Tampa United States

ISBN: (纸本)9781665442084

Industry 4.0 intends to realize mass individualization production driven by customers’ demands, thus generating several advanced manufacturing modes. However, the existing modes have disadvantages such as low customer participation, low response for modifications in real-time, and low utilization of distributed idle productivity resources. The above deficiencies would not cater to the idea of Industry 4.0 well, making the cost of individualization products too high or the degree of individualization too low. In this paper, a customer highly involved dynamic demand-driven smart manufacturing mode and a mathematical model are presented for mass individualization production. Under this mode, customers can be prosumers, participating in the whole production process and proposing modifications. Meanwhile, multiple distributed idle productivity resources are employed with dynamic demand-driven manufacturing. In consequence of the mathematical model and algorithms, the multiple task allocation among multiple factories problem is solved, maximizing the total profit of available factories with high efficiency and low resource waste. Experiments and comparisons are made about the feasibility and efficiency of the algorithms.

关键词： Productivity Heuristic algorithms Dynamic scheduling Real-time systems Production facilities Mathematical models Fourth Industrial Revolution

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On the ADEP and DOR Analysis of RIS-aided URLLC Systems with Partial CSI in Smart Factory

On the ADEP and DOR Analysis of RIS-aided URLLC Systems with...

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2021 IEEE Globecom Workshops, GC Wkshps 2021

作者： Bao, Tingnan Wang, Haiming Yang, Hong-Chuan Wang, Wen-Jing Hasna, Mazen O. Lenovo Research + Institute of Computing Technology Chinese Academy of Sciences Beijing China Lenovo Reseach Lenovo Group Limited Beijing China University of Victoria Department of Electrical and Computer Engineering Victoria Canada Shaanxi Key Laboratory of Information Communication Network and Security XUPT Xi'an China Qatar University Department of Electrical Engineering Doha Qatar

ISBN: (纸本)9781665423908

Factory automation applications impose stringent quality of service (QoS) over ultra-reliable and low-latency communication (URLLC) system. However, the existing wireless systems cannot meet the requirement for these mission-critical industrial internet-of-things (IIoT) applications. In this paper, we consider the reconfigurable intelligent surface (RIS)-aided URLLC systems in the smart factory. To facilitate the performance analysis of the practical situation, the presence of phase error at RIS is discussed. We analyze and derive approximate closed-form expression of average decoding error probability (ADEP) and the closed-form expression of performance limits de-lay outage rate (DOR) under our proposed scenario, respectively. Through analytical results and associated numerical examples, we demonstrate the effect of the number of reflecting elements at the RIS, channel blocklength and packet size in achieving high reliability and low latency. Therefore, the deployment of RIS can offer an attractive solution to enhance the reliability over URLLC systems in the smart factory. © 2021 IEEE.

关键词： Quality of service

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