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Robust Watermarking Based on Multi-layer Watermark Feature Fusion

IEEE Transactions on Multimedia 2025年

作者： Wu, Shaowu Lu, Wei Luo, Xiangyang Sun Yat-Sen University School of Computer Science and Engineering Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Guangzhou510006 China State Key Laboratory of Mathematical Engineering and Advanced Computing Henan450002 China

The purpose of robust image watermarking is to embed a watermark into a carrier image in an invisible form and extract the watermark successfully even under noise interference conditions to achieve copyright confirmation and traceability. Although watermarking methods based on deep learning can improve the robustness by adding a noise simulation layer, few theoretical analyses of the codec structure have been conducted. Theoretical explainability is the theoretical basis for developing a network architecture, which plays a guiding role in network development. On the basis of the interpretability of convolutional networks, this paper analyzes the mathematical process of embedding and extracting watermarks in codecs and proposes a novel watermarking framework based on multi-layer watermark feature fusion. Specifically, the encoder can be a convolutional network structure of arbitrary depth, whereas the decoder needs only to adopt its corresponding deconvolution structure. To improve the quality and robustness of the generated watermarked image, the watermark is associated with an arbitrary layer feature space in the decoder. In the decoder, the network quickly converges to each original encoding feature space through the deconvolution structure, thus decoupling the watermark features. Finally, the watermark is extracted via the automatic fusion of multi-layer watermark features. The experimental results show that the proposed method is suitable for few-shot learning, and its invisibility, robustness and generalization performance on multiple datasets are significantly better than those of other advanced methods. © 2025 IEEE.

关键词： Decoding

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Lag Synchronization and Lag H∞ Synchronization for Multiweighted Coupled Reaction-Diffusion Neural Networks Suffering Topology Attacks

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IEEE Transactions on Control of Network Systems 2025年

作者： Wang, Jin-Liang Zhao, Xin-Yu Ren, Shun-Yan Huang, Tingwen Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems School of Computer Science and Technology Tianjin300387 China Tiangong University School of Electronics & Information Engineering Tianjin300387 China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one hand, by adopting state feedback control scheme, the problem of the lag synchronization for the multistate coupled CRNN is addressed. Moreover, the influences of external disturbances for the lag synchronization of the CRNN with multistate couplings are also taken into consideration. On the other hand, several lag and lag H∞ synchronization conditions for CRNN with multiple spatial-diffusion couplings are derived under the help of the Kronecker product and the state feedback control method. Finally, two numerical examples are provided to verify the correctness of the derived criteria. © 2014 IEEE.

关键词： State feedback

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Distributed Estimation and Motion Control in Multi-Agent Systems Under Multiple Attacks

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IEEE Transactions on Automation science and Engineering 2025年 22卷 12548-12559页

作者： Jenabzadeh, Ahmadreza Shu, Zhan Huang, Tingwen Zhu, Quanmin Shang, Yilun Cui, Yukang Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Peng Cheng Laboratory Shenzhen518000 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China University of the West of England School of Engineering BristolBS16 1QY United Kingdom Northumbria University Faculty of Engineering and Environment Department of Computer and Information Sciences Newcastle upon TyneNE1 8ST United Kingdom

This paper addresses the problem of distributed estimation and motion control (DEMC) in multi-agent systems (MASs) with both linear and Lipschitz nonlinear dynamics. Unlike conventional DEMC methods designed for MASs under ideal conditions, this work investigates scenarios where all agents are vulnerable to various forms of attacks. The considered attacks comprise false-data injection (FDI) attacks and denial of service (DoS) attacks that affect the communication channels among agents to destabilize the MAS. Also, the unbounded actuator attacks which exist in practical environments to intentionally degrade the MAS performance is considered. To cope with these kinds of attacks, two novel resilient approaches are established aimed at estimating and following a mobile target under attacks. The proposed distributed attack-resilient control strategies are designed based on a dual-layer structure, guaranteeing effective DEMC with an ultimately bounded error. The results from two simulation examples are provided to validate the presented algorithms. © 2004-2012 IEEE.

