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RDH-DES: Reversible Data Hiding over Distributed Encrypted-Image Servers Based on Secret Sharing

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ACM Transactions on Multimedia Computing, Communications and Applications 2023年第1期19卷 5-5页

作者： Xiong, Lizhi Han, Xiao Yang, Ching-Nung Xia, Zhihua Engineering Research Center of Digital Forensics Ministry of Education School of Computer and Software Nanjing University of Information Science and Technology No. 219 Ningliu Road Nanjing Jiangsu210044 China Department of Computer Science and Information Engineering National Dong Hwa University No. 1 Sec. 2 Da Hsueh Rd. Hualien974301 Taiwan

Reversible Data Hiding in Encrypted Image (RDHEI) schemes may redistribute the data hiding procedure to other parties and can preserve privacy of the cover image. Recently, cloud computing technology has led to the rapid growth of networked media, and many multimedia rights are owned by multiple parties, such as a film's producer and multiple distributors. Thus, the data hiding task could be distributed to multiple distributed servers. Multi-party data hiding has become an important demand for networked media. In addition, it is essential to preserve multi-server and multi-message privacy and data integrity. However, most of the RDHEI schemes involve only one data hider. That inspired us to design the secure multi-party embedding over distributed encrypted-image servers as a solution for multi-party RDHEI applications. In this article, we propose a novel Reversible Data Hiding over Distributed Encrypted-Image Servers (RDH-DES) based on secret sharing. The Chinese remainder theorem, secret sharing, and block-level scrambling are developed as a lightweight cryptography to generate the encrypted image shares. These shares are distributed to different image servers and are used to embed secret data in the proposed framework. The marked encrypted image can be constructed through the marked encrypted shares from different parties, and the decryption and extraction can be completed by the receiver. The experimental results and theoretical analysis have demonstrated that the proposed scheme is secure and effective. © 2023 Association for Computing Machinery.

关键词： Steganography

A Digital Twin-based Intelligent Network Architecture for Underwater Acoustic Sensor Networks

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arXiv 2024年

作者： Song, Shanshan Huangfu, Bingwen Guo, Jiani Liu, Jun Cui, Junhong Shen, Xuemin The College of Computer Science and Technology Jilin University Changchun130012 China The School of Electronic and Information Engineering Beihang University Beijing100191 China Shenzhen Institute for Advanced Study UESTC Shenzhen China The College of Computer Science and Technology Jilin University Changchun China The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Underwater acoustic sensor networks (UASNs) drive toward strong environmental adaptability, intelligence, and multifunctionality. However, due to unique UASN characteristics, such as long propagation delay, dynamic channel quality, and high attenuation, existing studies present untimeliness, inefficiency, and inflexibility in real practice. Digital twin (DT) technology is promising for UASNs to break the above bottlenecks by providing high-fidelity status prediction and exploring optimal schemes. In this article, we propose a Digital Twin-based Network Architecture (DTNA), enhancing UASNs’ environmental adaptability, intelligence, and multifunctionality. By extracting real UASN information from local (node) and global (network) levels, we first design a layered architecture to improve the DT replica fidelity and UASN control flexibility. In local DT, we develop a resource allocation paradigm (RAPD), which rapidly perceives performance variations and iteratively optimizes allocation schemes to improve real-time environmental adaptability of resource allocation algorithms. In global DT, we aggregate decentralized local DT data and propose a collaborative Multi-agent reinforcement learning framework (CMFD) and a task-oriented network slicing (TNSD). CMFD patches scarce real data and provides extensive DT data to accelerate AI model training. TNSD unifies heterogeneous tasks’ demand extraction and efficiently provides comprehensive network status, improving the flexibility of multi-task scheduling algorithms. Finally, practical and simulation experiments verify the high fidelity of DT. Compared with the original UASN architecture, experiment results demonstrate that DTNA can: (i) improve the timeliness and robustness of resource allocation;(ii) greatly reduce the training time of AI algorithms;(iii) more rapidly obtain network status for multi-task scheduling at a low cost. Copyright © 2024, The Authors. All rights reserved.

关键词： Resource allocation

Testing Physical Unclonable Functions Implemented on Commercial Off-the-Shelf NAND Flash Memories Using Programming Disturbances 12

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Testing Physical Unclonable Functions Implemented on Commerc...

