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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Bing Li Weifeng Pan Jinhu Lü State Key Laboratory Software Engineering and School Computer and Complex Network Research Center Wuhan University of China Wuhan China State Key Laboratory Software Engineering Wuhan University of China Wuhan China School Electrical Computer Engineering RMIT University Melbourne Australia Acad. Mathematics System Science Chinese Academy and Sciences Beijing China

software systems represent one of the most complex man-made systems. In this paper, we analyze the evolution of Object-Oriented (OO) software using complex network theory from a multi-granularity perspective. First, the software net works are constructed for a multi-version software system at different levels of granularity. Then, some parameters used in complex network theory are introduced to study the topological characteristics of these software networks. By investigating the parameters' values in consecutive software networks, we have a better understanding about software evolution. A case study on an open source OO project, Azureus, is conducted as an example to illustrate our approach. It uncovers some underlying dynamic characteristics of OO systems. These results provide a different dimension to our understanding of software system dynamics and also are very useful for the design and development of OO software systems.

关键词： Logic gates Communities US Department of Defense

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Conformal mesh parameterization using discrete Calabi flow

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computer AIDED GEOMETRIC DESIGN 2018年 63卷 96-108页

作者： Zhao, Hui Li, Xuan Ge, Huabin Lei, Na Zhang, Min Wang, Xiaoling Gu, Xianfeng [a]Tsinghua University China [b]Beijing Advanced Innovation Center for Imaging Technology Capital Normal University China [c]Department of Mathematics Beijing Jiaotong University China [d]DUT-RU International School of Information and Software Engineering Dalian University of Technology China [e]Computer Science Department State University of New York at Stony Brook USA [f]Brigham and Women's Hospital Harvard Medical School USA [g]Center of Mathematical Sciences and Applications Harvard University USA [h]Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province China [i]School of Mechanical Engineering University of Science and Technology Beijing China

In this paper, we introduce discrete Calabi flow to the graphics research community and present a novel conformal mesh parameterization algorithm. Calabi energy has a succinct and explicit format. Its corresponding flow is conformal and convergent under certain conditions. Our method is based on the Calabi energy and Calabi flow with solid theoretical and mathematical base. We demonstrate our approach on dozens of models and compare it with other related flow based methods, such as the well-known Ricci flow and conformal equivalence of triangle meshes (CETM). Our experiments show that the performance of our algorithm is comparably the same with other methods. The discrete Calabi flow in our method provides another perspective on conformal flow and conformal parameterization. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Calabi flow Mesh parameterization Conformal mapping

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Imperceptible and Reliable Adversarial Attack 1

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4th International Conference on Frontiers in Cyber Security, FCS 2021

作者： Zhang, Jiawei Wang, Jinwei Luo, Xiangyang Ma, Bin Xiong, Naixue School of Computer and Software Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology Nanjing210044 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhenzhou450001 China Shandong Provincial Key Laboratory of Computer Networks and Qilu University of Technology Jinan250353 China Department of Computer Science and Mathematics Sul Ross State University AlpineTX79830 United States

ISBN: (数字)9789811905230

ISBN: (纸本)9789811905223

Deep neural networks are vulnerable to adversarial examples, which can fool classifiers by adding small perturbations. Various adversarial attack methods have been proposed in the past several years, and most of them add the perturbation in a "sparse" or "global" way. Since the number of pixels perturbed by the "sparse" method and the perturbation intensity of each pixel added by the "global" method are both small, the adversarial property can be destroyed easily. Finally, it makes the adversarial attack and the adversarial training based on these samples unreliable. To address this issue, we present an "pixel-wise" method which is somewhere in between the "sparse" or "global" way. First, the perception of human eyes to the error of different image regions is different. Second, image processing methods have different effects on the different areas of the image. Based on these two considerations, we propose an imperceptible and reliable adversarial attack method, which projects the perturbation to the different areas differently. Extensive experiments demonstrate our method can preserve the attack ability while maintaining good view quality. More importantly, the proposed projection can be combined with existing attack methods to generate a stronger generation algorithm which improves the robustness of adversarial examples. Based on the proposed method, the reliability of adversarial attacks can be greatly improved. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Pixels

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Self-Supervised Teaching and Learning of Representations on Graphs 23

Self-Supervised Teaching and Learning of Representations on ...

