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An energy efficient authentication scheme using chebyshev chaotic map for smart grid environment

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arXiv 2020年

作者： Zhang, Liping Zhu, Yue Ren, Wei Wang, Yinghan Xiong, Neal N. Zhang, Yan School of Computer Science China University of Geosciences Wuhan430074 China School of Computer Science China University of Geosciences Guangxi Key Laboratory of Cryptography and Information Security Guilin541004 China Key Laboratory of Network Assessment Technology CAS [Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Mathematics and Computer Science Northeastern State University OK74464 United States Department of Informatics University of Oslo Norway

Smart grid (SG) is an automatic electric power transmission network with bidirectional flows of both energy and information. As one of the important applications of smart grid, charging between electric vehicles has attracted much attentions. However, authentication between vehicle users and an aggregator may be vulnerable to various attacks due to the usage of wireless communications. Although several authentication schemes are proposed for smart grid environments with privacy protection, some of them still impose security issues such as anonymity absence. In addition, most of the existing authentication schemes have not thoroughly tackled the charging peak in their design, so these schemes cannot guarantee the requirement in terms of low energy consumption in smart grid environments. In order to reduce the computational costs yet preserve required security, the Chevyshev chaotic map based authentication schemes are proposed. However, the security requirements of Chebyshev polynomials bring a new challenge to the design of authentication schemes based on Chebyshev chaotic maps. To solve this issue, we propose a practical Chebyshev polynomial algorithm by using a binary exponentiation algorithm based on square matrix to achieve secure and efficient Chebyshev polynomial computation. We further apply the proposed algorithm to construct an energy-efficient authentication and key agreement scheme for smart grid environments. Compared with state-of-the-art schemes, the proposed authentication scheme effectively reduces the computational costs and communication costs by adopting the proposed Chebyshev polynomial algorithm. Furthermore, the ProVerif tool is employed to analyze the security of the proposed authentication scheme. Our experimental results justified that our proposed authentication scheme can outperform state-of-the-art schemes in terms of the computational overhead while achieving privacy protection. Copyright © 2020, The Authors. All rights reserved.

关键词： Authentication

Covid-19 public opinion and emotion monitoring system based on time series thermal new word mining

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arXiv 2020年

作者： Zhang, Yixian Chen, Jieren Liu, Boyi Yang, Yifan Li, Haocheng Zheng, Xinyi Chen, Xi Ren, Tenglong Xiong, Naixue School of Information and Communication Engineering Hainan University Haikou570100 China School of Computer Science and Cyberspace Security Hainan University Haikou570100 China University of Chinese Academy of Sciences Shenzhen518000 China National University of Defense Technology Changsha410000 China Department of Mathematics and Computer Science Northeastern State University TahlequahOK United States

With the spread and development of new epidemics, it is of great reference value to identify the changing trends of epidemics in public emotions. We designed and implemented the COVID-19 public opinion monitoring system based on time series thermal new word mining. A new word structure discovery scheme based on the timing explosion of network topics and a Chinese sentiment analysis method for the COVID-19 public opinion environment are proposed. Establish a "Scrapy-Redis-Bloomfilter" distributed crawler framework to collect data. The system can judge the positive and negative emotions of the reviewer based on the comments, and can also reflect the depth of the seven emotions such as Hopeful, Happy, and Depressed. Finally, we improved the sentiment discriminant model of this system and compared the sentiment discriminant error of COVID-19 related comments with the Jiagu deep learning model. The results show that our model has better generalization ability and smaller discriminant error. We designed a large data visualization screen, which can clearly show the trend of public emotions, the proportion of various emotion categories, keywords, hot topics, etc., and fully and intuitively reflect the development of public opinion. Copyright © 2020, The Authors. All rights reserved.

关键词： Monitoring

Deep Variational Network Toward Blind Image Restoration

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arXiv 2020年

作者： Yue, Zongsheng Yong, Hongwei Zhao, Qian Zhang, Lei Meng, Deyu Wong, Kwan-Yee K. The School of Mathematics and Statistics Xi’an Jiaotong University Xi’an China The Department of Computer Science The University of Hong Kong Hong Kong The Department of Computing The Hong Kong Polytechnic University Hong Kong The School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an China The Macau Institute of Systems Engineering Macau University of Science and Technology Taipa China

Blind image restoration (IR) is a common yet challenging problem in computer vision. Classical model-based methods and recent deep learning (DL)-based methods represent two different methodologies for this problem, each with its own merits and drawbacks. In this paper, we propose a novel blind image restoration method, aiming to integrate both the advantages of them. Specifically, we construct a general Bayesian generative model for the blind IR, which explicitly depicts the degradation process. In this proposed model, a pixel-wise non-i.i.d. Gaussian distribution is employed to fit the image noise. It is with more flexibility than the simple i.i.d. Gaussian or Laplacian distributions as adopted in most of conventional methods, so as to handle more complicated noise types contained in the image degradation. To solve the model, we design a variational inference algorithm where all the expected posteriori distributions are parameterized as deep neural networks to increase their model capability. Notably, such an inference algorithm induces a unified framework to jointly deal with the tasks of degradation estimation and image restoration. Further, the degradation information estimated in the former task is utilized to guide the latter IR process. Experiments on two typical blind IR tasks, namely image denoising and super-resolution, demonstrate that the proposed method achieves superior performance over current state-of-the-arts. The source code is available at https://***/zsyOAOA/VIRNet. © 2020, CC BY-NC-SA.