12th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2022

作者： Anagnostopoulos, Nikolaos Athanasios Fan, Yufan Saleem, Muhammad Umair Mexis, Nico Gelóczi, Emiliia Klement, Felix Frank, Florian Schaller, André Arul, Tolga Katzenbeisser, Stefan University of Passau Faculty of Computer Science and Mathematics Innstraße 43 Passau94032 Germany Technical University of Darmstadt Computer Science Department Hochschulstraße 10 Darmstadt64289 Germany Technical University of Darmstadt Department of Electrical Engineering and Information Technology Merckstraße 25 Darmstadt64283 Germany EUMETSAT Allee 1 Darmstadt64295 Germany

In this work, we present a Physical Unclonable Function (PUF) implemented on a Commercial Off-The-Shelf (COTS) NAND Flash memory module using programming disturbances, and examine the robustness of its responses to environmental variations. In particular, we test a removable Flash memory module serving as a PUF, under nominal conditions, as well as under temperature and voltage variations. To determine its resilience to environmental variations, we utilise well-known PUF metrics, such as the Hamming weight and the intra-device Hamming distance. Our results prove that, in general, the tested Samsung K9F1G08U0E NAND Flash memory can be used to realise a lightweight, scalable, and flexible hardware security primitive, namely a PUF, that can be utilised in the context of smart homes, smart vehicles, and other smart applications, as well as to protect commercial devices and networks in general. However, voltage variations seem to pose a substantial threat to the adoption of this PUF in practice. This threat may be addressed by small-scale design improvements that should be implemented and tested in practice as part of future works. © 2022 IEEE.

关键词： Automation

PSCodec: A Series of High-Fidelity Low-bitrate Neural Speech Codecs Leveraging Prompt Encoders

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arXiv 2024年

作者： Pan, Yu Zhang, Xiang Yang, Yuguang Yao, Jixun Hu, Yanni Ye, Jianhao Zhou, Hongbin Ma, Lei Zhao, Jianjun The School of Information Science and Electrical Engineering Kyushu University Fukuoka8190385 Japan The Shanghai Ximalaya Technology Co Ltd. Shanghai201203 China The Department of Computer Science The University of Tokyo Tokyo1138656 Japan The Department of Electrical and Computer Engineering University of Alberta EdmontonT2G 1S6 Canada

Neural speech codecs have recently emerged as a focal point in the fields of speech compression and generation. Despite this progress, achieving high-quality speech reconstruction under low-bitrate scenarios remains a significant challenge. In this paper, we propose PSCodec, a series of neural speech codecs integrated effective prompt encoders, including PSCodec-Base, PSCodec-DRL-ICT, and PSCodec-CasAN, which excel in delivering high-performance speech reconstruction with low bandwidths. Specifically, we first introduce PSCodec-Base, which leverages a pretrained speaker verification model-based prompt encoder (VPP-Enc) and a learnable Mel-spectrogram-based prompt encoder (MelP-Enc) to effectively disentangle and integrate voiceprint and Mel-related features in utterances. To further enhance feature utilization efficiency, we propose PSCodec-DRL-ICT, incorporating a structural similarity (SSIM) based disentangled representation loss (DRL) and an incremental continuous training (ICT) strategy. While PSCodec-DRL-ICT achieves impressive performance, its reliance on extensive hyperparameter tuning and multi-stage training introduces complexity. To circumvent these limitations, we propose PSCodec-CasAN, utilizing an advanced cascaded attention network (CasAN) to enhance representational capacity of the entire system. Extensive experiments indicate that our proposed PSCodec-Base, PSCodec-DRL-ICT, and PSCodec-CasAN all significantly outperform several state-of-the-art neural codecs, offering substantial improvements in speech reconstruction quality and speaker similarity under low-bitrate conditions. © 2024, CC BY-NC-ND.

关键词： Speech enhancement

User-centric Immersive Communications in 6G: A Data-oriented Framework via Digital Twin

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arXiv 2024年

作者： Zhou, Conghao Hu, Shisheng Gao, Jie Huang, Xinyu Zhuang, Weihua Shen, Xuemin Sherman School of Telecommunications Engineering Xidian University China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada School of Information Technology Carleton University OttawaONK1S 5B6 Canada

In this article, we present a novel user-centric service provision for immersive communications (IC) in 6G to deal with the uncertainty of individual user behaviors while satisfying unique requirements on the quality of multi-sensory experience. To this end, we propose a data-oriented framework for network resource management, featuring personalized data management that can support network modeling tailored to different user demands. Our framework leverages the digital twin (DT) technique as a key enabler. Particularly, a DT is established for each user, and the data attributes in the DT are customized based on the characteristics of the user. The DT functions, corresponding to various data operations, are customized in the development, evaluation, and update of network models to meet unique user demands. A trace-driven case study demonstrates the effectiveness of our framework in achieving user-centric IC and the significance of personalized data management in 6G. Copyright © 2024, The Authors. All rights reserved.

