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arXiv 2021年

作者： Schrom, Edward Kinzig, Ann Forrest, Stephanie Graham, Andrea L. Levin, Simon A. Bergstrom, Carl T. Castillo-Chavez, Carlos Collins, James P. De Boer, Rob J. Doupé, Adam Ensafi, Roya Feldman, Stuart Grenfell, Bryan T. Halderman, J. Alex Huijben, Silvie Maley, Carlo Moses, Melanie Perelson, Alan S. Perrings, Charles Plotkin, Joshua Rexford, Jennifer Tiwari, Mohit Department of Ecology and Evolutionary Biology Princeton University 106A Guyot Hall PrincetonNJ08544 United States School of Life Sciences Arizona State University TempeAZ85287 United States Julie Ann Wrigley Global Institute of Sustainability Arizona State University TempeAZ85287 United States Biodesign Center for Biocomputation Security and Society Arizona State University TempeAZ85287 United States School of Computing Informatics and Decision Sciences Engineering Arizona State University TempeAZ85287 United States Santa Fe Institute Santa FeNM87501 United States Department of Biology University of Washington SeattleWA98195 United States Arizona State University TempeAZ85287 United States Theoretical Biology and Bioinformatics Utrecht University Utrecht3584 CH Netherlands Center for Cybersecurity and Digital Forensics Global Security Initiative Arizona State University TempeAZ85287 United States Department of Electrical Engineering and Computer Science Computer Science and Engineering Division University of Michigan Ann ArborMI48109 United States Schmidt Futures New YorkNY10011 United States Princeton School of Public and International Affairs Princeton University PrincetonNJ08544 United States Center for Computer Security and Society University of Michigan Ann ArborMI48109 United States Center for Evolution and Medicine School of Life Sciences Arizona State University TempeAZ85287 United States Arizona Cancer Evolution Center Arizona State University TempeAZ85287 United States Department of Computer Science University of New Mexico AlbuquerqueNM87131 United States University of New Mexico Department of Computer Science AlbuquerqueNM87131 United States Department of Biology University of New Mexico AlbuquerqueNM87131 United States Theoretical Biology and Biophysics Group Los Alamos National Laboratory Los AlamosNM87545 United States Department of Biology University of Pennsylvania PhiladelphiaPA19104 Unite

We explore the commonalities between methods for assuring the security of computer systems (cybersecurity) and the mechanisms that have evolved through natural selection to protect vertebrates against pathogens, and how insights derived from studying the evolution of natural defenses can inform the design of more effective cybersecurity systems. More generally, security challenges are crucial for the maintenance of a wide range of complex adaptive systems, including financial systems, and again lessons learned from the study of the evolution of natural defenses can provide guidance for the protection of such *** Codes A.0. Copyright © 2021, The Authors. All rights reserved.

关键词： Cybersecurity

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Deep Learning for Password Guessing and Password Strength Evaluation, A Survey

Deep Learning for Password Guessing and Password Strength Ev...

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IEEE International Conference on Trust, security and Privacy in computing and Communications (TrustCom)

作者： Tao Zhang Zelei Cheng Yi Qin Qiang Li Lin Shi Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis Guangxi University for Nationalities Nanning China Department of Computer and Information Technology Purdue University West Lafayette USA PLA Information Engineering University Zhengzhou China Henan Key Laboratory of Network Cryptography Technology Zhengzhou China Cloud Computing and Big Data Research Institute China Academy of Information and Communications Technology Beijing China

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

Text passwords are the most widely used authentication methods and will also be used in the future. Text passwords can be regarded as meaningful strings, and deep learning methods have an advantage of text processing. LSTM, RNN, GAN and other deep learning models have been using in password guessing and password strength measurements. In the paper, we make a survey on state-of-the-art deep learning methods for password guessing and password strength evaluation, including password pattern extraction, candidate password generation and password strength measurement. Compared with traditional methods, neural networks based methods can achieve better results and performance.