关键词： Image reconstruction

Study of CdZnTeSe Gamma-Ray Detector under Various Bias Voltages

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Materials Sciences and Applications 2020年第8期11卷 553-559页

作者： Mebougna L. Drabo Stephen U. Egarievwe Utpal N. Roy Benicia A. Harrison Carmella A. Goree Emmanuel K. Savage Ralph B. James Department of Mechanical & Civil Engineering and Construction Management Alabama A&M University Huntsville AL USA Nuclear Engineering and Radiological Science Center Alabama A&M University Huntsville AL USA Department of Electrical Engineering and Computer Science Alabama A&M University Huntsville AL USA Department of Nonproliferation and National Security Brookhaven National Laboratory Upton NY USA Science and Technology Directorate Savannah River National Laboratory Aiken SC USA Biological and Environmental Sciences Department Alabama A&M University Huntsville AL USA Department of Physics Chemistry and Mathematics Alabama A&M University Huntsville AL USA

Cadmium zinc telluride selenide (CdZnTeSe) is a new semiconductor material for gamma-ray detection and spectroscopy applications at room temperature. It has very high crystal quality compared to similar materials such as cadmium telluride and cadmium zinc telluride. The consistency of peak position in radiation detection devices is important to practical applications. In this paper, we have characterized a CdZnTeSe planar detector for bias voltages in the range of -20 V to -200 V and amplifier shaping time of 2, 3 and 6 μs. The peak position of the 59.6-keV gamma line of ²⁴¹Am becomes more stable as the absolute value of the applied voltage increases. The best energy resolution of 8.5% was obtained for the 59.6-keV gamma peak at -160 V bias voltage and 3-μs shaping time. The energy resolution was relatively stable in the -120 V to -200 V range for a 6-μs shaping time. Future work will be focused on the study of the peak position and energy resolution over time.

关键词： CdZnTeSe Energy Resolution Energy-Peak Stability Gamma-Ray Spectroscopy Nuclear Detectors

Inconsistencies among spectral robustness metrics 1

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14th EAI International Conference on Heterogeneous Networking for Quality, Reliability, security and Robustness, Qshine 2018

作者： Wang, Xiangrong Feng, Ling Kooij, Robert E. Marzo, Jose L. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Computing Science Department Institute of High Performance Computing A*STAR Singapore Singapore iTrust Centre for Research in Cyber Security Singapore University of Technology and Design Singapore Singapore Institute of Informatics and Applications University of Girona Girona Spain

ISBN: (数字)9783030144135

ISBN: (纸本)9783030144128

Network robustness plays a critical role in the proper functioning of modern society. It is common practice to use spectral metrics, to quantify the robustness of networks. In this paper we compare eight different spectral metrics that quantify network robustness. Four of the metrics are derived from the adjacency matrix, the others follow from the Laplacian spectrum. We found that the metrics can give inconsistent indications, when comparing the robustness of different synthetic networks. Then, we calculate and compare the spectral metrics for a number of real-world networks, where inconsistencies still occur, but to a lesser extent. Finally, we indicate how the concept of the R∗-value, a weighted sum of robustness metrics, can be used to resolve the found inconsistencies. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2019.

关键词： Circuit theory

Erratum to:Recent Advances of Chimp Optimization Algorithm:Variants and Applications

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Journal of Bionic engineering 2024年第3期21卷 1618-1618页

作者： Mohammad Sh.Daoud Mohammad Shehab Laith Abualigah Mohammad Alshinwan Mohamed Abd Elaziz Mohd Khaled Yousef Shambour Diego Oliva Mohammad A.Alia Raed Abu Zitar College of Engineering Al Ain University112612 Abu DhabiUnited Arab Emirates College of Computer Sciences and Informatics Amman Arab UniversityAmman 11953Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq 25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied Science Research Center Applied Science Private UniversityAmman 11931Jordan School of Computer Sciences Universiti Sains Malaysia11800 Pulau PinangMalaysia Faculty of Information Technology Applied Science Private UniversityAmman 11931Jordan Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 7120001Egypt The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura UniversityMakkah 24382Saudi Arabia Depto.de Innovacio′n Basada en la Informacio′n y el Conocimiento Universidad de GuadalajaraCUCEI45129 GuadalajaraMexico Cyber Security Department Faculty of Science and Information TechnologyAl Zaytoonah University of JordanAmman 11733Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044 Abu DhabiUnited Arab Emirates School of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

Erratum to:J Bionic Eng https://***/10.1007/*** this article the statement in the Funding information section was incorrectly given as‘22UQU4361183DSR03’and should have read‘23UQU4361183DSR03’.