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2023 World Wide Web Conference, WWW 2023

作者： Wan, Liangtian Fu, Zhenqiang Sun, Lu Wang, Xianpeng Xu, Gang Yan, Xiaoran Xia, Feng Key Laboratory for Ubiquitous Network Service Software of Liaoning Province School of Software Dalian University of Technology Dalian China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian China State Key Laboratory of Marine Resource Utilization in South China Sea School of Information and Communication Engineering Hainan University Haikou China State Key Laboratory of Millimeter Waves School of Information Science and Engineering Southeast University Nanjing China Research Center of Big Data Intelligence Research Institute of Artificial Intelligence Zhejiang Lab Hangzhou China School of Computing Technologies Rmit University Melbourne Australia

ISBN: (纸本)9781450394161

Recent years have witnessed significant advances in graph contrastive learning (GCL), while most GCL models use graph neural networks as encoders based on supervised learning. In this work, we propose a novel graph learning model called GraphTL, which explores self-supervised teaching and learning of representations on graphs. One critical objective of GCL is to retain original graph information. For this purpose, we design an encoder based on the idea of unsupervised dimensionality reduction of locally linear embedding (LLE). Specifically, we map one iteration of the LLE to one layer of the network. To guide the encoder to better retain the original graph information, we propose an unbalanced contrastive model consisting of two views, which are the learning view and the teaching view, respectively. Furthermore, we consider the nodes that are identical in muti-views as positive node pairs, and design the node similarity scorer so that the model can select positive samples of a target node. Extensive experiments have been conducted over multiple datasets to evaluate the performance of GraphTL in comparison with baseline models. Results demonstrate that GraphTL can reduce distances between similar nodes while preserving network topological and feature information, yielding better performance in node classification. © 2023 ACM.

关键词： Classification (of information)

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Accountable authority identity-based encryption with public traceability

Accountable authority identity-based encryption with public ...

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Cryptographers' Track at the RSA Conference 2013, CT-RSA 2013

作者： Lai, Junzuo Deng, Robert H. Zhao, Yunlei Weng, Jian School of Information Systems Singapore Management University Singapore Singapore Software School Fudan University China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences China Department of Computer Science Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security Jinan University China Shanghai Key Laboratory of Integrate Administration Technologies for Information Security China

ISBN: (纸本)9783642360947

At Crypto'07, Goyal introduced the notion of accountable authority identity-based encryption (A-IBE) in order to mitigate the inherent key escrow problem in identity-based encryption, and proposed two concrete constructions. In an A-IBE system, if the private key generator (PKG) distributes a decryption key or produces an unauthorized decryption box for a user maliciously, it runs the risk of being caught and sued in the court of law with the help of a tracing algorithm. Subsequent efforts focused on constructions of A-IBE schemes with enhanced security. In these A-IBE constructions, the tracing algorithm needs to take a user's decryption key as input. If the user lost his key or is deliberately uncooperative in court, then we cannot implicate the PKG or the user. An interesting open problem left by Goyal et al. at CCS'08 is to consider the possibility of tracing a decryption box using only a public tracing key, or with the assistance of a tracing authority. In this paper, we address this problem positively. We first extend the original model of A-IBE to accommodate public traceability, and then propose an A-IBE scheme in the new model. To the best of our knowledge, the proposed scheme is the first A-IBE with public traceability. © 2013 Springer-Verlag.

关键词： Accountable Authority Identity Based Encryption Public Traceability

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An Experimental Study of Unsupervised Rank Aggregation Methods in World University Rankings

An Experimental Study of Unsupervised Rank Aggregation Metho...

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Intelligent Education and Intelligent research (IEIR), International Conference on

作者： Shiwei Feng Qi Deng Siyi Wang Lin Song Chao Liang Hubei Key Laboratory of Multimedia and Network Communication Engineering National Engineering Research Center for Multimedia Software (NERCMS) School of Computer Science Wuhan University

Recently, more and more college ranking systems are receiving attention due to the demand and necessity of higher education and college ranking system is a key topic in the field of social choice. However, these rankings have different evaluation criteria that lead to confusion for decision-makers. To address this issue, a simple and practical approach is to aggregate these ranking systems from different sources. In this paper, we conduct an experimental study on aggregation of world university ranking. Specifically, we first classify unsupervised RA methods. Then, we compare the aggregation effects of 28 unsupervised RA methods on five public university rankings.

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Efficient public key cryptosystem resilient to key leakage chosen ciphertext attacks

Efficient public key cryptosystem resilient to key leakage c...

