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arXiv 2024年

作者： Liu, Daizong Tao, Yunbo Zhou, Pan Hu, Wei Wangxuan Institute of Computer Technology Peking University No. 128 Zhongguancun North Street Beijing China The Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

With the maturity of depth sensors in various 3D safety-critical applications, 3D point cloud models have been shown to be vulnerable to adversarial attacks. Almost all existing 3D attackers simply follow the white-box or black-box setting to iteratively update coordinate perturbations based on back-propagated or estimated gradients. However, these methods are hard to deploy in real-world scenarios (no model details are provided) as they severely rely on parameters or output logits of victim models. To this end, we propose point cloud attacks from a more practical setting, i.e., hard-label black-box attack, in which attackers can only access the prediction label of 3D input. We introduce a novel 3D attack method based on a new spectrum-aware decision boundary algorithm to generate high-quality adversarial samples. In particular, we first construct a class-aware model decision boundary, by developing a learnable spectrum-fusion strategy to adaptively fuse point clouds of different classes in the spectral domain, aiming to craft their intermediate samples without distorting the original geometry. Then, we devise an iterative coordinate-spectrum optimization method with curvature-aware boundary search to move the intermediate sample along the decision boundary for generating adversarial point clouds with trivial perturbations. Experiments demonstrate that our attack competitively outperforms existing white/black-box attackers in terms of attack performance and adversary quality. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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ImagineNet: Target Speaker Extraction with Intermittent Visual Cue Through Embedding Inpainting

ImagineNet: Target Speaker Extraction with Intermittent Visu...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zexu Pan Wupeng Wang Marvin Borsdorf Haizhou Li Institute of Data Science National University of Singapore (NUS) Singapore Department of Electrical and Computer Engineering NUS Singapore Machine Listening Lab University of Bremen Germany Shenzhen Research Institute of Big Data School of Data Science The Chinese University of Hong Kong Shenzhen China

The speaker extraction technique seeks to single out the voice of a target speaker from the interfering voices in a speech mixture. Typically an auxiliary reference of the target speaker is used to form voluntary attention. Either a pre-recorded utterance or a synchronized lip movement in a video clip can serve as the auxiliary reference. The use of visual cue is not only feasible, but also effective due to its noise robustness, and becoming popular. However, it is difficult to guarantee that such parallel visual cue is always available in real-world applications where visual occlusion or intermittent communication can occur. In this paper, we study the audio-visual speaker extraction algorithms with intermittent visual cue. We propose a joint speaker extraction and visual embedding inpainting framework to explore the mutual benefits. To encourage the interaction between the two tasks, they are performed alternately with an interlacing structure and optimized jointly. We also propose two types of visual inpainting losses and study our proposed method with two types of popularly used visual embeddings. The experimental results show that we outperform the baseline in terms of signal quality, perceptual quality, and intelligibility.

关键词： Visualization Lips Design methodology Signal processing algorithms Signal processing Noise robustness Synchronization

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TPE for JPEG images with Dynamic M-ary Decomposition and Adaptive Threshold Constraints

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Ma, Yakun Chai, Xiuli Long, Guoqiang Gan, Zhihua Zhang, Yushu Henan University School of Artificial Intelligence Henan Engineering Research Center for Industrial Internet of Things Zhengzhou450046 China Henan University School of Software Intelligent Data Processing Engineering Research Center of Henan Province Institute of Intelligent Network System Kaifeng475004 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China

Traditional JPEG image encryption that prioritizes solely confidentiality fails to account for the pressing usability requirements of cloud-based environments, thus boosting the boom in thumbnail-preserving encryption (TPE) to balance image privacy and usability. However, existing TPE schemes for JPEG images face numerous challenges, such as insufficient security, inability to achieve lossless decryption, and high file extension. To address these challenges, we propose a TPE scheme based on dynamic M-ary decomposition and adaptive threshold constraints (TPE-MDTC). First, the valid ranges of quantized DC coefficients for JPEG images are determined. Then, a sum-preserving encryption method for quantized DC coefficients with compliance threshold constraints is designed using the bit-plane permutation to preserve thumbnails with high accuracy. Next, the introduction of dynamic M-ary decomposition effectively changes bit statistical characteristics preserved by bit-plane permutation, enhancing the ciphertext security. Finally, a quantized AC encryption method with RV (Run/Value) pair global permutation is proposed, effectively modifying the unit block features, thereby significantly improving the security and attack resistance of encrypted images. Experimental results show that the proposed TPE-MDTC scheme can reconstruct the original JPEG images without loss, and the generated ciphertext images exhibit significant advantages over previous schemes regarding file extension and security. © 1991-2012 IEEE.

关键词： Ciphertext

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Understanding and Detecting Privacy Leakage Vulnerabilities in Hyperledger Fabric Chaincodes

Understanding and Detecting Privacy Leakage Vulnerabilities ...

