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arXiv 2018年

作者： Zhang, Guohui Liang, Gaoyuan Su, Fang Qu, Fanxin Wang, Jing-Yan Huawei Technologies Co. Ltd. Shanghai China Jiangsu University of Technology Jiangsu213001 China Shaanxi University of Science & Technology Xi’an China Northwestern Polytechnical University Xi’an China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China

In the problem of domain transfer learning, we learn a model for the prediction in a target domain from the data of both some source domains and the target domain, where the target domain is in lack of labels while the source domain has sufficient labels. Besides the instances of the data, recently the attributes of data shared across domains are also explored and proven to be very helpful to leverage the information of different domains. In this paper, we propose a novel learning framework for domain-transfer learning based on both instances and attributes. We proposed to embed the attributes of different domains by a shared convolutional neural network (CNN), learn a domain-independent CNN model to represent the information shared by different domains by matching across domains, and a domain-specific CNN model to represent the information of each domain. The concatenation of the three CNN model outputs is used to predict the class label. An iterative algorithm based on gradient descent method is developed to learn the parameters of the model. The experiments over benchmark datasets show the advantage of the proposed model. Copyright © 2018, The Authors. All rights reserved.

关键词： Gradient methods

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A novel supervised bimodal emotion recognition approach based on facial expression and body gesture

A novel supervised bimodal emotion recognition approach base...

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作者： Yan, Jingjie Lu, Guanming Bai, Xiaodong Li, Haibo Sun, Ning Liang, Ruiyu Jiangsu Provincial Key Laboratory of Image Processing and Image Communication College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing210003 China Engineering Research Center of Wide Band Wireless Communication Technology Nanjing University of Posts and Telecommunications Nanjing211167 China School of Communication Engineering Nanjing Institute of Technology Nanjing211167 China

In this letter, we propose a supervised bimodal emotion recognition approach based on two important human emotion modalities including facial expression and body gesture. A effectively supervised feature fusion algorithms named supervised multiset canonical correlation analysis (SMCCA) is presented to established the linear connection between three sets of matrices, which contain the feature matrix of two modalities and their concurrent category matrix. The test results in the bimodal emotion recognition of the FABO database show that the SMCCA algorithm can get better or considerable efficiency than unsupervised feature fusion algorithm covering canonical correlation analysis (CCA), sparse canonical correlation analysis (SCCA), multiset canonical correlation analysis (MCCA) and so on. © 2018 The Institute of Electronics, information and Communication Engineers.

关键词： Emotion Recognition

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FPGA optimal implementation of PRINCE against power analysis attacks 5

FPGA optimal implementation of PRINCE against power analysis...

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5th International Conference on information Science and Cloud Computing, ISCC 2017

作者： Zou, Yi Li, Lang College of Computer Science and Technology Hengyang Normal University Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

The algorithm PRINCE proposed in ASIACRYPT 2012 is a lightweight cipher, currently suitable for the implementation on RFID Smart Card of the IoT. It's studied to achieve the optimal implementation of PRINCE encryption algorithm, and to add a fixed random mask to enhance the anti power attacking ability of PRINCE. In this paper, we constructed the same operations into a module called PrinceRound, and used counter to control the PrinceRound module, while the same round operation runs repeatedly. As a result, it can save registers and effectively reduce the amount of computation. Furthermore, we used a special method by adding the random mask to S-box. The experimental results show that the optimized PRINCE occupies area 9.8% fewer than original PRINCE on FPGA and the encryption with a fixed random mask can run correctly. Last but not least, our research is the first one about the implementation of PRINCE algorithm on FPGA, and can serve as a reference for further application of IOT encryption. © Copyright owned by the author(s).

关键词： Field programmable gate arrays (FPGA)

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Web server security evaluation method based on multi-source data

Web server security evaluation method based on multi-source ...

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International Conference on Cloud Computing, Big Data and Blockchain (ICCBB)

作者： Kedong Wu Xiaoling Gao Yanhua Liu Provincial Key Laboratory of Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian Fujian Fuzhou Fujian China

ISBN: (纸本)9781728112787

Traditional web security assessments are evaluated using a single data source, and the results of the calculations from different data sources are different. Based on multi-source data, this paper uses Analytic Hierarchy Process to construct an evaluation model, calculates the weight of each level of indicators in the web security evaluation model, analyzes and processes the data, calculates the host security threat assessment values at various levels, and visualizes the evaluation results through ECharts+WebGL technology.

关键词： Security Servers IP networks XML information processing Data models Safety

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A Dynamic Community Detection Algorithm Based on Parallel Incremental Related Vertices 2

A Dynamic Community Detection Algorithm Based on Parallel In...

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2017 IEEE 2nd International Conference on Big Data Analysis（ICBDA 2017）

作者： Guohui Li Kun Guo YuZhong Chen Ling Wu Danhong Zhu College of Mathematics and Computer Sciences Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing(Fuzhou University) Key Laboratory of Spatial Data Mining & Information Sharing Ministry of Education

ISBN: (纸本)9781509036202

One of the traditional ways for detecting dynamic communities is to find the communities at each interval through the static community detection ***,it usually leads to high computation *** this paper,a novel algorithm based on the Map Reduce model and the label propagation progress with the strategy of incremental related vertices is proposed,which is called PLPIRV(Parallel Label Propagation and Incremental Related Vertices).Based on the communities found at the previous interval,the new algorithm adjusts the communities the incremental related vertices belong *** clustering of the whole network can be avoided by incrementally analyzing the variation of the networks,so that the time cost can be greatly *** on artificial and real datasets show that the proposed algorithm performs well on dynamic community detection.

