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

作者： Zhibo Wang Jingxin Li Jiahui Hu Ju Ren Zhetao Li Yanjun Li State Key Laboratory for Novel Software Technology Nanjing University P. R. China Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education School of Cyber Science and Engineering Wuhan University P. R. China School of Information Science and Engineering Central South University P. R. China Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education College of Information Engineering Xiangtan University P. R. China School of Computer Science and Technology Zhejiang University of Technology P. R. China

Reverse auction-based incentive mechanisms have been commonly proposed to stimulate mobile users to participate in crowdsensing, where users submit bids to the platform to compete for tasks. Recent works pointed out that bid is a private information which can reveal sensitive information of users (e.g., location privacy), and proposed bid-preserving mechanisms with differential privacy against inference attack. However, all these mechanisms rely on a trusted platform, and would fail in bid protection completely when the platform is untrusted (e.g., honest-but-curious). In this paper, we focus on the bid protection problem in mobile crowdsensing with an untrusted platform, and propose a novel privacy-preserving incentive mechanism to protect users' true bids against the honest-but-curious platform while minimizing the social cost of winner selection. To this end, instead of uploading the true bid to the platform, a differentially private bid obfuscation function is designed with the exponential mechanism, which helps each user to obfuscate bids locally and submit obfuscated task-bid pairs to the platform. The winner selection problem with the obfuscated task-bid pairs is formulated as an integer linear programming problem and proved to be NP-hard. We consider the optimization problem at two different scenarios, and propose a solution based on Hungarian method for single measurement and a greedy solution for multiple measurements, respectively. The proposed incentive mechanism is proved to satisfy ε-differential privacy, individual rationality and γ-truthfulness. The extensive experiments on a real-world data set demonstrate the effectiveness of the proposed mechanism against the untrusted platform.

关键词： Task analysis Privacy Differential privacy Sensors Mobile handsets Cryptography Integer linear programming

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Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

arXiv

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arXiv 2020年

作者： Yu, Liang Sun, Yi Xu, Zhanbo Shen, Chao Yue, Dong Jiang, Tao Guan, Xiaohong College of Automation & College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing210003 China Systems Engineering Institute Ministry of Education Key Lab for Intelligent Networks and Network Security Xi’an Jiaotong University Xi’an710049 China college of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210003 China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210003 China Wuhan National Laboratory for Optoelectronics School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China

In commercial buildings, about 40%-50% of the total electricity consumption is attributed to Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic burden on building operators. In this paper, we intend to minimize the energy cost of an HVAC system in a multi-zone commercial building under dynamic pricing with the consideration of random zone occupancy, thermal comfort, and indoor air quality comfort. Due to the existence of unknown thermal dynamics models, parameter uncertainties (e.g., outdoor temperature, electricity price, and number of occupants), spatially and temporally coupled constraints associated with indoor temperature and CO2 concentration, a large discrete solution space, and a non-convex and non-separable objective function, it is very challenging to achieve the above aim. To this end, the above energy cost minimization problem is reformulated as a Markov game. Then, an HVAC control algorithm is proposed to solve the Markov game based on multi-agent deep reinforcement learning with attention mechanism. The proposed algorithm does not require any prior knowledge of uncertain parameters and can operate without knowing building thermal dynamics models. Simulation results based on real-world traces show the effectiveness, robustness and scalability of the proposed algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Research on the Focused Crawler of Mineral Intelligence Service Based on Semantic Similarity

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Journal of Physics: Conference Series 2020年第1期1575卷

作者： Shiqi Deng Computer Academy Xiangtan University Xiangtan People's Republic of China 411105 Hunan Key Laboratory of Internet of Things and Information Security Xiangtan University Xiangtan People's Republic of China 411105

Large-scale general search engines have been unable to meet the needs of 'specialized, sophisticated and deep' information in the field of mineral intelligence services. Vertical search engines have emerged at the historic moment, and the focused crawler is the key technology to achieve vertical search engines. This paper proposes a hybrid topic strategy based on text content and web link structure for the characteristics of mineral information field. In order to improve the topic relevance determination ability of the focused crawler, this article introduces HowNet and the word embedding technology in the field of natural language processing, and combines them to carry out the text-based topic relevance determination; at the same time, it also introduces the HITS algorithm based on the link structure of web pages. The topic strategy based on text content is organically combined with the topic strategy based on the webpage link structure to realize the recognition and prediction of the webpage topic. Simulation experiment results show that the method proposed in this paper can achieve a high recall rate and precision rate for the acquisition of mineral intelligence information on the Internet.

