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arXiv 2023年

作者： Huang, Huan Dai, Lipeng Zhang, Hongliang Zhang, Chongfu Tian, Zhongxing Cai, Yi Swindlehurst, A. Lee Han, Zhu The School of Electronic and Information Engineering Soochow University Suzhou215006 China The School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China The Center for Pervasive Communications and Computing University of California IrvineCA92697 United States The University of Houston HoustonTX77004 United States

Emerging intelligent reflective surfaces (IRSs) significantly improve system performance, but also pose a significant risk for physical layer security (PLS). Unlike the extensive research on legitimate IRS-enhanced communications, in this article we present an adversarial IRS-based fully-passive jammer (FPJ). We describe typical application scenarios for Disco IRS (DIRS)-based FPJ, where an illegitimate IRS with random, time-varying reflection properties acts like a "disco ball" to randomly change the propagation environment. We introduce the principles of DIRS-based FPJ and overview existing investigations of the technology, including a design example employing one-bit phase shifters. The DIRS-based FPJ can be implemented without either jamming power or channel state information (CSI) for the legitimate users (LUs). It does not suffer from the energy constraints of traditional active jammers, nor does it require any knowledge of the LU channels. In addition to the proposed jamming attack, we also propose an anti-jamming strategy that requires only statistical rather than instantaneous CSI. Furthermore, we present a data frame structure that enables the legitimate access point (AP) to estimate the DIRS-jammed channels’ statistical characteristics in the presence of the DIRS jamming. Typical cases are discussed to show the impact of the DIRS-based FPJ and the feasibility of the anti-jamming precoder (AJP). Moreover, we outline future research directions and challenges for the DIRS-based FPJ and its anti-jamming precoding to stimulate this line of research and pave the way for practical applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Channel state information

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Extracting hidden messages of MLSB steganography based on optimal stego subset

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Science China(Information Sciences) 2018年第11期61卷 241-243页

作者： Chunfang YANG Xiangyang LUO Jicang LU Fenlin LIU Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing

Dear editor,In recent years, steganalysis researchers have tried their best to extract the hidden messages. For example, under the condition of a known embedding position generator, Liu et al.[1] proposed a collision attack algorithm to recover the stego key of least significant bit (LSB) steganography. Fridrich et al.[2] proposed a chi-squared-test-based method to recover the stego key of LSB steganography for the case of an unknown carrier. Under the condition of multiple stego images embedded into the same positions, Ker [3] first proposed locating the

关键词： LSB

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Double JPEG Compression Detection Based on Markov Model 18th

Double JPEG Compression Detection Based on Markov Model

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18th International Workshop on Digital Forensics and Watermarking, IWDW 2019

作者： Wang, Jinwei Huang, Wei Luo, Xiangyang Shi, Yung-Qing Nanjing University of Information Science and Technology Nanjing210044 China Department of Computer and Software Nanjing University of Information Science and Technology NanjingJiangsu210044 China Shanxi Key Laboratory of Network and System Security Xidian University Xi’an710071 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China State Key Laboratory of Information Security Institute Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Electrical Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

ISBN: (纸本)9783030435745

In this paper, a feature based on the Markov model in quaternion discrete cosine transform (QDCT) domain is proposed for double JPEG compression detection. Firstly, a given JPEG image is extracted from blocked images to obtain amplitude and three angles (ψ, φ, and θ). Secondly, when extracting the Markov features, we process the transition probability matrix with the corresponding refinement. Our proposed refinement method not only reduces redundant features, but also makes the acquired features more efficient for detection. Finally, a support vector machine (SVM) is employed for NA-DJPEG compression detection. It is well known that detecting NA-DJPEG compressed images with (Formula Presented) is a challenging task, and when the images with small size (i.e., 64 × 64), the detection will be more difficult. The experimental result indicates that our method can still achieve a high classification accuracy in this case. © 2020, Springer Nature Switzerland AG.

