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A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection

computer Systems Science & engineering 2022年第6期41卷 1043-1056页

作者： Xiaorui Zhang Wenfang Zhang Wei Sun Xingming Sun Sunil Kumar Jha Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszowVoivodeship100031Poland

In a telemedicine diagnosis system,the emergence of 3D imaging enables doctors to make clearer judgments,and its accuracy also directly affects doctors’diagnosis of the *** order to ensure the safe transmission and storage of medical data,a 3D medical watermarking algorithm based on wavelet transform is proposed in this *** proposed algorithm employs the principal component analysis(PCA)transform to reduce the data dimension,which can minimize the error between the extracted components and the original data in the mean square ***,this algorithm helps to create a bacterial foraging model based on particle swarm optimization(BF-PSO),by which the optimal wavelet coefficient is found for embedding and is used as the absolute feature of watermark embedding,thereby achieving the optimal balance between embedding capacity and imperceptibility.A series of experimental results from MATLAB software based on the standard MRI brain volume dataset demonstrate that the proposed algorithm has strong robustness and make the 3D model have small deformation after embedding the watermark.

关键词： 3-D medical watermarking robust watermarking PCA BF-PSO

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Novel Algorithm For Adjacent Vertex-Distinguishing Edge Coloring Of Large-Scale Random Graphs

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Journal of engineering Science and technology Review 2021年第3期14卷 69-75页

作者： Huanping, Zhao Peijin, Zhu Jingwen, Li Huojie, Shi School of Computer and Software Nanyang Institute of Technology Nanyang 473004 China School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China Department of Biological Systems Engineering Washington State University PullmanMI98101 United States

Graph coloring is one of the areas in graph theory with high research importance. Adjacent vertex-distinguishing edge coloring is a type of multi-conditional coloring in graph coloring, but existing associated studies lack analysis on constraint conditions. In this study, a novel algorithm was designed to increase the adjacent vertex-distinguishing edge coloring efficiency of large-scale random graphs. Sub-graphs were produced in this work by using a nondestructive segmentation algorithm to reduce the scale of random graphs, and random pre-coloring was performed on the edges of each sub-graph. Iteration was performed step by step in accordance with regulations by searching the conflict set of inaccurate edge coloring until the color met the requirements of the ultimate objective function. Next, the sub-graphs that were colored successfully were combined to realize adjacent vertex-distinguishing edge coloring of large-scale random graphs. Afterward, the accuracy of the adjacent vertex-distinguishing edge chromatic number was proven through theoretical analysis and experimental comparison. Several experiments were also performed on random graphs with less than 4000 vertexes and an edge density smaller than 0.1. Results show that when the number of vertexes is greater than 2000 and the edge density exceeds 0.07, the run time generally rings from 0.9 s to 1.5 s, whereas the run time for other random graphs is between 0.6 and 1.2 s. The algorithm can solve the adjacent vertex-distinguishing edge chromatic number of random graphs effectively, and the time complexity of the algorithm do not exceed O(n3). The proposed algorithm provides evidence for solving the shortest path of large-scale random graphs. © 2021 school of Science, IHU. All rights reserved

关键词： Multiobjective optimization

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Robust Reversible Audio Watermarking Scheme for Telemedicine and Privacy Protection

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computers, Materials & Continua 2022年第5期71卷 3035-3050页

作者： Xiaorui Zhang Xun Sun Xingming Sun Wei Sun Sunil Kumar Jha Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China IT Fundamentals and Education Technologies Applications University of Information Technology and Management in RzeszowRzeszow Voivodeship100031Poland

The leakage of medical audio data in telemedicine seriously violates the privacy of *** order to avoid the leakage of patient information in telemedicine,a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio *** scheme decomposes the medical audio into two independent embedding domains,embeds the robust watermark and the reversible watermark into the two domains *** order to ensure the audio quality,the Hurst exponent is used to find a suitable position for watermark *** to the independence of the two embedding domains,the embedding of the second-stage reversible watermark will not affect the first-stage watermark,so the robustness of the first-stage watermark can be well *** the second stage,the correlation between the sampling points in the medical audio is used to modify the hidden bits of the histogram to reduce the modification of the medical audio and reduce the distortion caused by reversible *** experiments show that this scheme has strong robustness against signal processing operations such as MP3 compression of 48 db,additive white Gaussian noise(AWGN)of 20 db,low-pass filtering,resampling,re-quantization and other attacks,and has good imperceptibility.

