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15th International Conference on Information Security and Cryptology, Inscrypt 2019

作者： Lu, Tingting Li, Jiangtao Zhang, Lei Lam, Kwok-Yan Shanghai Key Laboratory of Trustworthy Computing Software Engineering Institute East China Normal University Shanghai China State Key Laboratory of Cryptology P.O. Box 5159 Beijing China Shanghai Institute for Advanced Communication and Data Science Shanghai China School of Computer Engineering and Science Shanghai University Shanghai China Nanyang Technological University Singapore Singapore

ISBN: (纸本)9783030429201

Group signature is a useful cryptographic primitive that allows a message to be signed by a user on behalf of a group which is managed by some trusted authority, namely the group manager. However, group signature schemes typically place a disturbingly high level of trust on the group manager, which has become a major deployment issue in cyber applications where there is no centralized trust management. In this paper, we investigate mechanisms that aim to achieve a balance between anonymity and accountability in group signatures by decentralizing the operation of tracing the signer. We propose a practical group signature scheme with decentralized tracing. When comparing with a similar result by Benjumea et al. (FC 2008), our proposal has the advantage of a shorter signature size. © 2020, Springer Nature Switzerland AG.

关键词： Managers

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ZeroSpy: Exploring Software Inefficiency with Redundant Zeros 20

ZeroSpy: Exploring Software Inefficiency with Redundant Zero...

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Supercomputing Conference

作者： Xin You Hailong Yang Zhongzhi Luan Depei Qian Xu Liu Beihang University China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China North Carolina State University USA

ISBN: (数字)9781728199986

ISBN: (纸本)9781728199993

Redundant zeros cause inefficiencies in which the zero values are loaded and computed repeatedly, resulting in unnecessary memory traffic and identity computation that waste memory bandwidth and CPU resources. optimizing compilers is difficult in eliminating these zero-related inefficiencies due to limitations in static analysis. Hardware approaches, in contrast, optimize inefficiencies without code modification, but are not widely adopted in commodity processors. In this paper, we propose ZeroSpy - a fine-grained profiler to identify redundant zeros caused by both inappropriate use of data structures and useless computation. ZeroSpy also provides intuitive optimization guidance by revealing the locations where the redundant zeros happen in source lines and calling contexts. The experimental results demonstrate ZeroSpy is capable of identifying redundant zeros in programs that have been highly optimized for years. Based on the optimization guidance revealed by ZeroSpy, we can achieve significant speedups after eliminating redundant zeros.

关键词： Optimizing compilers Memory management Redundancy Static analysis Production Software Optimization

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Superconductivity in pressurized trilayer La4Ni3O10-δ single crystals

arXiv

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arXiv 2023年

作者： Zhu, Yinghao Peng, Di Zhang, Enkang Pan, Bingying Chen, Xu Chen, Lixing Ren, Huifen Liu, Feiyang Hao, Yiqing Li, Nana Xing, Zhenfang Lan, Fujun Han, Jiyuan Wang, Junjie Jia, Donghan Wo, Hongliang Gu, Yiqing Gu, Yimeng Ji, Li Wang, Wenbin Gou, Huiyang Shen, Yao Ying, Tianping Chen, Xiaolong Yang, Wenge Cao, Huibo Zheng, Changlin Zeng, Qiaoshi Guo, Jiangang Zhao, Jun State Key Laboratory of Surface Physics Department of Physics Fudan University Shanghai200433 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Shanghai201203 China College of Physics and Optoelectronic Engineering Ocean University of China Shandong Qingdao266100 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Neutron Scattering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Center for High Pressure Science and Technology Advanced Research Shanghai201203 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China Center for High Pressure Science and Technology Advanced Research Beijing100094 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China Institute of Nanoelectronics and Quantum Computing Fudan University Shanghai200433 China Shanghai Branch Hefei National Laboratory Shanghai201315 China

The pursuit of discovering new high-temperature superconductors that diverge from the copper-based paradigm1-3 carries profound implications for elucidating mechanisms behind superconductivity and may also enable new applications4-8. Here, our investigation reveals that application of pressure effectively suppresses the spin and charge order in trilayer nickelate La4Ni3O10-δ single crystals, leading to the emergence of superconductivity with a maximum critical temperature (Tc) of around 30 K at 69.0 GPa. The DC susceptibility measurements confirm a substantial diamagnetic response below Tc, indicating the presence of bulk superconductivity with a volume fraction exceeding 80%. In the normal state, we observe a "strange metal" behavior, characterized by a linear temperature-dependent resistance extending up to 300 K. Furthermore, the layer-dependent superconductivity observed hints at a unique interlayer coupling mechanism specific to nickelates, setting them apart from cuprates in this regard. Our findings provide crucial insights into the fundamental mechanisms underpinning superconductivity, while also introducing a new material platform to explore the intricate interplay between the spin/charge order, flat band structures, interlayer coupling, strange metal behavior and high-temperature superconductivity. © 2023, CC BY-NC-ND.