关键词： statement section correctly

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

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arXiv 2020年

作者： Abdar, Moloud Pourpanah, Farhad Hussain, Sadiq Rezazadegan, Dana Liu, Li Ghavamzadeh, Mohammad Fieguth, Paul Cao, Xiaochun Khosravi, Abbas Rajendra Acharya, U. Makarenkov, Vladimir Nahavandi, Saeid Deakin University Australia College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China Dibrugarh University Dibrugarh India Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia Center for Machine Vision and Signal Analysis University of Oulu Oulu Finland Google research United States Department of Systems Design Engineering University of Waterloo Waterloo Canada State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Electronics and Computer Engineering Ngee Ann Polytechnic Clementi Singapore Department of Computer Science University of Quebec in Montreal MontrealQC Canada

—Uncertainty quantification (UQ) plays a pivotal role in the reduction of uncertainties during both optimization and decision making, applied to solve a variety of real-world applications in science and engineering. Bayesian approximation and ensemble learning techniques are two of the most widely-used UQ methods in the literature. In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., self-driving cars and object detection), image processing (e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring), bioinformatics, etc. This study reviews recent advances in UQ methods used in deep learning, investigates the application of these methods in reinforcement learning, and highlight the fundamental research challenges and directions associated with the UQ field. Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

A customized educational booster for online students in cybersecurity education 11

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A customized educational booster for online students in cybe...

11th International Conference on computer Supported Education, CSEDU 2019

作者： Rahouti, Mohamed Xiong, Kaiqi Department of Electrical Engineering University of South Florida TampaFL33620 United States Cyber Florida University of South Florida TampaFL33620 United States Department of Mathematics and Statistics University of South Florida TampaFL33620 United States Intelligent Computer Networking and Security Lab University of South Florida TampaFL33620 United States

ISBN: (纸本)9789897583674

Real-world lab experiments have been an integral part of computer science and engineering curriculums. However, human and computing resources as well as financial support to courses may be limited at many universities ranging from small to large universities and from liberal arts colleges to top research universities as there is a dramatic increase of student enrollments in computer science and engineering for the past ten years. Nowadays, like many other universities nation wide, University of South Florida (USF) in collaboration with the Cyber Florida center offers online cyber security degrees as well as certificates. Throughout such programs, online students are expected to acquire knowledge via an interdisciplinary set of core courses prior to taking a deep dive into one of four following concentrations: cyber intelligence, digital forensics, information assurance and computer security fundamentals. However, when it comes to training student with real-world cyber security labs, both instructors and students face various challenges with regard to resources and virtual environment for exploring and running a broad range of security experiments and tests. In order to achieve the goal of our funded NSF project, in this paper we will discuss our teaching contributions to the development of a broad range of cyber security labs, facilitation of applied cryptography learning through experimental modules, and our customized virtual machine that fits the needs of various online computer networking and security courses. Specifically, we will first present our methodology for the design of our experimental modules and then present in details our pre-built Linux-based portable virtual machine. Those learning and experimental modules have been developed at different levels to meet the need of students with different academic and industrial backgrounds. Copyright © 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Virtual reality

Cryptanalysis and improvement of a semi-quantum private comparison protocol based on Bell states

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arXiv 2020年

作者： Xie, Li Li, Qin Yu, Fang Lou, Xiaoping Zhang, Cai School of Cyberspace Security Xiangtan University Xiangtan411105 China Faculty of Informatics Masaryk University Brno Czech Republic Department of Computer Science Jinan University Guangzhou510632 China College of Information Science and Engineering Hunan Normal University Changsha410081 China College of Mathematics and Informatics South China Agricultural University Guangzhou510642 China

Semi-quantum private comparison (SQPC) allows two participants with limited quantum ability to securely compare the equality of their secrets with the help of a semi-dishonest third party (TP). Recently, Jiang proposed a SQPC protocol based on Bell states (Quantum Inf Process 19(6): 180, 2020) and claimed it is secure. In this paper, we present two types of attack on Jiang’s SQPC protocol. In the first type of attack, an outside eavesdropper will make participants accept a wrong result. In the second type of attack, a malicious participant will not only make the other participant accept a wrong result, but also learn the secret of the honest participant. Neither type of attack will be detected. In addition, we propose an improved SQPC protocol that can resist these two types of attack. © 2020, CC BY-NC-ND.

关键词： Quantum cryptography