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An Access Control Model for Multi-level security in Multi-domain networking Environments 9th

An Access Control Model for Multi-level Security in Multi-do...

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2017 9th International Conference on Modelling, Identification and Control (ICMIC 2017)

作者： Hongbin Zhang Junshe Wang Jiang Chang the School of Information Science & Engineering at HEBUST Shaanxi Key Laboratory of Network and System Security Xidian University

ISBN: (纸本)9781509065769;9781509065752

Access control is important to protect the network *** increasing demand for secure interactions between network domains brings in new challenges to access control *** this paper we design an access control model which provides a multilevel mapping method between hierarchical access control structures for achieving multilevel security protection in multi-domain networking *** access control structures ensure rigorous multilevel security in intra *** the mapping method based on quantized subject attributes is proposed to determine the subject's security level in its target *** is used in the model to adjust the mapping value in order to achieve flexible multilevel inter-domain access *** results we obtained from simulations are also reported in this paper to verify the effectiveness of the proposed access control model.

关键词： multi-domain multi-level security access control multi-attributes quantization inter-domain mapping

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Experimental implementation of high-speed balanced homodyne detector

Experimental implementation of high-speed balanced homodyne ...

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Frontiers in Optics, FIO 2018

作者： Zhang, Xiaoxiong Zhang, Yichen Xu, Bingjie Yu, Song Guo, Hong State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Science and Technology on Security Communication Laboratory Institute of Southwestern Communication Chengdu610041 China State Key Laboratory of Advanced Optical Communications Systems and Networks School of Electronics Engineering and Computer Science Center for Quantum Information Technology Center for Computational Science and Engineering Peking University Beijing100876 China

We present a high-speed balanced homodyne detector whose bandwidth is above 900 MHz and quantum to classical noise ratio reaches 12 dB respectively, which could be applied to the high-speed continuous variable quantum... 详细信息

ISBN: (纸本)9781943580460

关键词： Quantum optics

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Orthogonalized lattice enumeration for solving SVP

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Science China(information Sciences) 2018年第3期61卷 191-205页

作者： Zhongxiang ZHENG Xiaoyun WANG Guangwu XU Yang YU Department of Computer Science and Technology Tsinghua University Institute for Advanced Study Tsinghua University Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong Universtiy Department of Electrical Engineering and Computer Sciences University of Wisconsin

The orthogonalized integer representation was independently proposed by Ding et al. using genetic algorithm and Fukase et al. using sampling technique to solve shortest vector problem(SVP). Their results are promising. In this paper, we consider sparse orthogonalized integer representations for shortest vectors and propose a new enumeration method, called orthognalized enumeration, by integrating such a representation. Furthermore, we present a mixed BKZ method, called MBKZ, by alternately applying orthognalized enumeration and other existing enumeration methods. Compared to the existing ones, our methods have greater efficiency and achieve exponential speedups both in theory and in practice for solving SVP. Implementations of our algorithms have been tested to be effective in solving challenging lattice problems.

关键词： lattice-based SVP sparse representations enumeration BKZ

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Incremental User Modeling of Online Activity for Cyber-I Growth with Successive Browsing Logs

Incremental User Modeling of Online Activity for Cyber-I Gro...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Yen Tsan Ao Guo Jianhua Ma Runhe Huang Zhong Chen MoE Key Laboratory of Network and Software Security Assurance Peking University Beijing China Graduate School of Computer and Information Sciences Hosei University Tokyo Japan Faculty of Computer and Information Sciences Hosei University Tokyo Japan

The following topics are dealt with: learning (artificial intelligence); security of data; Internet; feature extraction; Internet of Things; pattern classification; mobile computing; data privacy; cloud computing; soc... 详细信息