关键词： Deep learning Training Transfer learning security Gallium nitride Password Text processing

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Tongue image segmentation via color decomposition and thresholding

Tongue image segmentation via color decomposition and thresh...

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作者： Li, Zuoyong Yu, Zhaochai Liu, Weixia Xu, Yong Zhang, Daoqiang Cheng, Yong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China The Fujian College's Research Base of Humanities and Social Science for Internet Innovation Research Center Minjiang University Fuzhou350121 China Straits Institute Minjiang University Fuzhou350121 China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen518055 China Department of Computer Science and Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

Tongue image segmentation is a crucial step in developing an automatic tongue diagnosis system. After exploring characteristics of image thresholding in different color spaces, we propose a simple and effective tongue image segmentation method. Specifically, the proposed method first extracts an initial tongue body region by performing image thresholding on the transformed hue component in HSI (Hue, Saturation, and Intensity) color space. Then, one of two image thresholding results on the red component of an original tongue image is adaptively selected to find the gap region between the tongue body root and the upper lip. Finally, the initial tongue body region is refined by removing fake object regions such as the upper lip to obtain final tongue image segmentation result. Experimental results on a tongue image dataset containing 200 subjects demonstrate the effectiveness of the proposed method. © 2018 John Wiley & Sons, Ltd.

关键词： Image segmentation

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A generic transformation to enable optimal repair in MDS codes for distributed storage systems

A generic transformation to enable optimal repair in MDS cod...

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作者： Li, Jie Tang, Xiaohu Tian, Chao Information Security and National Computing Grid Laboratory Southwest Jiaotong University Chengdu610031 China Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and Statistics Hubei University Wuhan430062 China Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States Department of Electrical and Computer Engineering Texas A and M University College StationTX77843 United States

We propose a generic transformation that can convert any nonbinary (n=k{+}r,k)maximum distance separable (MDS) code into another (n,k) MDS code over the same field such that: 1) some arbitrarily chosen r nodes have the optimal repair bandwidth and the optimal rebuilding access;2) for the remaining k nodes, the normalized repair bandwidth and the normalized rebuilding access (over the file size) are preserved;and 3) the sub-packetization level is increased only by a factor of r. Two immediate applications of this generic transformation are then presented. The first application is that we can transform any nonbinary MDS code with the optimal repair bandwidth or the optimal rebuilding access for the systematic nodes only, into a new MDS code which possesses the corresponding repair optimality for all nodes. The second application is that by applying the transformation multiple times, any nonbinary (n,k) scalar MDS code can be converted into an (n,k) MDS code with the optimal repair bandwidth and the optimal rebuilding access for all nodes, or only a subset of nodes, whose sub-packetization level is also optimal. © 1963-2012 IEEE.

关键词： Repair

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iSplit LBI: Individualized partial ranking with ties via split LBI

arXiv

引用

arXiv 2019年

作者： Xu, Qianqian Sun, Xinwei Yang, Zhiyong Cao, Xiaochun Huang, Qingming Yao, Yuan Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Microsoft Research Asia State Key Laboratory of Information Security Institute of Information Engineering CAS School of Cyber Security University of Chinese Academy of Sciences School of Computer Science and Tech. University of Chinese Academy of Sciences Key Laboratory of Big Data Mining and Knowledge Management CAS Peng Cheng Laboratory Department of Mathematics Hong Kong University of Science and Technology Hong Kong