关键词： Support vector machines

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Ultra-high-amplitude Peregrine solitons induced by helicoidal spin-orbit coupling

arXiv

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arXiv 2024年

作者： Ding, Cui-Cui Zhou, Qin Malomed, B.A. Research Group of Nonlinear Optical Science and Technology Research Center of Nonlinear Science School of Mathematical and Physical Sciences Wuhan Textile University Wuhan430200 China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile University Wuhan430200 China Department of Physical Electronics School of Electrical Engineering Faculty of Engineering The Center for Light-Matter University Tel Aviv University Tel Aviv Israel Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile

In the framework of the model of a spatially non-uniform Bose-Einstein condensate with helicoidal spin-orbit (SO) coupling, we find abnormal Peregrine solitons (PSs) on top of flat and periodic backgrounds, with ultra-high amplitudes. We explore the roles of the SO coupling strength and helicity pitch in the creation of these anomalously tall PSs and find that their amplitude, normalized to the background height, attains indefinitely large values. The investigation of the modulation instability (MI) in the same system demonstrates that these PSs exist in a range of relatively weak MI, maintaining the feasibility of their experimental observation. Copyright © 2024, The Authors. All rights reserved.

关键词： Solitons

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Observation of giant nonlinear valley Hall effect

arXiv

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arXiv 2025年

作者： He, Pan Zhang, Min Cao, Jin Li, Jingru Liu, Hao Zhai, Jinfeng Wang, Ruibo Xiao, Cong Yang, Shengyuan A. Shen, Jian State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Hefei National Laboratory Hefei230088 China Institute of Applied Physics and Materials Engineering Faculty of Science and Technology University of Macau China Fudan University Shanghai200433 China Department of Physics Fudan University Shanghai China Shanghai Research Center for Quantum Sciences Shanghai China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China

The valley Hall effect (VHE) holds great promise for valleytronic applications by leveraging the valley degree of freedom. To date, research on VHE has focused on its linear response to an applied current, leaving nonlinear valley responses undetected and nonlinear valleytronic devices undeveloped. Here, we report the experimental observation of a nonlinear VHE in a graphene-hBN moiré superlattice, evidenced by the generation of second-harmonic nonlocal voltages under AC currents. Remarkably, the nonlinear VHE has magnitude surpassing the linear VHE and is highly tunable via a gate voltage, which exhibits a pair of opposite peaks on the two sides of a Dirac gap. The nonlinear signal shows quadratic scaling with driving current and quartic scaling with local resistance, setting it apart from the linear counterpart. These experimental features are consistent with the theoretical picture of nonlocal transport mediated by nonlinear VHE and linear inverse VHE. We further reveal a nonlinear inverse VHE by observing the third- and fourth-harmonic nonlocal voltages. The nonlinear VHE provides a novel mechanism for valley manipulation and enables a novel valleytronic device—the valley rectifier—that converts AC charge current into DC valley current. Copyright © 2025, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

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Hypermultiplexed Integrated-Photonics-based Tensor Optical Processor

arXiv

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arXiv 2024年

作者： Ou, Shaoyuan Xue, Kaiwen Zhou, Lian Lee, Chun-Ho Sludds, Alexander Hamerly, Ryan Zhang, Ke Feng, Hanke Kopparapu, Reshma Zhong, Eric Wang, Cheng Englund, Dirk Yu, Mengjie Chen, Zaijun Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States Research Laboratory of Electronics MIT CambridgeMA02139 United States PHI Laboratories NTT Research Inc. 940 Stewart Drive SunnyvaleCA94085 United States Department of Electrical Engineering State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong Kowloon Hong Kong School of Advanced Computing University of Southern California Los AngelesCA90089 United States Opticore Inc. Los AngelesCA90007 United States

The escalating data volume and complexity resulting from the rapid expansion of artificial intelligence (AI), internet of things (IoT) and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware. Here we demonstrate a hypermultiplexed integrated-photonics-based tensor optical processor (HITOP) that can perform trillions of operations per second (TOPS) at the energy efficiency of 40 TOPS/W. Space-time-wavelength three-dimensional (3D) optical parallelism enables O(N2) operations per clock-cycle using O(N) modulator devices. The system is built with wafer-fabricated III/V micron-scale lasers and high-speed thin-film Lithium-Niobate electro-optics for encoding at 10s femtojoule/symbol. Lasing threshold incorporates analog inline rectifier (ReLu) nonlinearity for low-latency activation. The system scalability is verified with machine learning models of 405,000 parameters. A combination of high clockrates, energy-efficient processing and programmability unlocks the potential of light for large-scale AI accelerators in applications ranging from training of large AI models to real-time decision making in edge deployment. © 2024, CC0.

关键词： Photonic integrated circuits

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PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implicit Variables 2nd

PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implic...

