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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Shang, Zhigang Li, Mo An, Yanyan Yu, Han Wang, Yi Qin, Jixing Acoustic Science and Technology Laboratory Harbin Engineering University China Harbin Engineering University Key Laboratory of Marine Information Acquisition and Security Ministry of Industry and Information Technology China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China China Academy of Aerospace Systems Science and Engineering Beijing China China State Shipbuilding Corporation Applied Acoustics Research Institute Hangzhou China Unit 91977 of the Pla Beijing China Institute of Acoustics Chinese Academy of Sciences State Key Laboratory of Acoustic Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In order to solve the problem that the air-sea cross-domain network can only establish a single-path transmission connection and cannot effectively use multiple interfaces to transmit data, this paper study a method of parallel transmission through multiple paths, based on the multi homed characteristics of the air-sea cross-domain communication gateway. Due to the differences in the bandwidth, delay and packet loss rate of different paths, the reasonable splitting of data can improve the transmission rate and communication quality of communication signals, integrate the characteristics of each path channel, achieve greater channel equalization and improve the throughput and security of system data transmission. Simulation results show that reasonable data splitting can improve data transmission speed and throughput. © 2022 IEEE.

关键词： Gateways (computer networks)

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A Privacy Protection Scheme for Consumer Electronics data Based on blockchain and AI

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IEEE Transactions on Consumer Electronics 2025年

作者： Wang, Luping Yan, Chen Wu, Hongjie Zhu, Fa Kumari, Saru Alenazi, Mohammed J.F State Key Laboratory of Blockchain and Data Security Suzhou University of Science and Technology Suzhou215009 China Zhejiang University Hangzhou310027 China Suzhou University of Science and Technology Suzhou215009 China Nanjing Forestry University College of Information Science College of Artificial Intelligence Nanjing210037 China Chaudhary Charan Singh University Department of Mathematics Uttar Pradesh Meerut250001 India Department of Computer Engineering Riyadh11451 Saudi Arabia

As information technology advances, a significant amount of data related to consumer electronics has emerged, the consumer data is commonly stored on cloud servers, resulting in frequent data leaks and privacy breaches. To tackle these challenges, we propose a novel privacy protection scheme that combines encryption and blockchain technologies. This approach integrates Searchable Encryption, blockchain, and Artificial Intelligence (AI) to facilitate efficient access control and policy enforcement. By employing a decentralized network structure, our scheme minimizes reliance on a central authority, thereby enhancing system security and reliability. User information is independently stored in both blockchain and cloud systems, with digital signatures ensuring data accuracy. To further bolster user privacy, we implement attribute-based encryption for access management and utilize AI for real-time monitoring of potential security threats and suspicious access patterns. Our scheme also features an attribute revocation mechanism to protect sensitive information from unauthorized access. Additionally, customized smart contracts promote equitable interactions between users and cloud service providers. Lastly, the theoretical analyses and experimental results validate that our solution is both secure and efficient in safeguarding consumer data, highlighting its significant innovative contributions to data privacy protection. © 1975-2011 IEEE.

关键词： Sensitive data

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Attribute-Based key Management for Patient-Centric and Trusted data Access in blockchain-Enabled IoMT

SSRN

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SSRN 2023年

作者： Xiang, Axin Gao, Hongfeng Tian, Youliang Wang, Linjie Xiong, Jinbo State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guizhou Guiyang550025 China Guizhou Provincial Key Laboratory of Cryptography and Blockchain Technology Guizhou University Guizhou Guiyang550025 China Network and Information Management Center Guizhou University Guizhou Guiyang550025 China School of Data Science Tongren University Guizhou Tongren554300 China Fujian Provincial Key Laboratory of Network Security and Cryptology College of Computer and Cyber Security Fujian Normal University Fujian Fuzhou350117 China

Internet of Medical Things (IoMT) provides real-time data collection and access services to medical entities by connecting their devices to Internet. However, within such a complex architecture, achieving patient-centric data access still presents trustworthiness challenges. Ciphertext-policy attribute-based encryption (CP-ABE) and blockchain are both the promising cryptographic technologies that support patients with secure and fine-grained access control over their data. Nevertheless, both have their unique key management issues. In this paper, we propose a novel patient-centric and trusted data access (PCT-DA) system in blockchain-enabled IoMT. Firstly, we develop an online/offline encryption and verifiable outsourced decryption CP-ABE scheme to relieves the computation pressure on patients/users. Secondly, we design a flexible attribute-based key management mechanism to overcome the security drawbacks of data encryption keys and user attribute keys. Finally, we build a trusted integrity audit contract to guarantee the incentive fairness of patients/users, allowing them to release/access medical data honestly. Moreover, theoretical analyses prove that the PCT-DA system not only achieves confidentiality, integrity, auditability and forward/backward security, but also guarantees static security under random oracles. Simulation experiments indicate that our proposal reduces the time cost by approximately 14.14 seconds over state-of-the-art and is more flexible in BE-IoMT. © 2023, The Authors. All rights reserved.