关键词： Multi agent systems

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Mask-Aware Hierarchical Aggregation Transformer for Occluded Person Re-identification

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IEEE Transactions on Circuits and Systems for Video technology 2025年

作者： Zhang, Guoqing Yang, Yan Zheng, Yuhui Martin, Gaven Wang, Ruili Nanjing University of Information Science and Technology School of Computer Science Nanjing210044 China Massey University School of Mathematical and Computational Sciences Auckland0632 New Zealand Massey University Institute for Advanced Study Auckland New Zealand University of Nottingham China School of Computer Science Ningbo China

Occluded person re-identification (Re-ID) is a challenging problem due to the absence of notable discriminative features resulting from incomplete body part images and interference from occluded regions. Recently, some transformer-based methods have demonstrated excellent capabilities in resolving this problem, however these methods are not able to precisely focus on the non-occluded body parts and cannot capture fine-grained local features. To achieve these we propose a Mask-Aware Hierarchical Aggregation TrAnsforMer (MAHATMA) method to enhance occluded person Re-ID. Specifically, we propose a Mask information Embedding (MIE) module, which directs the model to focus on non-occluded body parts by incorporating the mask semantic information of a human body. Furthermore, to effectively capture fine-grained local features, we propose a Hierarchical Feature Aggregation (HFA) module that mines more exploitable high-quality detail information by aggregating hierarchical image patch representations. To further alleviate the feature loss problem, we propose a Diverse Feature Completion (DFC) module, which is able to complete global features through multi-path feature integration. Extensive experimental evaluations demonstrate that our method exhibits superior performance in dealing with occluded and holistic person datasets. © 1991-2012 IEEE.

关键词： Reamers

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A blockchain-oriented covert communication technology with controlled security level based on addressing confusion ciphertext

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Frontiers of computer science 2025年第2期19卷 133-135页

作者： Lejun ZHANG Bo ZHANG Ran GUO Zhujun WANG Guopeng WANG Jing QIU Shen SU Yuan LIU Guangxia XU Zhihong TIAN Sergey GATAULLIN Cyberspace Institute Advanced Technology Guangzhou UniversityGuangzhou 510006China Research and Development Center for E-Learning Ministry of EducationBeijing 100039China College of Information Engineering Yangzhou UniversityYangzhou 225009China School Math and Computer Science Quanzhou Normal UniversityQuanzhou 362000China Pazhou Lab Guangzhou 510330China School of Physics and Materials Science Guangzhou UniversityGuangzhou 510006China Central Economic and Mathematics Institute Russian Academy of SciencesMoscow 117418Russia Industrial Programming Department MIREA-Russian Technological UniversityMoscow 119454Russia

1 Introduction Traditional covert communication[1]usually relies on centralized channels,which are efficient in transmission but susceptible to eavesdropping and attacks,leading to information ***,distributed methods also exist,such as peer-to-peer networks and distributed hash *** technology,which is decentralized,anonymous,non-tamperable and anti-attack,can be applied to covert communication to solve the problems of traditional methods and improve the quality of communication.

关键词： communication tables networks

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Frozen Food Supply Chain Monitoring with IoT

Frozen Food Supply Chain Monitoring with IoT

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International Conference on Ubiquitous information Management and Communication (IMCOM)

作者： Mohd Sallehin Mohd Kassim Muhammad Haziq bin Rozman Faridah Yahya Advanced Telecommunication Technology Cluster International Industrial and Institutional Partnership Department Computer Engineering Technology Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Bachelor of Information Technology (Hons) Internet of Thing Computer Engineering Technology Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Applied Statistics and Data Science Clusters (ASAD) Computer Engineering Technology Section Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