ISBN: (纸本)9781538675199

关键词： Big Data Data models Predictive models Task analysis Program processors Testing Uniform resource locators

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HideMe: Privacy-Preserving Photo Sharing on Social networks

HideMe: Privacy-Preserving Photo Sharing on Social Networks

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

作者： Fenghua Li Zhe Sun Ang Li Ben Niu Hui Li Guohong Cao School of Cyber Security University of Chinese Academy of Sciences China Department of Computer Science and Computer Engineering University of Arkansas USA Chinese Academy of Sciences Institute of Information Engineering China State Key Laboratory of Integrated Services Networks School of Cyber Engineering Xidian University China Department of Computer Science and Engineering The Pennsylvania State University PA USA

Photo sharing on Online Social networks (OSNs) has become one of the most popular social activities in our daily life. However, some associated friends or bystanders in the photos may not want to be viewed due to privacy concerns. In this paper, we propose the design, implementation and evaluation of HideMe, a framework to preserve the associated users' privacy for online photo sharing. HideMe acts as a plugin to existing photo sharing OSNs, and it enables the following: a) extraction of factors when users upload their photos, b) associated friends in the uploaded photos are able to set their own privacy policies based on scenarios, instead of a photo-by-photo setting, c) any user in other friend's uploaded photos could be hidden away from unwanted viewers based on one time policy generation. We also design a distance-based algorithm to identify and protect the privacy of bystanders. Moreover, HideMe not only protects users' privacy but also reduces the system overhead by a carefully designed face matching algorithm. We have implemented a prototype of HideMe, and evaluation results have demonstrated its effectiveness and efficiency.

关键词： Privacy Face Access control Data privacy Facebook Databases

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A center-point algorithm for unit commitment with carbon emission trading

arXiv

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arXiv 2019年

作者： Yang, Linfeng Li, Wei Chen, Guo Fang, Beihua Tang, Chunming Dong, Zhaoyang School of Computer Electronics and Information Guangxi University Nanning530004 China School of Electrical Engineering and Telecommunications University of NSW SydneyNSW2052 Australia School of Mathematics and Information Science Guangxi University Nanning530004 China Guangxi Key Laboratory of Multimedia Communication and Network Technology Guangxi University China

This paper proposes a global optimization method for it ensures finding good solutions while solving the unit commitment (UC) problem with carbon emission trading (CET). This method consists of two parts. In the first part, a sequence of linear integer-relaxed subproblems are first solved to rapidly generate a tight linear relaxation of the original mixed integer nonlinear programming problem (MINLP) model. In the second part, the algorithm introduces the idea of center-cut so that it can quickly find good solutions. The approach tested on 10 test instances with units ranging from 35 to 1560 over a scheduling period of 24h, and compared with state-of-the-art solver CPLEX. The results show that the proposed algorithm can find better solutions than CPLEX in a short time. And it is more suitable to solve large scale UC problem than CPLEX. Copyright © 2019, The Authors. All rights reserved.

关键词： Approximation algorithms

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Differential attacks on reduced SIMON versions with dynamic key-guessing techniques

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中国科学（信息科学） 2018年第9期61卷 259-261页

作者： Ning WANG Xiaoyun WANG Keting JIA Jingyuan ZHAO Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong University Jinan 250100 China School of Mathematics Shandong University Jinan 250100 China Key Laboratory of Cryptologic Technology and Information Security Ministry of EducationShandong University Jinan 250100 China School of Mathematics Shandong University Jinan 250100 China Institute for Advanced Study Tsinghua University Beijing 100084 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China Beijing Research Institute of Telemetry Beijing 100094 China

In 2013,NSA published the specifications of two lightweight block cipher families SIMON and SPECK [1].Since the SIMON family was announced,it has attracted a lot of attention of the *** this article,we use the existing differential characteristics given in [2-5] to analyze the reduced SIMON ***,we extend the characteristics backward and forward for several rounds and get the full differential path we *** to Wang et al.'s method in [6],we deduce the sufficient bit conditions corresponding to the differential *** find that the bit conditions can be divided into two *** conditions of the first type only depend on plain-texts or ciphertexts,which can be fulfilled by selecting the conforming plaintexts,ciphertexts and building the data structures.

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