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Cryptographers' Track at the RSA Conference 2013, CT-RSA 2013

作者： Liu, Shengli Weng, Jian Zhao, Yunlei Dept. of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Department of Computer Science Emergency Technology Research Center of Risk Evaluation and Prewarning on Public Network Security Jinan University China Software School Fudan University Shanghai 201203 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai China

ISBN: (纸本)9783642360947

Leakage-resilient public key encryption (PKE) schemes are designed to resist "memory attacks", i.e., the adversary recovers the cryptographic key in the memory adaptively, but subject to constraint that the total amount of leaked information about the key is bounded by some parameter λ. Among all the IND-CCA2 leakage-resilient PKE proposals, the leakage-resilient version of the Cramer-Shoup cryptosystem (CS-PKE), referred to as the KL-CS-PKE scheme proposed by Naor and Segev in Crypto09, is the most practical one. But, the key leakage parameter λ and plaintext length m of KL-CS-PKE are subject to λ + m ≤ log q - ω(log κ), where κ is security parameter and q is the prime order of the group on which the scheme is based. Such a dependence between λ and m is undesirable. For example, when λ (resp., m) approaches to log q, m (resp., λ) approaches to 0. In this paper, we designed a new variant of CS-PKE that is resilient to key leakage chosen ciphertext attacks. Our proposal is λ ≤ log q - ω(log κ) leakage-resilient, and the leakage parameter λ is independent of the plaintext space that has the constant size q (exactly the same as that in CS-PKE). The performance of our proposal is almost as efficient as the original CS-PKE. As far as we know, this is the first leakage-resilient CS-type cryptosystem whose plaintext length is independent of the key leakage parameter, and is also the most efficient IND-CCA2 PKE scheme resilient to up to log q - ω(log κ) leakage. © 2013 Springer-Verlag.

关键词： Public key cryptography

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NNVISR: Bring Neural network Video Interpolation and Super Resolution into Video Processing Framework

arXiv

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arXiv 2023年

作者： Tong, Yuan Hu, Mengshun Wang, Zheng National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering School of Computer Science Wuhan University China

We present NNVISR - an open-source filter plugin for the VapourSynth1 video processing framework, which facilitates the application of neural networks for various kinds of video enhancing tasks, including denoising, super resolution, interpolation, and spatio-temporal super-resolution. NNVISR fills the gap between video enhancement neural networks and video processing pipelines, by accepting any network that enhances a group of frames, and handling all other network agnostic details during video processing. NNVISR is publicly released at https://***/tongyuantongyu/vs-NNVISR. © 2023, CC BY-SA.

关键词： Interpolation

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whu-nercms at trecvid2021:instance search task

arXiv

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arXiv 2021年

作者： Niu, Yanrui Yang, Jingyao Lu, Ankang Huang, Baojin Zhang, Yue Huang, Ji Wen, Shishi Xu, Dongshu Liang, Chao Wang, Zhongyuan Chen, Jun Hubei Key Laboratory of Multimedia and Network Communication Engineering National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University China

We will make a brief introduction of the experimental methods and results of the WHU-NERCMS in the TRECVID2021 in the paper. This year we participate in the automatic and interactive tasks of Instance Search (INS). For the automatic task, the retrieval target is divided into two parts, person retrieval, and action retrieval. We adopt a two-stage method including face detection and face recognition for person retrieval and two kinds of action detection methods consisting of three frame-based human-object interaction detection methods and two video-based general action detection methods for action retrieval. After that, the person retrieval results and action retrieval results are fused to initialize the result ranking lists. In addition, we make attempts to use complementary methods to further improve search performance. For interactive tasks, we test two different interaction strategies on the fusion results. We submit 4 runs for automatic and interactive tasks respectively. The introduction of each run is shown in Table 1. The official evaluations show that the proposed strategies rank 1st in both automatic and interactive tracks. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

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Who, What and Where: Composite-semantic Instance Search for Story Videos

Who, What and Where: Composite-semantic Instance Search for ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jiahao Guo Chao Liang Zhongyuan Wang National Engineering Research Center for Multimedia Software (NERCMS) Hubei Key Laboratory of Multimedia and Network Communication Engineering School of Computer Science Wuhan University

This paper studies Who-What-Where (3W) composite-semantic video instance search (INS) problem, which aims to find a specific person doing a queried action in a particular place. Mainstream approaches adopt a complete decomposition strategy, which divides a composite-semantic query into multiple single-semantic queries. However, due to the lack of necessary correlation analysis among constituent semantics, these methods cannot always generate identity-matching and semantics-consistent 3W INS results. To address the above challenges, we propose a partial decomposition scheme with action as the link. Specifically, we selectively split the 3W INS as person-action INS and action-location INS. The former ensures the retrieved person and action share the same identity by modeling their relative spatial positions at the frame level, while the latter improves the semantic consistency between action and location with a cross-semantic attention mechanism at the shot level. Particularly, we build a large-scale 3W INS dataset, containing over 470k video shots, on basis of NIST TRECVID 2016-2021 INS tasks and verify the effectiveness of the proposed method with both quantitative and qualitative experiments.

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