关键词： Telemedicine privacy protection audio watermarking robust reversible watermarking two-stage embedding

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BedIDS: An Effective Network Anomaly Detection Method by Fusing Behavior Evolution characteristics

BedIDS: An Effective Network Anomaly Detection Method by Fus...

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

作者： Zhen Liu Changzhen Hu Chun Shan Junkai Yi Computer School Beijing Information Science & Technology University Beijing China Beijing Key Laboratory of Software Security Engineering Technology School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China School of Automation Beijing Information Science & Technology University Beijing China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

Leveraging artificial intelligence models to enhance the performance of intrusion detection systems has become an important component in the field. However, as the scale of networks continues to expand, the structure of networks becomes more complex, and the amount of data in the networks grows larger. Existing methods are facing numerous challenges, including difficulties in constructing training datasets for models, challenges in transferring and reusing models, and high costs associated with model training. This paper introduces a novel approach named BedIDS. This method involves constructing the evolutionary process of network behavior and calculating the evolutionary characteristics of network behavior. Using only the most fundamental five network traffic features, including IP addresses, BedIDS achieves rapid and accurate detection performance on a device equipped with a 3060ti graphics card. We conducted tests using the CICIDS2017 and UNSW-NB15 datasets to evaluate its performance. Experimental results demonstrate that BedIDS maintains high detection accuracy and improves detection speed while requiring a relatively low AI computing force.

关键词： Training Performance evaluation Radio frequency Privacy Costs Accuracy Intrusion detection Telecommunication traffic Feature extraction Security

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Enhancing Low-Latency and High-Reliability Data Forwarding for In-Vehicle Time-Sensitive Networks

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IEEE Transactions on Vehicular technology 2025年

作者： Sun, Haitong Zhang, Haijun Guan, Wanqing Liu, Xiangnan Ma, Hui Leung, Victor C.M. Hebei Key Laboratory of Space-Air-Ground Intelligent Communication China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden Department of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China

To satisfy the low delay, low jitter, and high success rate requirements for in-vehicle networks, IEEE 802.1 Task Group proposed Time-Sensitive Networking (TSN), which has aroused increasing attention in managing time-critical services in networks. This paper resolves the following issue: how to minimize the worst-case response time (WCRT) of frame forwarding in TSN under no-wait scenarios to guarantee low-latency transmission, stability, and high success rate for in-vehicle TSN networks? Currently, some work resolves this problem by leveraging integer linear programming, and others apply heuristic methods to avoid the time complexity problem, but the success rate is affected since they are prone to get trapped in local optima. To reach a balance between time-complexity and success rate, a scheme named Frame Dynamic Priority Scheduling Mechanism (FDPSM) is proposed, where the frame dynamic priority levels are set up and frames are scheduled accordingly. The target is to maximize the success rate and minimize the WCRT for in-vehicle networks. We evaluate the proposed mechanism from aspects such as traffic forwarding time, size of windows, number of hops, and the network load, together with success rate and the simulation results demonstrate the advantages of the FDPSM for in-vehicle TSN networks. © 2025 IEEE. All rights reserved,

关键词： Integer programming

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Individual Recognition Method of Radiation Source Based on Deep Subdomain Adaptation Network 22

Individual Recognition Method of Radiation Source Based on D...