关键词： Data quality

A Data Completion Algorithm Based on Low-Rank Prior Knowledge for Data-Driven Applications

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IEEE Transactions on Network and Service Management 2024年

作者： Tang, Jun Guo, Bing Shen, Yan Garg, Sahil Kaddoum, Georges Hossain, M. Shamim Sichuan University College of Computer Science Chengdu China Chengdu University of Information Technology School of Computer Science Chengdu China École de Technologie Supérieure Electrical Engineering Department MontréalQCH3C 1K3 Canada Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact and Outcome Punjab Rajpura140401 India Lebanese American University Artificial Intelligence and Cyber Systems Research Center Beirut03797751 Lebanon King Saud University College of Computer and Information Sciences Department of Software Engineering Riyadh12372 Saudi Arabia

Low rank tensor ring based data recovery algorithms have been widely used in data-driven consumer electronics to recover missing data entries in the collecting data pre-processing stage for providing stable and reliable service. However, traditional recovery methods often fail to utilize the abundant prior knowledge of data and the non-local self-similarity of the data, thus leading to the failure to effectively capture the spatial relationships within high-dimensional data to recover them accurately. To address these problems, we present a novel Non-local Self-similarity and Low-rank Prior Knowledge based tensor ring completion method. Firstly, we incorporate the BM3D denoising operator within a Plug-and-Play framework to exploit the self-similarity in the data. Then a logarithmic determinant function is integrated to distinguish singular values in the cyclic unfolding matrix of the tensor and adopts a tensor ring completion approach based on weighted nuclear norms. Finally, in order to evaluate the effectiveness of our proposed method, we conducted a series of experiments by using the missing image dataset and the missing traffic data dataset respectively, and the experimental results show that our method achieves the highest level in terms of data recovery accuracy. © 2024 IEEE.

关键词： Data assimilation

Polarization-insensitive thin-film lithium niobate electro-optic modulator

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Polarization-insensitive thin-film lithium niobate electro-o...

CLEO: Science and Innovations, S and I 2022

作者： Pan, Ying He, Mingbo Xu, Mengyue Lin, Zhongjin Ke, Wei Lin, Yanmei Yu, Siyuan Cai, Xinlun State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University Guangzhou China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

Based on the thin-film lithium niobate platform, we experimentally demonstrate a polarization-insensitive electro-optic modulator which features a polarization-dependent loss of 0.35 dB and an on-chip loss of less tha... 详细信息

ISBN: (纸本)9781557528209

关键词： Thin films

Performance of A Reconfigurable Intelligent Surface Controlled by An Illegitimate User

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arXiv 2023年

作者： Chen, Xinwu Han, Shuai Jiang, Hai The School of Electronics and Information Engineering Harbin Institute of Technology Harbin150001 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 1H9 Canada

In this paper, we investigate how an illegitimate user can use a reconfigurable intelligent surface (RIS) to maximally degrade the secrecy performance of the legitimate system. We first consider the case when the illegitimate user performs eavesdropping only. A problem is formulated to minimize the system secrecy rate by optimizing the phase shifts of the RIS elements. We also consider the case when the illegitimate user works with full-duplex technology and can perform eavesdropping and jamming simultaneously through the RIS. A problem is formulated to minimize the system secrecy rate by optimizing the jamming power and the phase shifts of the RIS elements. Although the two formulated problems are nonconvex, they are optimally solved in this paper. Our results show that good eavesdropping performance can be achieved by placing the RIS at an appropriate position. Further, jamming plus eavesdropping can largely reduce the secrecy rate of the legitimate system. Copyright © 2023, The Authors. All rights reserved.

关键词： Jamming

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arXiv 2024年

作者： Zhang, Keke Chen, Weiling Zhao, Tiesong Wang, Zhou Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information College of Physics and Information Engineering Fuzhou University Fuzhou350108 China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350108 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Image Quality Assessment (IQA) with references plays an important role in optimizing and evaluating computer vision tasks. Traditional methods assume that all pixels of the reference and test images are fully aligned. Such Aligned-Reference IQA (AR-IQA) approaches fail to address many real-world problems with various geometric deformations between the two images. Although significant effort has been made to attack Geometrically-Disparate-Reference IQA (GDR-IQA) problem, it has been addressed in a task-dependent fashion, for example, by dedicated designs for image super-resolution and retargeting, or by assuming the geometric distortions to be small that can be countered by translation-robust filters or by explicit image registrations. Here we rethink this problem and propose a unified, non-training-based Deep Structural Similarity (DeepSSIM) approach to address the above problems in a single framework, which assesses structural similarity of deep features in a simple but efficient way and uses an attention calibration strategy to alleviate attention deviation. The proposed method, without application-specific design, achieves state-of-the-art performance on AR-IQA datasets and meanwhile shows strong robustness to various GDR-IQA test cases. Interestingly, our test also shows the effectiveness of DeepSSIM as an optimization tool for training image super-resolution, enhancement and restoration, implying an even wider generalizability. 1 Copyright © 2024, The Authors. All rights reserved.

关键词： Restoration