Due to the inherent uncertainty of data, the problem of predicting partial ranking from pairwise comparison data with ties has attracted increasing interest in recent years. However, in real-world scenarios, different individuals often hold distinct preferences. It might be misleading to merely look at a global partial ranking while ignoring personal diversity. In this paper, instead of learning a global ranking which is agreed with the consensus, we pursue the tie-aware partial ranking from an individualized perspective. Particularly, we formulate a unified framework which not only can be used for individualized partial ranking prediction, but also be helpful for abnormal user selection. This is realized by a variable splitting-based algorithm called iSplitLBI. Specifically, our algorithm generates a sequence of estimations with a regularization path, where both the hyperparameters and model parameters are updated. At each step of the path, the parameters can be decomposed into three orthogonal parts, namely, abnormal signals, personalized signals and random noise. The abnormal signals can serve the purpose of abnormal user selection, while the abnormal signals and personalized signals together are mainly responsible for individual partial ranking prediction. Extensive experiments on simulated and real-world datasets demonstrate that our new approach significantly outperforms state-of-the-art alternatives. The code is now availiable at https://***/qianqianxu010/ NeurIPS2019-iSplitLBI. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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Coherence-based automated essay scoring using self-attention 17th

Coherence-based automated essay scoring using self-attention

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17th China National Conference on Computational Linguistics, CCL 2018 and 6th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2018

作者： Li, Xia Chen, Minping Nie, Jianyun Liu, Zhenxing Feng, Ziheng Cai, Yingdan Key Laboratory of Language Engineering and Computing Guangdong University of Foreign Studies Guangzhou China School of Information Science and Technology/School of Cyber Security Guangdong University of Foreign Studies Guangzhou China Department of Computer Science and Operations Research University of Montreal Montreal Canada

ISBN: (纸本)9783030017156

Automated essay scoring aims to score an essay automatically without any human assistance. Traditional methods heavily rely on manual feature engineering, making it expensive to extract the features. Some recent studies used neural-network-based scoring models to avoid feature engineering. Most of them used CNN or RNN to learn the representation of the essay. Although these models can cope with relationships between words within a short distance, they are limited in capturing long-distance relationships across sentences. In particular, it is difficult to assess the coherence of the essay, which is an essential criterion in essay scoring. In this paper, we use self-attention to capture useful long-distance relationships between words so as to estimate a coherence score. We tested our model on two datasets (ASAP and a new non-native speaker dataset). In both cases, our model outperforms the existing state-of-the-art models. © Springer Nature Switzerland AG 2018.

关键词： Automation

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Energy-efficient cooperative secure transmission in multi-UAV enabled wireless networks

arXiv

引用

arXiv 2019年

作者： Hua, Meng Wang, Yi Wu, Qingqing Dai, Haibo Huang, Yongming Yang, Luxi School of Information Science and Engineering Southeast University Nanjing210096 China School of Electronics and Communication Engineering Zhengzhou University of Aeronautics Zhengzhou450046 China Physical Layer Security Laboratory National Digital Switching System Engineering and Technological Research Center Zhengzhou450002 China Department of Electrical and Computer Engineering National University of Singapore Singapore School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210003 China

This paper investigates a multiple unmanned aerial vehicles (UAVs) enabled cooperative secure transmission scheme in the presence of multiple potential eavesdroppers. Specifically, multiple source UAVs (SUAVs) send confidential information to multiple legitimate ground users and in the meantime multiple jamming UAVs (JUAVs) cooperatively transmit interference signals to multiple eavesdroppers in order to improve the legitimate users' achievable secrecy rate. By taking into account the limited energy budget of UAV, our goal is to maximize the system secrecy energy efficiency (SEE), namely the achievable secrecy rate per energy consumption unit, by jointly optimizing the UAV trajectory, transmit power and user scheduling under the constraints of UAV mobility as well as the maximum transmit power. The resulting optimization problem is shown to be a non-convex and mixed-integer fractional optimization problem, which is challenging to solve. We decompose the original problem into three sub-problems, and then an efficient iterative algorithm is proposed by leveraging the block coordinate descent and Dinkelbach method in combination with successive convex approximation techniques. Simulation results show that the proposed scheme outperforms the other benchmarks significantly in terms of the system SEE. Copyright © 2019, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Performance Analysis of ZCC-Optical-CDMA over SMF for Fiber-To-The-Home Access Network