关键词： blockchain

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AsyncSC: An Asynchronous Sidechain for Multi-Domain data Exchange in Internet of Things

arXiv

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arXiv 2024年

作者： Yang, Lingxiao Dong, Xuewen Wan, Zhiguo Gao, Sheng Tong, Wei Lu, Di Shen, Yulong Du, Xiaojiang The School of Computer Science and Technology Xidian University The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education China The Shaanxi Key Laboratory of Blockchain and Secure Computing Xi'An710071 China The Zhejiang Lab Hangzhou311121 China The School of Information Central University of Finance and Economics Beijing100081 China The School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China The School of Computer Science and Technology Xidian University China The Shaanxi Key Laboratory of Network and System Security Xi'An710071 China The School of Engineering and Science Stevens Institute of Technology Hoboken07030 United States

Sidechain techniques improve blockchain scalability and interoperability, providing decentralized exchange and cross-chain collaboration solutions for Internet of Things (IoT) data across various domains. However, current state-of-the-art (SOTA) schemes for IoT multi-domain data exchange are constrained by the need for synchronous networks, hindering efficient cross-chain interactions in discontinuous networks and leading to suboptimal data exchange. In this paper, we propose AsyncSC, a novel asynchronous sidechain construction. It employs a committee to provide Cross-blockchain as a Service (C-BaaS) for data exchange in multi-domain IoT. To fulfill the need for asynchronous and efficient data exchange, we combine the ideas of aggregate signatures and verifiable delay functions to devise a novel cryptographic primitive called delayed aggregate signature (DAS), which constructs asynchronous cross-chain proofs (ACPs) that ensure the security of cross-chain interactions. To ensure the consistency of asynchronous transactions, we propose a multilevel buffered transaction pool that guarantees the transaction sequencing. We analyze and prove the security of AsyncSC, simulate an asynchronous communication environment, and conduct a comprehensive evaluation. The results show that AsyncSC outperforms SOTA schemes, improving throughput by an average of 1.21 to 3.96 times, reducing transaction latency by 59.76% to 83.61%, and maintaining comparable resource overhead. Copyright © 2024, The Authors. All rights reserved.

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Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

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Computer Systems Science & Engineering 2021年第12期39卷 373-390页

作者： Jiaming Mao Mingming Zhang Mu Chen Lu Chen Fei Xia Lei Fan ZiXuan Wang Wenbing Zhao State Grid Jiangsu Electric Power Co. Ltd.Information and Telecommunication BranchNanJing210003China Institute of Information and Communication Global Energy Interconnection Research InstituteState Grid Key Laboratory of Information and Network SecurityNanjing210003China Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Research and Development Center of Post Industry Technology of the State Posts Bureau(Internet of Things Technology)Broadband Wireless Communication Technology Engineering Research Center of the Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing210003China Department of Electrical Engineering and Computer Science Cleveland State UniversityCleveland44115USA

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased net-work traffic *** the past few decades,network traffic identification has been a research hotspot in the field of network management and security ***,as more network services use encryption technology,network traffic identification faces many *** classic machine learning methods can solve many problems that cannot be solved by port-and payload-based methods,manually extract features that are frequently updated is time-consuming and *** learning has good automatic feature learning capabilities and is an ideal method for network traffic identification,particularly encrypted traffic identification;Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled ***,in real scenarios,labeled samples are often difficult to *** paper adjusts the structure of the auxiliary classification generation adversarial network(ACGAN)so that it can use unlabeled samples for training,and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised *** results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network(CNN)based classifier.

