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Improved cryptanalysis of the VMPC stream cipher

Journal of Computational Information Systems 2012年第2期8卷 831-838页

作者： Li, Shunbo Hu, Yupu Zhao, Yongbin Wang, Yan Department of Mathematics Xidian University Xi'an 710071 China Key Lab. of Computer Networks and Information Security Ministry of Education Xidian University Xi'an 710071 China School of Science Xi'an University of Architecture and Technology Xi'an 710055 China

VMPC is a modified RC4 stream cipher proposed in FSE 2004, which is designed especially to resist distinguishing attacks. In this paper, we present a heuristic distinguishing attack against VMPC. By finding the weakness in the first two words of a keystream with two effective assumptions, we build a distinguisher and get a considerable bias. This attack only requires about 234.02 output bytes to distinguish VMPC from truly random sequence with success probability 0.9545. Thereby, this technique is further used to the Tsunoo's method and improve his results by a factor of about 24. 1553-9105/Copyright © 2012 Binary Information Press.

关键词： Cryptography

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Test case generation method at register transfer level

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of computer-Aided Design and computer Graphics 2005年第9期17卷 2053-2060页

作者： Gao, Yan Shen, Li Computer Architecture Research Lab. Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

As a primary part of design verification and chip testing in the life cycle of Integrated Circuits (ICs), test generation receives increasing attention. By the application of branch coverage, bit-function coverage and statement-observability coverage measures, this paper introduces a high level test case generation method based on Control Flow Graph/Data Flow Graph (CFG/DFG) model, and then puts forward a feasible test generation method at Register Transfer Level (RTL). Experimental results demonstrate that the method can produce shorter test sequence in less time, and obtains an equal or a little less stuck-at fault coverage at gate-level. Furthermore, the method provides sufficient flexibility due to the adoption of test case technique.

关键词： Automatic test pattern generation (ATPG) Integrated circuits (ICs) Register transfer level (RTL) Test case

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Edge AIBench: Towards comprehensive end-to-end edge computing benchmarking

arXiv

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arXiv 2019年

作者： Hao, Tianshu Huang, Yunyou Wen, Xu Gao, Wanling Zhang, Fan Zheng, Chen Wang, Lei Ye, Hainan Hwang, Kai Ren, Zujie Zhan, Jianfeng State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences BenchCouncil [International Open Benchmarking Council Beijing Academy of Frontier Sciences and Technology Chinese University of Hongkong at Shenzhen Zhejiang Lab

In edge computing scenarios, the distribution of data and collaboration of workloads on different layers are serious concerns for performance, privacy, and security issues. So for edge computing benchmarking, we must take an end-to-end view, considering all three layers: client-side devices, edge computing layer, and cloud servers. Unfortunately, the previous work ignores this most important point. This paper presents the BenchCouncil’s coordinated effort on edge AI benchmarks, named Edge AIBench. In total, Edge AIBench models four typical application scenarios: ICU Patient Monitor, Surveillance Camera, Smart Home, and Autonomous Vehicle with the focus on data distribution and workload collaboration on three layers. Edge AIBench is a part of the open-source AIBench project, publicly available from http://***/AIBench/***. We also build an edge computing testbed with a federated learning framework to resolve performance, privacy, and security issues. Copyright © 2019, The Authors. All rights reserved.

关键词： Edge computing

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Energy-efficient NTT Design with One-bank SRAM and 2-D PE Array

Energy-efficient NTT Design with One-bank SRAM and 2-D PE Ar...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Jianan Mu Huajie Tan Jiawen Wu Haotian Lu Chip-Hong Chang Shuai Chen Shengwen Liang Jing Ye Huawei Li Xiaowei Li State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences CASTEST Tianjin University Nanyang Technological University Rock-Solid Security Lab Fiberhome

In Number Theoretic Transform (NTT) operation, more than half of the active energy consumption stems from memory accesses. Here, we propose a generalized design method to improve the energy efficiency of NTT operation by considering the effect of processing element (PE) geometry and memory organization on the data flow between PEs and memory. To decrease the number of data bits that are required to be accessed from the memory, a two-dimensional (2-D) PE array architecture is used. A pair of ping-pong buffers are proposed to transposed swap the coefficients to enable a single bank of memory to be used with the 2-D PE array to reduce the average memory bit access energy without compromising the throughput. Our experimental results show that this design method can produce NTT accelerators with up to 69.8% saving in average energy consumption compared with the existing designs based on multi-bank SRAM and one-bank SRAM with one-dimensional PE array with the same number of PEs and total memory size.