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Journal of Physics: Conference Series 2020年第2期1529卷

作者： Alaan Ghazi S. A. Aljunid Alaa Fareed Syed Zulkarnain Syed Idrus C. B. M Rashidi Marwa albayaty Aras Al-dawoodi Ahmed M. Fakhrudeen School of Human Development & Techno Communication University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Technical Engineering Alkitab University Iraq Internet Research Laboratory School of Computing University Utara Malaysia Malaysia Computer Science Department College of Computer Science and Information Technology Kirkuk University Iraq Networks Department College of Computer Science and Information Technology Kirkuk University Iraq

To provide a sustainable fiber-to-the-home (FTTH), several multiplexing techniques have been developed for this purpose. The correlation features are the main obstacle behind the network performance limitation, which imposes to a high level of multiple access interference. However, the development of multiplexing techniques helps to overcome these limitations, such as optical-code division multiple access (Optical-CDMA). Optical-CDMA is considered as one of the most powerful solutions for FTTH. This paper aims to enhance FTTH network performance by applying Zero cross-correlation code (ZCC) with Optical-CDMA with maximum link single-mode fiber. In the simulation, the system performance is demonstrated in terms of bit error rate, Q-Factor and eye diagram measurements.

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A chaotic artificial bee colony algorithm based on lévy search

A chaotic artificial bee colony algorithm based on lévy sea...

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作者： Lin, Shijie Dong, Chen Wang, Zhiqiang Guo, Wenzhong Chen, Zhenyi Ye, Yin College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Key Laboratory of Information Security of Network Systems Fuzhou350116 China Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China Department of Electrical Engineering University of South Florida TampaFL33620 United States

A Lévy search strategy based chaotic artificial bee colony algorithm (LABC) is proposed in this paper. The chaotic sequence, global optimal mechanism and Lévy flight mechanism were introduced respectively into the initialization, the employed bee search and the onlooker bee search. The experiments show that the proposed algorithm performed better in convergence speed, global search ability and optimization accuracy than other improved ABC. Copyright © 2018 The Institute of Electronics, Information and Communication Engineers.

关键词： Evolutionary algorithms

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Fast stochastic ordinal embedding with variance reduction and adaptive step size

arXiv

引用

arXiv 2019年

作者： Ma, Ke Zeng, Jinshan Xiong, Jiechao Xu, Qianqian Cao, Xiaochun Liu, Wei Yao, Yuan School of Computer Science and Technology University of Chinese Academy of Sciences Beijing100049 China Artificial Intelligence Research Center Peng Cheng Laboratory Shenzhen518055 China School of Computer Information Engineering Jiangxi Normal University NanchangJiangxi330022 China Tencent AI Lab Shenzhen Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen518055 China School of Cyber Security University of Chinese Academy of Sciences Beijing100049 China Department of Mathematics and by courtesy Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

—Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years. Most of the existing methods are based on semi-definite programming (SDP), which is generally time-consuming and degrades the scalability, especially confronting large-scale data. To overcome this challenge, we propose a stochastic algorithm called SVRG-SBB, which has the following features: i) achieving good scalability via dropping positive semi-definite (PSD) constraints as serving a fast algorithm, i.e., stochastic variance reduced gradient (SVRG) method, and ii) adaptive learning via introducing a new, adaptive step size called the stabilized Barzilai-Borwein (SBB) step size. Theoretically, under some natural assumptions, we show the O(T1 ) rate of convergence to a stationary point of the proposed algorithm, where T is the number of total iterations. Under the further Polyak-Lojasiewicz assumption, we can show the global linear convergence (i.e., exponentially fast converging to a global optimum) of the proposed algorithm. Numerous simulations and real-world data experiments are conducted to show the effectiveness of the proposed algorithm by comparing with the state-of-the-art methods, notably, much lower computational cost with good prediction performance. Copyright © 2019, The Authors. All rights reserved.

关键词： Stochastic systems

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