关键词： Encrypted traffic recognition deep learning generative adversarial network traffic classification semisupervised learning

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Mechanical Vibration Signal Compression Based on Speech Codecs for Intelligent Manufacturing

SSRN

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SSRN 2023年

作者： Tang, Lili Tian, Hui Chang, Chin-Chen Huang, Hui College of Mechanical Engineering and Automation Huaqiao University Xiamen361021 China College of Computer Science and Technology Huaqiao University Xiamen361021 China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Xiamen361021 China Department of Information Engineering and Computer Science Feng Chia University Taichung40724 Taiwan

How to effectively compress mechanical signals so that they can support remote and real-time health monitoring is a hot issue in the context of intelligent manufacturing. Therefore, this paper presents a novel mechanical vibration signal compression scheme based on speech codecs, which can realize signal compression in many scenarios such as tool wear detection and bearing fault diagnosis. In this work, signal compression is first transformed into a multi-objective optimization problem, and the feasibility of solving this problem from the perspective of speech coding is deeply analyzed. Further, this paper presents five compression algorithms with different compression ratios. The presented algorithms are evaluated with tool wear detection in stone processing and bearing fault diagnosis. The experimental results show that the proposed algorithms can achieve higher compression ratios (4.0~24.6) while ensuring low time overhead (average time not more than 0.0194ms) and high reconstruction quality (MSE index are all lower than 0.008). © 2023, The Authors. All rights reserved.

关键词： Fault detection

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Fight Fire with Fire: How Much Can We Trust ChatGPT on Source Code-Related Tasks?

arXiv

引用

arXiv 2024年

作者： Yu, Xiao Liu, Lei Hu, Xing Keung, Jacky Wai Liu, Jin Xia, Xin State Key Laboratory of Blockchain and Data Security Zhejiang University Zhejiang Hangzhou China Faculty of Electronic and Information Engineering Xi’an Jiaotong University Shanxi Xi’an China Department of Computer Science City University of Hong Kong Hong Kong School of Computer Science Wuhan University Wuhan China College of Computer Science and Technology Zhejiang University Hangzhou China

With the increasing utilization of large language models such as ChatGPT during software development, it has become crucial to verify the quality of code content it generates. Recent studies proposed utilizing ChatGPT as both a developer and tester for multi-agent collaborative software development. The multi-agent collaboration empowers ChatGPT to produce test reports for its generated code, enabling it to self-verify the code content and fix bugs based on these reports. However, these studies did not assess the effectiveness of the generated test reports in validating the code. Therefore, we conduct a comprehensive empirical investigation to evaluate ChatGPT’s self-verification capability in code generation, code completion, and program repair. We request ChatGPT to (1) generate correct code and then self-verify its correctness;(2) complete code without vulnerabilities and then self-verify for the presence of vulnerabilities;and (3) repair buggy code and then self-verify whether the bugs are resolved. Our findings on two code generation datasets, one code completion dataset, and two program repair datasets reveal the following observations: (1) ChatGPT often erroneously predicts its generated incorrect code as correct, its vulnerable completed code as non-vulnerable, and its failed program repairs as successful during its self-verification. (2) The self-contradictory hallucinations in ChatGPT’s behavior arise: (a) ChatGPT initially generates code that it believes to be correct but later predicts it to be incorrect;(b) ChatGPT initially generates code completions that it deems secure but later predicts them to be vulnerable;(c) ChatGPT initially outputs code that it considers successfully repaired but later predicts it to be buggy during its self-verification. (3) The self-verification capability of ChatGPT can be enhanced by asking the guiding question, which queries whether ChatGPT agrees with assertions about incorrectly generated or repaired code and vulnerabil

关键词： Software design

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A Hybrid blockchain Scheme for Tracing Manufacturing Processes and Trading Transactions

A Hybrid Blockchain Scheme for Tracing Manufacturing Process...

引用

International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Ye Yuan Mingxing Yang Ruoting Xiong Yani Sun Xianchao Zhang Wei Ren HuBei Land Resources Vocational College China Gemological Institute China University of Geosciences Wuhan China School of Computing Science University of East Anglia UK Yunnan Key Laboratory of Blockchain Application Technology Yunnan Innovation Institute of Beihang University Kunming China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing China State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR Beijing China Ministry of Education Key Laboratory of Data Protection and Intelligent Management (Sichuan University) China School of Computer Science China University of Geosciences Wuhan China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

blockchain can be envisioned as an enabling framework in terms of cryptography and distributed computing to construct trusted data records among un-trusted users. It can be applied in two typical scenarios - historical process provenance and transaction tracing, by immutably sequentialized blocks. In the former there exists no tokens; but in the latter token handover among accounts should be cryptographically guaranteed. In some situations, above two applications may be both required. E.g., in the manufacture of a jewel, processing flow by different operators should be recorded for quality guaranteeing, and in its trading stage, the ownership handover should be recorded for value confirmation. To tackle above two requirements, two chains are usually thus demanded. In this paper, we propose a single chain solution to avoid cross-chain burden, by a hybrid block structure. The process data can be imported from the legacy (non-anonymous) information processing system, and transaction data stems from anonymous payment demand for ownership handover. We formally describe and prove token handover model with cryptographical authenticity. We also propose several security enhancements in the design for shortening the length of the chain, and protecting the data confidentiality in the chain. Our design is general and not limited to single application. The experimental results and extensive analysis justified that the performance and security of our proposed scheme is efficient.