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22nd IEEE International Conference on Communication technology, ICCT 2022

作者： Tang, Zhen Zhang, Tao Yang, Xiaomeng Qian, Lei The Sixty- Third Research Institute National University of Defense Technology School of Computer and Software Nanjing University of Information Science and Technology Nanjing China The Sixty-Third Research Institute National University of Defense Technology Nanjing China The Sixty- Third Research Institute National University of Defense Technology School of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9781665470674

Aiming at the problem of the recognition accuracy degradation caused by the channel noise inconsistency between the signal of the radiation source to be identified and the trained radiation source dataset, this paper proposes an individual identification method of radiation sources based on subdomain adaptation. First, the radiation source signal is spliced into IQ images to generate a feature data set. Then the improved Resnet-50 network which has been pre-trained on the image set is utilised to extract the common characteristics of the source and target domains. Finally, the local maximum mean difference adaptive layer is added. By calculating the pseudo-labels in the target domain to match the conditional distribution distance, the difference in the characteristic distribution of sub-type radiation sources under different signal-to-noise ratio (SNR) can be reduced, and the model recognition accuracy can be improved. The experimental findings reveal that the proposed method greatly increases the accuracy of the individual radiation source identification technique based on the deep neural network. Under the condition that the SNR of the signal to be detected increases or falls by 4 dB compared to the training dataset, the identification accuracy of the approach suggested in this study improves by 11.4 percent and 12.7 percent respectively compared with the model Resnet-50. © 2022 IEEE.

关键词： Signal to noise ratio

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Attribute-Based Policy-Hiding Redactable Blockchain With Authorizable Verification for Energy Internet

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IEEE Internet of Things Journal 2025年

作者： Xue, Jingting Liu, Liang Li, Fagen Jing, Ximin Zhang, Wenzheng Zhang, Xiaojun Zhou, Yu Southwest Petroleum University School of Computer Science and Software Engineering Engineering Research Center for Intelligent Oil and Gas Exploration Chengdu610500 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Institute of Southwestern Communication Science and Technology on Communication Security Laboratory Chengdu610041 China

The goal of the energy internet is to enable communication between distributed energy endpoints to facilitate information exchange and trading matching. Blockchain, which ensures content consistency, bridges the gaps between multiple energy stakeholders and satisfies the need for universal trust. However, applying blockchain directly in peer-to-peer trading can result in the permanent inclusion of illegal or outdated data in blockchain databases, hindering efficient interaction. Driven by emerging application requirements and legal regulations, redactable blockchain (EuroS&P 2017) was introduced, allowing the block history to be rewritten via collisions in chameleon hash functions. Nevertheless, current solutions still face challenges, including trapdoor security risks, privacy leakage, and indefinite redactions. This paper presents a redactable energy blockchain scheme (REBS) with partially attribute-based policy hiding, which enables controlled multi-authority key generation and redactor attribute verification. To prevent the abuse of redaction permission, REBS employs time-updatable chameleon hash functions for redaction. Additionally, we design a delegation algorithm that adds dynamic flexibility to attribute verification nodes, permitting them to delegate key share distribution authority to other nodes on demand. The detailed security proofs and performance evaluations demonstrate the feasibility of REBS. © 2014 IEEE.

关键词： Energy policy

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UA-HGAT: Uncertainty-aware Heterogeneous Graph Attention Network for Short Text Classification 15

UA-HGAT: Uncertainty-aware Heterogeneous Graph Attention Net...

引用

2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart Data, SmartData 2022

作者： Kong, DeYan Ji, ZhenYan Sang, Yanjuan Dong, Wei Yang, Yanyan Beijing Jiaotong University School of Software Engineering Beijing China Blueintelligence Technology Co.Ltd. R&d Department Wuhan China Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Beijing100190 China