This project aimed to implement a prototype capable of real-time monitoring and control of various parameters in information management setting with Internet of Things (IoT). Research methodology involved designing and implementing the system prototype to resemble a supply container or transportation truck with installed sensors controlled by a microcontroller. Main components used temperature sensors (AHT20), RFID reader for access control, GPS module for location tracking, and a web/mobile dashboard for remote monitoring. Additionally, a robust database system was developed to store sensor readings and transaction history, ensuring data integrity and facilitating seamless communication between components for real-time data transmission. Key findings indicate that the system effectively monitors temperature, manages access control through RFID authentication, tracks real-time location via GPS, and provides a user-friendly dashboard interface for data visualization.

关键词： Temperature sensors Access control Temperature measurement Supply chain management Supply chains Prototypes Data visualization Real-time systems Temperature control Sensors

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Enhancing Group Privacy for Effective CIoT Data Mining in 6G Networks Using Differential Privacy

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IEEE Transactions on Consumer Electronics 2025年

作者： Ning, Bo Zhang, Xinjian Liu, Chengfei Wang, Ning Li, Guanyu Dalian Maritime University School of Information Science and Technology Liaoning Dalian116026 China Swinburne University of Technolgy Department of Computer Science and Software Engineering MelbourneVIC3122 Australia Guangzhou University Cyberspace Institute of Advanced Technology Guangdong Guangzhou511442 China

In the realm of 6G wireless networks, the Consumer Internet of Things (CIoT) aims to revolutionize consumer electronics by integrating advanced technologies such as Artificial Intelligence (AI). As CIoT environments become more dynamic and data-rich, ensuring data privacy while maintaining the utility of data mining is crucial. Graph data mining, which models object relationships with expressive capabilities, is central to this transformation but may pose data leakage risks. Traditional differential privacy methods in graphs often focus on releasing attribute or node information or adding excessive noise, reducing data availability. Therefore our focus is on protecting group relationships and leveraging their closeness to design budget allocation mechanisms that reduce noise. The proposed model uses k-cores to hierarchically manage group relationships, considering the variation in edges between k-cores and (k-1)-cores. Significant changes indicate a high degree of aggregation and interdependence at higher levels, warranting greater privacy protection. By allocating the privacy budget according to edge levels, our approach balances protection and data availability. Experiments on four types of graphs show that the network generated by our model accurately represents the original graph, making it suitable for subsequent data mining applications. © 2025 IEEE.

关键词： information leakage

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FedKD-hybrid: Federated Hybrid Knowledge Distillation for Lithography Hotspot Detection

arXiv

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arXiv 2025年

作者： Li, Yuqi Lin, Xingyou Zhang, Kai Yang, Chuanguang Guo, Zhongliang Gou, Jianping Li, Yanli Institute of Computing Technology Chinese Academy of Sciences China College of Information Engineering Sichuan Agricultural University China Shenzhen University of Advanced Technology China School of Computer Science University of St Andrews United Kingdom College of Computer and Information Science College of Software Southwest University China School of Artificial Intelligence and Computer Science Nantong University China The School of Electrical and Computer Engineering The University of Sydney Australia

Federated Learning (FL) provides novel solutions for machine learning (ML)-based lithography hotspot detection (LHD) under distributed privacy-preserving settings. Currently, two research pipelines have been investigated to aggregate local models and achieve global consensus, including parameter/non-parameter based (also known as knowledge distillation, namely KD). While these two kinds of methods show effectiveness in specific scenarios, we note they have not fully utilized and transferred the information learned, leaving the potential of FL-based LDH remains unexplored. Thus, we propose FedKD-hybrid in this study to mitigate the research gap. Specifically, FedKD-hybrid clients agree on several identical layers across all participants and a public dataset for achieving global consensus. During training, the trained local model will be evaluated on the public dataset, and the generated logits will be uploaded along with the identical layer parameters. The aggregated information is consequently used to update local models via the public dataset as a medium. We compare our proposed FedKD-hybrid with several state-of-the-art (SOTA) FL methods under ICCAD-2012 and FAB (real-world collected) datasets with different settings;the experimental results demonstrate the superior performance of the FedKD-hybrid algorithm. Our code is available at https://***/itsnotacie/NN-FedKD-hybrid. © 2025, CC BY-NC-ND.