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2nd International Conference on Applied Intelligence, ICAI 2024

作者： Liu, Yixin Fan, Yueqin Li, Zhipeng Zhang, Qinhu Big Data and Intelligent Computing Research Center Guangxi Academy of Science Nanning530007 China School of Mechanical Engineering Guangxi University Nanning530004 China Ningbo Institute of Digital Twin Eastern Institute of Technology Ningbo315201 China Institute for Regenerative Medicine Medical Innovation Center and State Key Laboratory of Cardiology School of Medicine Shanghai East Hospital Tongji University Shanghai200123 China College of Advanced Agricultural Sciences Zhejiang Agriculture and Forestry University Hangzhou311300 China

ISBN: (纸本)9789819619061

In the field of drug discovery and development, deep learning techniques have become a powerful tool to accelerate the discovery and development of new drugs. In the design and optimization of lead molecules, generative adversarial network and graph neural network are one of the prime techniques for accelerating research and development, because the former is based on the idea of two-player game to learn drug features to generate effective molecules, while the unstructured inputs of the latter are well-suited for the analysis of molecular data. Therefore, this study develops a new graph generative adversarial model, called PreZ-DGGAN, by inserting the graph neural network layer into the generative adversarial network. Within PreZ-DGGAN, the latent variable input of the generator is pre-learned by an improved graph variational autoencoder, which effectively avoids the mode collapse of the generative adversarial network, whereas the hidden layer of the discriminator is graph neural network layer, which is able to better learn the real molecules and judge the generated molecules as true or false. Experiments on two molecule datasets show that the molecules generated by PreZ-DGGAN have higher validity (100% on average) and uniqueness (91.5% on average), and the generated molecules are more diverse in structure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Representation Learning on Networks for Community Detection

Representation Learning on Networks for Community Detection

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International Conference on advanced Cloud and Big Data (CBD)

作者： Jingya Zhou Jianxi Fan Jin Wang Baolei Cheng School of Computer Science and Technology Soochow University Suzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Community detection is a fundamental problem in network analysis. In recent years, network representation learning has been leveraged to help the detection of potential communities. However, representation learning and community detection in these studies are usually optimized independently. In addition, they also have a strong assumption that the number of communities is prespecified before detection. To address those problems, we propose a joint representation learning and community detection (JRC) method. To allow the learned representations to be community-aware, JRC introduces two additional terms to the loss function for clustering. One is designed to getting node representations as close as possible to the exemplar of the community. Another is set up as a smoothness regularization to enforce the community properties of high cohesion and low coupling. Experimental results on multiple real-world network datasets show that JRC improves the quality of community detection and outperforms many competitive baselines.

关键词： Couplings Big Data

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Recurrent Neural Network Based Binary Code Vulnerability Detection

Recurrent Neural Network Based Binary Code Vulnerability Det...

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2019第二届算法、计算和人工智能国际会议

作者： Jianyun Zheng Jianmin Pang Xiaochuan Zhang Xin Zhou MingLiang Li Jun Wang State Key Laboratory of Mathematical Engineering and Advanced Computing

Vulnerability detection, especially vulnerability automatic detection, have long been an area of active research. Considering that RNN can model dependencies automatically, we propose a recurrent neural network(RNN) based method for binary code vulnerability detection. We collected correspond to 4 types of vulnerabilities, including CWE-134, CWE-191, CWE-401 and *** find which RNN is better in vulnerability detection, we evaluated 6 different RNNs, including SRNN, BSRNN, LSTM, BLSTM, GRU and BGRU. The results demonstrated that BSRNN is better than others in vulnerability detection.

关键词： Vulnerability detection Deep Learning Recurrent Neural Network

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A Framework for Multi-Variant Execution Environment

A Framework for Multi-Variant Execution Environment

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作者： Wang Junchao Liu Zhenwu Liu Hao Pang Jianmin State key Laboratory of Mathematical Engineering and Advanced Computing

Software diversity has been proven to be an effective approach to enhance system *** make the best of the advantage brought by software diversity,a multi-variant execution environment is ***,although some MVEEs have been proposed,most of them are either too simple or only focusing one aspect which limits their widely adoption in *** this paper we propose a framework for multi-variant execution environment to enhance the security of software *** framework addresses different aspects when implementing a MVEE and can help to make the best of software diversity to enhance the system's security.

关键词： A Framework for Multi-Variant Execution Environment Framework

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