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International Symposium on Software Reliability engineering (ISSRE)

作者： Ziming Chen Yue Li Jianbo Gao Jiashuo Zhang Ke Wang Jianbin Hu Zhi Guan Zhong Chen School of Computer Science Peking University Beijing China College of Computer Science and Technology Taiyuan University of Technology Taiyuan China Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing China Peking University Chongqing Research Institute of Big Data Chongqing China National Engineering Research Center for Software Engineering Peking University Beijing China

ISBN: (数字)9798350353884

ISBN: (纸本)9798350353891

The application on a blockchain cannot maintain secrecy because its data is replicated across all peers in the network. To remedy this problem, Hyperledger Fabric introduces private data collection (PDC) into its smart contract (i.e. chaincode) to facilitate applications that require privacy. However, recent studies have revealed that PDC is too complex for chaincode developers to fully understand and use correctly, leading to privacy leaks vulnerabilities. In this paper, we present an empirical study on the prevalence of PDC misuse in chaincodes by extracting privacy leakage cases from StackOverflow posts and Hyperledger Fabric repositories on GitHub. Subsequently, we systematically categorize the misuse of PDC into three categories of vulnerabilities resulting in the leakage of private data and provide formal definitions for them. Furthermore, we develop PDChecker, an automated security analysis framework for identifying the privacy and security vulnerabilities in Fabric chaincodes. We evaluated PDChecker on 956 real-world chaincodes applying PDC and found that 67.78% of them contain at least one privacy leakage vulnerability. In addition, PDChecker uncovered 10 zero-day vulnerabilities documented by the China National Vulnerability database.

关键词： Privacy data privacy Distributed ledger databases Smart contracts Fabrics Blockchains Software reliability Security Software development management

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A Provably Secure and Lightweight Access Control Protocol for EI-Based Vehicle to Grid Environment

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IEEE Internet of Things Journal 2023年第18期10卷 16650-16657页

作者： Shamshad, Salman Mahmood, Khalid Shamshad, Usman Hussain, Ibrar Hussain, Shafiq Das, Ashok Kumar The University of Lahore Department of Software Engineering Lahore54590 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan Riphah International University Riphah School of Computing and Innovation Lahore54000 Pakistan University of Sahiwal Department of Computer Science Sahiwal57000 Pakistan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India Old Dominion University Virginia Modeling Analysis and Simulation Center SuffolkVA23435 United States

The energy Internet (EI) presents a novel paradigm for renewable energy distribution that utilizes communication and computing technologies to revolutionize the conventional intelligent transportation systems (ITSs) and power grid into a structure that provides assistance to open innovation. The EI offers sustainable and bidirectional transmission for the improvement and analysis of energy convention among electric vehicles (EVs) and service providers. To ensure efficient, reliable, and secure operation, EI must be safe from security attacks. Therefore, efficient and secure key negotiation is a significant issue for the EI-based Vehicle-to-Grid (V2G) architecture. Thus, to ensure the system's security, we have devised a robust scheme to facilitate a secure key agreement between the entities involved for the secure and efficient renewable energy distribution for the EI-based energy vehicles in V2G. The devised scheme's robustness is solicited through the widely accepted formal random or real (RoR) model. In addition, the informal security analysis is conducted on the devised scheme, which is evident that the designed scheme achieves all the required security features of EI-based ITS. Moreover, the performance evaluation results endorse that the designed scheme achieves the desired security and minimizes the communication, computation, and energy overhead by 29.33%, 27.94%, and 28.08% in comparison to the existing competitive schemes. © 2014 IEEE.

关键词： Vehicle-to-grid

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data Allocation for Approximate Gradient Coding in Edge Networks

Data Allocation for Approximate Gradient Coding in Edge Netw...

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IEEE International Symposium on Information Theory

作者： Haojun Li Yi Chen Kenneth W. Shum Chi Wan Sung School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen Research Institute of Big Data Department of Electrical Engineering City University of Hong Kong Hong Kong SAR

To leverage the computing power in an edge network, one can divide a machine learning task into several subtasks and assign the subtasks to several computing devices to complete. Under master-worker architecture, the master divides and distributes the data to several workers. In each iteration, the master asks the workers to compute some function of the local data stored in the workers. For example, in gradient-based learning, this function can be the partial gradient function. Since the workers have different computing resources, the speed of the distributed learning is hindered by some workers with long latency, called the stragglers. Gradient coding solves the problem of stragglers by allowing the master to recover the desired feedback information in the presence of s stragglers. If the total number of stragglers is n, the master can just wait for the n−s fastest workers. In this paper we consider the problem of data allocation so that the gradient vector can be approximated obtained by the master node with small error. A block repetition scheme is proved to be the optimal data allocation scheme if we want to minimize the average recovery error.