关键词： dynamic community detection parallel computation incremental algorithm label propagation

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A Generation Method of Automation Test Cases Based on Android

A Generation Method of Automation Test Cases Based on Androi...

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2017 5th International Conference on Machinery,Materials and Computing technology(ICMMCT 2017)

作者： Ming Zhang Baolei Cheng Weizhong Zha Jiwen Yang School of Computer Science and Technology Soochow University Provincial Key Laboratory for Computer Information Processing Technology

Aiming at the problems that complex testing process, incomplete testing and poor reusability of test cases for Android automated testing methods, we propose a generation method of automation test cases based on control traversal under the guidance of standard path. The method firstly records a test script as a standard path by the tester, then automatically acquires the control in the interface and generates the control relationship graph. Finally, the test case generation method based on the depth-first search was used to traverse the control relationship graph to generate test cases. The test case was used to test the Android mobile App. The results show that the test case generated by this method improves the test coverage and script reusability, simplifies the test operation and proves the feasibility of the method.

关键词： Automated Testing Test Case Standard Path Control Traversal Depth-First Search

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Research on power attack comprehensive experiment platform based on SAKURA -G hardware circuit 7

Research on power attack comprehensive experiment platform b...

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7th International Conference on computer Engineering and Networks, CENet 2017

作者： Jiao, Ge Li, Lang Zou, Yi College of Computer Science and Technology Hengyang Normal UniversityHunan Provincial Engineering Laboratory for Technology of Traditional Settlements Digitalization Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Hunan421002 China

The power attack of the hardware circuit is going through the steps of algorithm writen in FPGA, power consumption, data processing and analysis. In order to solve the problem of the existing power attack experimental platform because the processing steps are too scattered, feature complex operations and other issues, we've thus developed a higher degree of integration of the experimental platform. The advanced encryption standard (AES) algorithm is taken as an example to illustrate the whole process of implementing the correlation power analysis (CPA) attack on the experimental platform. The AES algorithm will be downloaded to the SAKURA-G experiment board, acquire the algorithm runtime power leakage, carry out the energy analysis because related attacks on information may leak location, and restore the AES first round of the first byte of the key. Empirical results show that the comprehensive experimental platform will integrate these steps into a platform, simplify the operation process, ensure the accuracy of power acquisition, realize the parallel data processing and improve the accuracy and efficiency of power attack. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Side channel attack

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Modelling of synchronisation and energy performance of FBE- and LBE-based standalone LTE-U networks

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Journal of Engineering 2017年第7期2017卷 292-299页

作者： Li, Jiamin Shan, Hangguan Huang, Aiping Yuan, Jiantao Cai, Lin X. Zhejiang Provincial Key Laboratory of Information Processing and Communication Networks Hangzhou China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago United States

Without the aid of licensed channel, deploying long-term evolution (LTE) networks over unlicensed spectrum (named standalone LTE-U networks) faces the difficulty of establishing and maintaining synchronisation between user equipments and base stations. In this work, considering the two modes of listen-before-talk-based channel access scheme, frame-based equipment (FBE) and load-based equipment (LBE), the authors propose analytical frameworks to study the successful probability of synchronisation and the energy consumption of synchronisation in a standalone LTE-U network. Specifically, for the LBE mode, the authors also propose a Lattice-Poisson algorithmbased approach to derive the distribution of the channel non-occupancy period of a standalone LTE-U network. Furthermore, the authors explore the impact of diverse protocol parameters of both FBE and LBE modes on the two studied performance metrics. Simulation results demonstrate the accuracy of the analysis, and shed some light on the selection of FBE and LBE for standalone LTE-U networks, in terms of synchronisation, energy consumption, and throughput of standalone LTE-U and Wi-Fi networks.

关键词： Synchronization

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Application of Deep Learning in Software Security Detection

Application of Deep Learning in Software Security Detection

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2018 International Conference on Computational Science and Engineering(ICCSE 2018)

作者： Lin Li Ying Ding Jiacheng Mao College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System

Machine learning is knowledge of learning rules from data through computational models and algorithms. It has been applied in various fields that require mining rules from complex data, and has become one of the most core technologies in the field of artificial intelligence in the broad sense. In recent years, a variety of deep neural networks have made remarkable achievements in a large number of machine learning problems, forming a new branch of machine learning, deep learning, and also raising a new climax of machine learning theory, method and application research. Software security is a highly concerned issue at present. Vulnerability detection technology is an important measure to improve software security. In order to make software application more secure, it is necessary to discuss the application of deep learning in software security detection.

关键词： Deep learning Software security Detection RNN

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Research on the key technology of Safety Protection in Application Environment of Blockchain

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IOP Conference Series: Materials Science and Engineering 2019年第3期569卷

作者： Hua Zhang Jiong Wang Ge Xu Zhiqiang Ruan College of Computer and Control Engineering Mmjiang University Fuzhou 350108 china Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University)

This paper analyzes the current situation of blockchain application security. Then, makes a concrete analysis on the problems existing in the application safety of blockchain, including the attack of consensus algorithm, the leakage of privacy, and the programming vulnerability of blockchain and hash collisions. Then it introduces in detail the three key technologies of security protection under the blockchain application environment, P2P network technology, asymmetric encryption technology and consensus mechanism technology. In order to make more relevant people know more about the key technologies of safety protection in the application environment of blockchain.

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