关键词： Single crystals

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High-capacity and Robust Image Watermarking Algorithm

Research Square

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Research Square 2021年

作者： Liu, Zheng Li, Xi-Yan Zhou, Qing-Lei Sun, Hanqing Lian, Weimin Wang, Guizhi School of Information Engineering Henan University of Animal Husbandry and Economy Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China School of Information Science and Technology HaiNan Normal University Haikou China School of Information Engineering Zhengzhou University Zhengzhou China

With the development of internet, digital media can be manipulated, reproduced, and distributed conveniently over networks. However, illegal copy, transmission and distribution of digital media become an important security issue. In this paper, we propose a high-capacity and robustness method based on discrete wavelet transforms(DWT) and optimal discrete cosine transforms(DCT). We present two approaches, they are: DWT-ODCT(high-capacity and robust image watermarking algorithm based on DWT and optimal DCT), and(P-DWT-ODCT) high-capacity and robust image watermarking algorithm based on DWT and optimal DCT by watermark preprocessing. The watermark image is preprocessed by halftone and quad tree techniques, and the position information about the content is extracted as the actual embedded value. The cover image is transformed by DWT and optimal DCT, which provides high imperceptibility and the least image distortion. Watermark bits are not directly inserted into the frequency coefficient, but embedded by modifying the coefficient according to some rules. With this method, regardless of the approach used, our study are higher capacity and robustness than the existing schemes. The watermark extraction produces high image quality after a variety of attacks. © 2021, CC BY.

关键词： Discrete wavelet transforms

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Retraction Note: A robust image steganography based on the concatenated error correction encoder and discrete cosine transform coefficients

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Journal of Ambient Intelligence and Humanized computing 2024年第1期15卷 245-245页

作者： Bao, Zhenkun Guo, Yanqing Li, Xiaolong Zhang, Yi Xu, Meng Luo, Xiangyang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Zhengzhou Science and Technology Institute Zhengzhou China School of Information and Communication Engineering Dalian University of Technology Dalian China Institute of Information Science Beijing Jiaotong University Beijing China

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A survey of coverage-guided greybox fuzzing with deep neural models

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Information and Software Technology 2025年 186卷

作者： Qiu, Junyang Jiang, Yupeng Miao, Yuantian Luo, Wei Pan, Lei Zheng, Xi State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214123 China School of Computing Macquarie University Sydney 2109 NSW Australia School of Information and Physical Sciences University of Newcastle Newcastle 2308 NSW Australia School of Information Technology Deakin University Melbourne 3125 VIC Australia

Coverage-guided greybox fuzzing (CGF) has emerged as a powerful technique for software vulnerability detection, yet traditional techniques often struggle with the increasing complexity of modern software systems and the vastness of input spaces. Deep neural networks (DNNs) have begun to fundamentally transform CGF by addressing these limitations through automated feature extraction, adaptive input generation, and intelligent path prioritization. However, despite these advancements, critical gaps persist in understanding the state-of-the-art landscape. Existing studies often lack rigorous benchmarks to evaluate scalability and generalizability, fail to address the interpretability of neural-guided decisions, and overlook the integration of emerging paradigms such as large language models (LLMs) and neurosymbolic reasoning. This survey systematically bridges these gaps by providing a comprehensive taxonomy of DNN-driven CGF techniques, analyzing their strengths and limitations across key fuzzing stages—seed generation, selection, and mutation. We find that although DNNs have significantly improved fuzzing efficiency, challenges such as semantically invalid seeds, high computational overhead, and limited cross-domain adaptability remain unresolved. Most importantly, we identify two transformative directions with the potential to redefine CGF: (1) LLM-powered fuzzing, which combines generative AI with domain-specific fine-tuning to produce context-aware inputs;and (2) neurosymbolic integration, which merges the precision of symbolic execution with the scalability of neural networks to tackle path explosion. By synthesizing these insights, this survey not only clarifies the state-of-the-art but also outlines a roadmap for developing robust, explainable, and widely applicable intelligent fuzzers. The future of CGF lies in hybrid models that integrate data-driven learning with formal methods, paving the way for autonomous vulnerability discovery in an era of increasingly c

关键词： Code coverage Deep learning Greybox fuzzing Large language models Software vulnerability

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Optimization on the symplectic Stiefel manifold: SR decomposition-based retraction and applications

arXiv

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arXiv 2022年

作者： Gao, Bin Son, Nguyen Thanh Stykel, Tatjana State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Institut für Mathematik Centre for Advanced Analytics and Predictive Sciences Universität Augsburg Universitätsstraße 12a Augsburg86159 Germany Thai Nguyen University of Sciences Thai Nguyen24118 Viet Nam

Numerous problems in optics, quantum physics, stability analysis, and control of dynamical systems can be brought to an optimization problem with matrix variable subjected to the symplecticity constraint. As this constraint nicely forms a so-called symplectic Stiefel manifold, Riemannian optimization is preferred, because one can borrow ideas from unconstrained optimization methods after preparing necessary geometric tools. Retraction is arguably the most important one which decides the way iterates are updated given a search direction. Two retractions have been constructed so far: one relies on the Cayley transform and the other is designed using quasi-geodesic curves. In this paper, we propose a new retraction which is based on an SR matrix decomposition. We prove that its domain contains the open unit ball which is essential in proving the global convergence of the associated gradient-based optimization algorithm. Moreover, we consider three applications—symplectic target matrix problem, symplectic eigenvalue computation, and symplectic model reduction of Hamiltonian systems—with various examples. The extensive numerical comparisons reveal the strengths of the proposed optimization *** Codes 15A23, 32C25, 65F15, 65F99, 65K05, 65P10, 90C30 © 2022, CC BY.