关键词： Federated learning

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Flexible Spectrum Sensing in NOMA System for LEO Satellite-Terrestrial Uplink Communications

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IEEE Internet of Things Journal 2025年第11期12卷 18439-18442页

作者： Zhu, Jie Xu, Tianheng Wang, Chao Ying, Kai Zhou, Ting Zhang, Haijun Hu, Honglin Chinese Academy of Sciences Shanghai Advanced Research Institute Shanghai201210 China Tongji University Department of Information and Communication Engineering Shanghai200092 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China Shanghai University School of Microelectronics Shanghai200444 China Shanghai Frontier Innovation Research Institute Shanghai201100 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

With the sixth-generation mobile communication technology (6G) experiencing a shift of spatial expansion, the integration of terrestrial architecture and satellites has become one core feature of 6G. While the scarcity of spectrum resources has become a significant challenge hindering the advancement of integrated satellite-terrestrial networks, it is crucial to push the development of effective strategies to optimize spectrum utilization. This letter introduces a flexible spectrum sensing technique in the Non-Orthogonal Multiple Access (NOMA) uplink system for Low Earth Orbit (LEO) satellite-terrestrial communications, striking an optimal balance between under-sensing and over-sensing. Confronted with diverse complicated scenarios of multi-satellite coverage, we conceive the operational principles and derive the sensing thresholds, exploiting spectrum holes and mitigating the fluctuation of false alarms. Notably, numerical outcomes showcase that the proposed technique outperforms the benchmarks, achieving a maximum throughput gain of 61.5% in dynamic communication environments. © 2014 IEEE.

关键词： Satellite communication systems

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MedFS: pursuing low update overhead via metadata-enabled delta compression for log-structured file system on mobile device 25

MedFS: pursuing low update overhead via metadata-enabled del...

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Proceedings of the 23rd USENIX Conference on File and Storage Technologies

作者： Chao Wu Cheng Ji Li-Pin Chang Zongwei Zhu Congming Gao Weichao Guo Chao Yu Yanzhi Wang Department of Computer Science and Engineering Nanjing University of Science and Technology Department of Computer Science National Yang Ming Chiao Tung University Suzhou Institute for Advanced Research University of Science and Technology of China School of Information Science Xiamen University Guangdong Oppo Mobile Telecommunications Corp. Ltd College of Engineering Northeastern University

ISBN: (纸本)9781939133458

The increasing deployment of data-intensive applications on mobile devices poses a formidable challenge in designing flash-based file systems tailored to these needs. Studies have shown that adopting delta compression in log-structured file systems is promising for such an environment as it can effectively reduce the write stress and improve flash longevity. Unfortunately, delta compression suffers from large maintenance overhead. While prior works have introduced nonvolatile memory buffer or battery-backed DRAM to mitigate this, they are less appealing for cost-sensitive mobile *** paper introduces MedFS, a Metadata-enabled delta compression on log-structured File System for mobile devices, to achieve a good design trade-off in log-structured file systems employing delta compression. Through a comprehensive analysis of mobile applications and file update patterns, we develop delta-inlining technique, which consolidates delta updates within the inline area of the file's inode block. By leveraging the inherent inode structure and automatically flushing dirty inodes to storage, we effectively address the maintenance overhead associated with delta compression. Additionally, we propose a complementary delta maintenance strategy that selectively manages delta chunks in the data area, overcoming the space constraints of the inline area. Experimental results show that MedFS significantly reduces the write traffic by 55.1% on average, leading to the prolonged storage endurance by 122.7% and improved I/O performance by up to 37.3% over existing work.

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