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Hierarchically characterizing CUDA program behavior

Hierarchically characterizing CUDA program behavior

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IEEE International Workshop/Symposium on Workload Characterization

作者： Zhibin Yu Hai Jin Nilanjan Goswami Tao Li Lizy K. John Service Computing Technologies and System Lab/Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China Intelligent Design of Efficient Architecture Lab University of Florida Gainesville FL USA Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

CUDA has become a very popular programming paradigm in parallel computing area. However, very little work has been done for characterizing CUDA kernels. In this work, we measure the thread level performance, collect the basic block level characteristics, and glean the instruction level properties for about 35 programs from CUDA SDK, Parboil, and Rodinia benchmark suites. In addition, we define basic block vectors, synchronization vectors and thread similarity matrix to capture the characteristics of CUDA programs efficiently. We find that CUDA programs have some unique characteristics at each level compared to sequential programs.

关键词： Graphics processing unit Vectors Kernel Instruction sets Programming USA Councils Educational institutions

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ecUWB: A Energy-Centric Communication Scheme for Unstable WiFi Based Backscatter Systems : (Invited Paper)

ecUWB: A Energy-Centric Communication Scheme for Unstable Wi...

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International Conference on computer Communications and Networks (ICCCN)

作者： Yue Xu Jingwen Zhang Hao Zhou Xiaoyan Wang Zhi Liu Yusheng Ji LINKE Lab School of Computer Science and Technology Univ. of Science and Technology of China China College of Engineering Ibaraki University Japan Department of Mathematical and Systems Engineering Shizuoka University Japan Information Systems Architecture Research Division National Institute of Informatics Japan

ISBN: (数字)9781728166070

ISBN: (纸本)9781728166087

By integrating both energy harvesting and backscatter communication technologies, so-called `battery-free tag' emerges as a promising solution to the energy related issues in IoT. However, such tags present new challenges due to the unstable energy supply and excitation signals, which are critical to realize successful backscatter communications. In this paper, we present a novel system, denoted as ecUWB, which enables robust communication for battery-free tags where unstable WiFi signals act as the unified source for both energy supply and excitation signals. At tag side, we propose a charging-transmission division scheme to achieve better signal utilization, and introduce a re-transmission mechanism for possible excitation signal interruption. At receiver side, we implement a simply method which is based on DBSCAN (Density-Based Spatial Clustering of Applications with Noise) to predict the uncontrollable signals, and propose an energy-centric tag scheduling method according to the tag energy estimation results. Extensive experiments are carried out on customized tags and NI USRP platform. The results show that ecUWB outperforms the existing ones in terms of performance and efficiency under the unstable WiFi signals.

关键词： Wireless fidelity Backscatter Energy harvesting Receivers Systems architecture Power supplies Modulation

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HIORE: Leveraging High-order Interactions for Unified Entity Relation Extraction

arXiv

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arXiv 2023年

作者： Wang, Yijun Sun, Changzhi Wu, Yuanbin Li, Lei Yan, Junchi Zhou, Hao WeChat Technical Architecture Department Tencent Inc China Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Computer Science and Technology East China Normal University China ByteDance AI Lab China University of California Santa Barbara United States

Entity relation extraction consists of two sub-tasks: entity recognition and relation extraction. Existing methods either tackle these two tasks separately or unify them with word-byword interactions. In this paper, we propose HIORE, a new method for unified entity relation extraction. The key insight is to leverage the high-order interactions, i.e., the complex association among word pairs, which contains richer information than the first-order word-by-word interactions. For this purpose, we first devise a W-shape DNN (WNet) to capture coarse-level high-order connections. Then, we build a heuristic high-order graph and further calibrate the representations with a graph neural network (GNN). Experiments on three benchmarks (ACE04, ACE05, SciERC) show that HIORE achieves the state-of-the-art performance on relation extraction and an improvement of 1.1 ∼ 1.8 F1 points over the prior best unified model. Copyright © 2023, The Authors. All rights reserved.