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Optimized Dynamic Watermarking for Audio DNNs with Adaptive Embedding and Boundary Sampling

Optimized Dynamic Watermarking for Audio DNNs with Adaptive ...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hao Fei Hewang Nie Siqi Sun Songfeng Lu Ting Luo Ling Qian Dunbo Cai Zhiguo Huang Runqing Zhang 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 Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China China Mobile (Suzhou) Software Technology Company Limited Suzhou China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The intensified concerns arising from the widespread adoption of deep learning have led to increased scrutiny of intellectual property protection in DNN models. Existing audio watermarking techniques, predominantly based on traditional signal processing methods, struggle to balance robustness, imperceptibility, and defense resistance in the face of evolving adversarial attacks. These limitations underscore the urgent need for more effective watermarking solutions in the audio domain. In this paper, we propose a dynamic audio watermarking framework that introduces an optimization-based approach to attach robust and adaptable triggers at arbitrary positions within audio signals, and innovatively integrates boundary sample selection driven by forgetting events and an adaptive watermark trigger embedding technique based on the SNR. Comprehensive experimental results reveal that our scheme preserves high model performance while maintaining remarkable stealthiness and robustness, offering a secure and reliable solution for safeguarding intellectual property in the audio domain and advancing the field of DNN watermarking.

关键词： Resistance Deep learning Adaptation models Watermarking Intellectual property Signal processing Robustness Speech processing Protection Signal to noise ratio

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Active-IRS-Aided Wireless Communication: Fundamentals, Designs and Open Issues

arXiv

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arXiv 2023年

作者： Kang, Zhenyu You, Changsheng Zhang, Rui National University of Singapore Singapore Southern University of Science and Technology China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China

intelligent reflecting surface (IRS) has emerged as a promising technology to realize smart radio environment for future wireless communication systems. Existing works in this line of research have mainly considered the conventional passive IRS that reflects wireless signals without power amplification, while in this article, we give an overview of a new type of IRS, called active IRS, which enables simultaneous signal reflection and amplification, thus significantly extending the signal coverage of passive IRS. We first present the fundamentals of active IRS, including its hardware architecture, signal and channel models, as well as practical constraints, in comparison with those of passive IRS. Then, we discuss new considerations and open issues in designing active-IRS-aided wireless communications, such as the reflection optimization, channel estimation, and deployment for active IRS, as well as its integrated design with passive IRS. Finally, numerical results are provided to show the potential performance gains of active IRS as compared to passive IRS and traditional active relay. © 2023, CC BY.

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Connector-S: A Survey of Connectors in Multi-modal Large Language Models

arXiv

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arXiv 2025年

作者： Zhu, Xun Zhang, Zheng Chen, Xi Shi, Yiming Li, Miao Wu, Ji Department of Electronic Engineering Tsinghua University China College of AI Tsinghua University China Beijing National Research Center for Information Science and Technology China Center for Big Data and Clinical Research Institute for Precision Medicine Tsinghua University China

With the rapid advancements in multi-modal large language models (MLLMs), connectors play a pivotal role in bridging diverse modalities and enhancing model performance. However, the design and evolution of connectors have not been comprehensively analyzed, leaving gaps in understanding how these components function and hindering the development of more powerful connectors. In this survey, we systematically review the current progress of connectors in MLLMs and present a structured taxonomy that categorizes connectors into atomic operations (mapping, compression, mixture of experts) and holistic designs (multi-layer, multi-encoder, multi-modal scenarios), highlighting their technical contributions and advancements. Furthermore, we discuss several promising research frontiers and challenges, including high-resolution input, dynamic compression, guide information selection, combination strategy, and interpretability. This survey is intended to serve as a foundational reference and a clear roadmap for researchers, providing valuable insights into the design and optimization of next-generation connectors to enhance the performance and adaptability of MLLMs. Copyright © 2025, The Authors. All rights reserved.

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TPE-H2MWD:an exact thumbnail preserving encryption scheme with hidden Markov model and weighted diffusion

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Frontiers of Information Technology & Electronic engineering 2023年第8期24卷 1169-1180页

作者： Xiuli CHAI Xiuhui CHEN Yakun MA Fang ZUO Zhihua GAN Yushu ZHANG School of Artificial Intelligence Henan Engineering Research Center for Industrial Internet of ThingsHenan UniversityZhengzhou450046China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001China School of Software Intelligent Data Processing Engineering Research Center of Henan ProvinceInstitute of Intelligent Network SystemHenan UniversityKaifeng475004China College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing211106China

With the substantial increase in image transmission,the demand for image security is ***-like images can be obtained by conventional encryption schemes,and although the security of the images can be guaranteed,the noise-like images cannot be directly previewed and *** on the rank-then-encipher method,some researchers have designed a three-pixel exact thumbnail preserving encryption(TPE2)scheme,which can be applied to balance the security and availability of images,but this scheme has low encryption *** this paper,we introduce an efficient exact thumbnail preserving encryption ***,blocking and bit-plane decomposition operations are performed on the plaintext *** zigzag scrambling model is used to change the bit positions in the lower four bit ***,an operation is devised to permute the higher four bit planes,which is an extended application of the hidden Markov ***,according to the difference in bit weights in each bit plane,a bit-level weighted diffusion rule is established to generate an encrypted image and still maintain the same sum of pixels within the *** results show that the proposed scheme improves the encryption efficiency and can guarantee the availability of images while protecting their privacy.

关键词： Hidden Markov model Weighted diffusion Balance between usability and privacy Image encryption

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