关键词： Dynamical systems

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PET Denoising and Uncertainty Estimation Based on NVAE Model

PET Denoising and Uncertainty Estimation Based on NVAE Model

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2021 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Cui, Jianan Xie, Yutong Gong, Kuang Kim, Kyungsang Yang, Jaewon Larson, Peder Hope, Thomas Behr, Spencer Seo, Youngho Liu, Huafeng Li, Quanzheng Zhejiang University State Key Laboratory of Modern Optical Instrumentation College of Optical Science and Engineering Hangzhou China Massachusetts General Hospital Harvard Medical School Center for Advanced Medical Computing and Analysis BostonMA United States Peking University Beijing China Massachusetts General Hospital Harvard Medical School Gordon Center for Medical Imaging BostonMA United States Department of Radiology and Biomedical Imaging CA94107 United States

ISBN: (纸本)9781665421133

The structure of the deep neural network is constantly changing, and its performance is constantly breaking through. Recently, a new network, Nouveau variational auto-encoder (NVAE), has been proposed and gained great attention. In addition to the ability to generate high-quality images, the more important nature of NVAE is that it can generate a distribution that makes it possible to measure the uncertainty. In this work, we proposed to use NVAE for PET image denoising and estimate the uncertainty from both training data and model at the same time. 2.5D training based on 28 patients was performed and quantification based on 7 real patient data showed that NVAE has a good performance for PET denoising, which outperforms the Unet. The variance of 1000 sample output was calculated to show the uncertainty map. © 2021 IEEE.

关键词： Deep neural networks

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System architecture for high-performance permissioned blockchains

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Frontiers of Computer Science 2019年第6期13卷 1151-1165页

作者： Libo FENG Hui ZHANG Wei-Tek TSAI Simeng SUN State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China Digital Society&Blockchain Laboratory School of Computer ScienceBeihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100191China School of Computing Informatics and Decision Systems EngineeringArizona State UniversityTempeUSA

Blockchain(BC),as an emerging distributed database technology with advanced security and reliability,has attracted much attention from experts who devoted to efinance,intellectual property protection,the internet of things(IoT)and so ***,the inefficient transaction processing speed,which hinders the BC’s widespread,has not been well tackled *** this paper,we propose a novel architecture,called Dual-Channel Parallel Broadcast model(DCPB),which could address such a problem to a greater extent by using three methods which are dual communication channels,parallel pipeline processing and block broadcast *** the dual-channel model,one channel processes transactions,and the other engages in the execution of *** parallel pipeline processing allows the system to operate *** block generation strategy improves the efficiency and speed of *** experiments have been applied to BeihangChain,a simplified prototype for BC system,illustrates that its transaction processing speed could be improved to 16K transaction per second which could well support many real-world scenarios such as BC-based energy trading system and Micro-film copyright trading system in CCTV.

关键词： blockchain concurrency performance dualchannel model parallel pipeline consensus algorithm

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Optimizing the Memory Hierarchy by Compositing Automatic Transformations on Computations and Data

Optimizing the Memory Hierarchy by Compositing Automatic Tra...

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IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Jie Zhao Peng Di State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Huawei Technologies Co. Ltd Beijing China

ISBN: (数字)9781728173832

ISBN: (纸本)9781728173849

Optimizing compilers exploit the memory hierarchy using loop tiling and fusion, but these two transformations usually interfere with each other due to the oversight of transformations on data in memories. We present a novel composition of loop tiling and fusion in this paper. Unlike existing tiling-after-fusion algorithms that only transform computation spaces, our approach first applies rectangular/parallelogram tiling to live-out computation spaces for fitting the memory hierarchy, followed by the computation of the memory footprints required by each tile. The upwards exposed data extracted from the memory footprints are used to determine the tile shapes of intermediate computation spaces, allowing the construction of arbitrary tile shapes. Finally, our technique implements a post-tiling fusion strategy for maximizing data locality without losing tilability or parallelism of live-out computation spaces, thereby enabling storage reduction and reuse, and optimizing the memory hierarchy. We demonstrate that our approach can achieve superior performance on both CPU and GPU architectures over the state of the art by experimenting on 11 benchmarks extracted from numerous domains including neural networks, image processing, sparse matrix computation and linear algebra. Also, the results of the ResNet-50 model on an AI accelerator show that our approach can obtain 16% performance improvement.

关键词： Shape Tiles Memory management Transforms Benchmark testing Sparse matrices Optimization

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