关键词： Distributed processing data privacy Manufacturing processes information processing Handover Throughput data structures blockchains Delays Periodic structures

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An Algorithm for Detecting Surface Defects in Industrial Strip Steel based on Receptive Field and Feature information Supplementation

An Algorithm for Detecting Surface Defects in Industrial Str...

引用

International Conference on Computer Supported Cooperative Work in Design

作者： Qingyu Xu Jiguo Yu Anming Dong Zihao Shang 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 School of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Big Data Institute 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 Shandong Data Intelligence Information Technology Co. Ltd. Jinan China

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

In the context of industry 4.0 and the rise of intelligent manufacturing, the quality of industrial products is becoming more and more important. Strip steel surface defect detection, as a key link in industrial production, is crucial to ensure the quality of industrial products. However, due to the irregularity of the defect scale and the inconspicuous defect features in the surface defect image of strip steel, it is difficult for the existing detection algorithms to realize the effective detection of defects. In order to better extract the features of defects and improve the network’s ability to detect defects, this paper proposes an algorithm for detecting surface defects on industrial strip steel based on receptive field and feature information supplementation. First, we design a receptive field (RF) module to replace the residual structure in the C3 module, which we name C3RF. This module can effectively increase the network’s receptive field, allowing the network to fully capture irregular defect features without increasing the cost. Second, for the characteristics that defective features are not obvious and tend to lose detail information as the network deepens, an extra information supplemental branching feature fusion pyramid (EFPN) is proposed on the basis of the original PAFPN architecture to compensate for the detail information that is lost by the fragile features in deeper layers. Finally, convolutional block attention module (CBAM) is introduced to replace the spatial pooling pyramid (SPPF) in the baseline network, which enhances the contrast between defects and backgrounds, and improves the classification and localization ability of the network. Our network achieves an accuracy of 82.2% on the publicly available strip steel defect detection dataset, which is a 4.0% improvement over the baseline. The results show that the network constructed in this paper can realize effective defect detection.

关键词： Radio frequency Location awareness Strips Production Feature extraction Real-time systems Hardware

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High Gain Beamforming Method in Low-Frequency Band Using Virtual Array Migration

SSRN

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SSRN 2024年

作者： Hu, Yuan Yin, Jingwei Li, Tianxing Cao, Jianguo Zhang, Liang National Key Laboratory of Underwater Acoustic Technology Harbin Engineering University 145 Nantong Street Nangang District Harbin China Key Laboratory for Polar Acoustics and Application of Ministry of Education Harbin Engineering University Ministry of Education 145 Nantong Street Nangang District Harbin China College of Underwater Acoustic Engineering Harbin Engineering University 145 Nantong Street Nangang District Harbin China Key Laboratory of Marine Information Acquisition and Security Harbin Engineering University Ministry of Industry and Information Technology 145 Nantong Street Nangang District Harbin China Key laboratory of underwater Acoustic Environment Chinese Academy of Sciences 21 North 4th Ring Road Haidian District Beijing China

When measuring the low-frequency radiated noise from underwater low-noise targets, a contradiction emerges between achieving low-frequency gain with large-scale arrays and reducing propagation losses with fixed measurement distances. This paper introduces a virtual array migration method based on actual element phase modulation. This method enhances the suppression of interference signals from undesired directions by increasing the phase difference between the steering vector and each array element, thus achieving high gain measurements under limited aperture conditions. To counteract the decrease in robustness associated with constructing virtual arrays, a virtual array factor is introduced for analysis. The research findings demonstrate that with a virtual array factor of 1, this method performs comparably to conventional beamforming. Opting for a virtual array factor of 5 ensures significant gain in interference signal processing in the low-frequency range, while maintaining robustness. Simulations and lake trial data analyses confirm the effectiveness of this algorithm, which offers substantial advantages in terms of high gain and anti-interference capabilities for low-frequency radiated noise measurements. © 2024, The Authors. All rights reserved.

关键词： Beamforming

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