ISBN: (数字)9781665454179

ISBN: (纸本)9781665454179

During the last decade, deep learning has played a significant role in improving text classification which is widely applied in question answering systems, comment extraction, sentiment analysis, etc. Considering that few labeled training data are available, semi-supervised short text classification needs to be studied urgently. Existing works focus on long texts and cannot achieve satisfactory performance on short texts due to the sparsity, non-standardization, and insufficient labeled data. In this paper, we propose a novel uncertainty-aware heterogeneous graph attention network for semi-supervised short text classification (UA-HGAT), which makes full use of limited labeled data and large amounts of unlabeled data via exploiting an uncertainty-aware mechanism. In the model, entity description from Wikipedia is introduced to empower short texts, and word-level information is acquired by Word2Vec. The entity description and word-level information are combined with topic information to address the issue of short text sparseness. In particular, we introduce uncertainty-aware mechanism and negative sample learning to relieve the erroneous high confidence predictions from poorly calibrated models, so that it can offer enough pseudo-label samples for the model training. Extensive experiments show that our model significantly outperforms the SOTA methods on AGNews and Snippets datasets. © 2022 IEEE.

关键词： Sentiment analysis

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R2DET: EXPLORING RELAXED ROTATION EQUIVARIANCE IN 2D OBJECT DETECTION

arXiv

引用

arXiv 2024年

作者： Wu, Zhiqiang Liu, Yingjie Dong, Hanlin Tang, Xuan Yang, Jian Jin, Bo Chen, Mingsong Wei, Xian Software Engineering Institute East China Normal University China School of Communication and Electronic Engineering East China Normal University China School of Geospatial Information Information Engineering University China School of Computer Science and Technology Tongji University China

Group Equivariant Convolution (GConv) empowers models to explore underlying symmetry in data, improving performance. However, real-world scenarios often deviate from ideal symmetric systems caused by physical permutation, characterized by non-trivial actions of a symmetry group, resulting in asymmetries that affect the outputs, a phenomenon known as Symmetry Breaking. Traditional GConv-based methods are constrained by rigid operational rules within group space, assuming data remains strictly symmetry after limited group transformations. This limitation makes it difficult to adapt to Symmetry-Breaking and nonrigid transformations. Motivated by this, we mainly focus on a common scenario: Rotational Symmetry-Breaking. By relaxing strict group transformations within Strict Rotation-Equivariant group Cn, we redefine a Relaxed Rotation-Equivariant group Rn and introduce a novel Relaxed Rotation-Equivariant GConv (R2GConv) with only a minimal increase of 4n parameters compared to GConv. Based on R2GConv, we propose a Relaxed Rotation-Equivariant Network (R2Net) as the backbone and develop a Relaxed Rotation-Equivariant Object Detector (R2Det) for 2D object detection. Experimental results demonstrate the effectiveness of the proposed R2GConv in natural image classification, and R2Det achieves excellent performance in 2D object detection with improved generalization capabilities and robustness. The code is available in https://***/wuer5/r2det. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Securing Real-Time Systems using Schedule Reconfiguration

Securing Real-Time Systems using Schedule Reconfiguration

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International Symposium on Object-Oriented Real-Time Distributed Computing

作者： Zain A. H. Hammadeh Monowar Hasan Mohammad Hamad Institute for Software Technology German Aerospace Center (DLR) Braunschweig Germany School of Electrical Engineering & Computer Science Washington State University Pullman WA USA Department of Computer Engineering Technical University of Munich Munich Germany

ISBN: (数字)9798350371284

ISBN: (纸本)9798350371291

Modern real-time systems are susceptible to cyber-attacks. The growing adoption of multi-core platforms, where safety and non-safety critical tasks coexist, further introduces new security challenges. Existing solutions suffer from either a lack of determinism or excessive cost. This paper addresses these shortcomings and proposes an offline analysis to compute all feasible schedules for real-time tasks running on a multi-core platform, isolating compromised tasks while guaranteeing a fail-operational system and low-cost reconfigurable scheduling. Our experimental results using a UAV autopilot system on a quad-core platform (Raspberry Pi) demonstrate that the proposed scheme incurs run-time recovery overhead at the level of microseconds. Also, the reconfiguration process covers up to 100% of all possible responses for compromised tasks in the synthetic test cases.

关键词： Schedules Processor scheduling Autonomous aerial vehicles Market research Real-time systems Safety Security

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