关键词： Graph neural networks

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3-D Functional Brain Network Classification using Convolutional Neural Networks

3-D Functional Brain Network Classification using Convolutio...

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International Symposium on Biomedical Imaging

作者： Dehua Ren Yu Zhao Hanbo Chen Qinglin Dong Jinglei Lv Tianming Liu College of Computer Science and Information Engineering Tianjin University of Science and Technology 300222 China Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center the University of Georgia Athens 30605 USA Queensland Institute of Medical Research (QIMR) Berghofer Herston Australia

ISBN: (纸本)9781509011735

Several recent studies have shown that dictionary learning and sparse representation can effectively reconstruct hundreds of interacting functional brain networks simultaneously from whole-brain fMRI data. However, accurate classification and recognition of those hundreds of functional networks from an individual or a population of many subjects is still a challenging and open problem due to the intrinsic variability of functional networks and other noise sources. To tackle this problem, this paper presents an effective deep learning framework to train convolutional neural networks from a large dataset of hundreds of thousands of available brain network volume maps, which was then applied on testing samples for network classification and recognition. We effectively applied computer-labeled data as training set so the whole process can be automated. Experimental results showed that the proposed method is quite robust in handling noisy patterns in the dataset, which suggests that our work offers a new computational framework for modeling functional connectomes from fMRI big data in the future.

关键词： deep learning 3D convolutional neural networks functional brain networks classification

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Safety Guaranteed Power-Delivered-to-Load Maximization for Magnetic Wireless Power Transfer

Safety Guaranteed Power-Delivered-to-Load Maximization for M...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Wangqiu Zhou Xinyu Wang Hao Zhou Shenyao Jiang Zhi Liu Yusheng Ji LINKE Lab School of Computer Science and Technology University of Science and Technology of China CAS Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Deqing Alpha Innovation Institute Huzhou China Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Electromagnetic radiation (EMR) safety has always been a critical reason for hindering the development of magneticenabled wireless power transfer technology. People focus on the actual received energy at charging devices while paying attention to their health. Thus, we study this significant problem in this paper, and propose a universal safety guaranteed power-delivered-to-load (PDL) maximization scheme (called SafeGuard). Technically, we first utilize the off-the-shelf electromagnetic simulator to perform the EMR distribution analysis to ensure the universality of the method. Then, we innovatively introduce the concept of multiple importance sampling for achieving efficient EMR safety constraint extraction. Finally, we treat the proposed optimization problem as an optimal boundary point search problem from the perspective of space geometry, and devise a brand-new grid-based multi-constraint parallel processing algorithm to efficiently solve it. We implement a system prototype for SafeGuard, and conduct extensive experiments to evaluate it. The results indicate that our SafeGuard can obviously improve the achieved PDL by up to 1.75× compared with the state-of-the-art baseline while guaranteeing EMR safety. Furthermore, SafeGuard can accelerate the solution process by 29.12× compared with the traditional numerical method to satisfy the fast optimization requirement of wireless charging systems.

关键词： Performance evaluation Monte Carlo methods System performance Inductive charging Prototypes Wireless power transfer Parallel processing

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A modal parameters identification method based on recurrent neural networks

A modal parameters identification method based on recurrent ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jing Xu Qing-Chun Meng Dong-Ming Zhou Yan Ge Department of Civil Engineering Qingdao Institute of Architecture and Engineering Qingdao China Department of Computer Science Ocean University of China Qingdao China State Key Lab of Intelligent Technology and Systems Tsinghua University Beijing Beijing China

ISBN: (纸本)0780384032

This paper presents a recurrent neural network-based approach for modal parameters identification of structure-unknown systems. The proposed approach involves two steps. The first step is to build a recurrent neural network to map the complex nonlinear relation between the excitations and responses of the structure-unknown system by off-line learning. The second step is to propose a procedure to determine the modal parameters of the system from the trained neural networks. The dynamic characteristics of the structure are directly evaluated from the weighting matrices of the trained recurrent neural network. Furthermore, an illustrative example demonstrates the feasibility of using the proposed method to identify modal parameters of structure-unknown systems. The method proposed can be used to research on fault diagnosis of engineer structure.

关键词： Parameter estimation Recurrent neural networks Neural networks MIMO Artificial neural networks Network topology Cybernetics Nonlinear dynamical systems Nonlinear equations Frequency domain analysis

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