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4th International Conference on Cloud Computing and Security, ICCCS 2018

作者： Xu, Jiang Zhang, Jian Ren, Yongjun Kim, Hye-Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Business Administration Research Institute Sungshin W. University Seoul Korea Republic of

ISBN: (纸本)9783030000059

At present some developed countries have put forward their digital continuity action plans. And the digital continuity has also become a hot spot in the research of electronic records. However, the technology and measures for the protection of the digital continuity are still lack. In this paper, we first point out the necessity of ensuring the availability and completeness of the electronic record. Moreover, the technology framework of availability and completeness for electronic record are firstly proposed. Secondly, we make use of the coding theory to ensure the availability of electronic record. In addition, the technology of ensuring completeness for electronic record is constructed based on functional dependency theory, and the method of evaluating completeness of electronic record is present using the functional dependency theory. © Springer Nature Switzerland AG 2018.

关键词： Big data

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Joint Bayesian guided metric learning for end-to-end face verification

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Neurocomputing 2018年 275卷 560-567页

作者： Di Chen Chunyan Xu Jian Yang Jianjun Qian Yuhui Zheng Linlin Shen School of Computer Science and Engineering Nanjing University of Science and Technology 210094 China Jiangsu Engineering Center of Network Monitoring School of computer and software Nanjing University of Information Science and Technology 210044 China School of Computer Science and Software Engineering Shenzhen University 518060 China

In this work, we address the problem of face verification, namely determining whether a pair of face images belongs to the same or different subjects. Previous works often consider solving the problem of face verification in two steps: feature extraction and face recognition, resulting in a fragmented procedure. We argue that these techniques, although working well, fail to explicitly exploit a full end-to-end framework for face verification, which has received much attention and achieved significant improvements recently. In this paper, we propose a novel Joint Bayesian guided metric learning technique for dealing with the face verification task, which well integrates the above two steps of face verification into an end-to-end convolutional neural network (CNN) architecture. In the training stage, an initial neural network, which has the similar architecture with GoogLeNet CNN model, is firstly pre-trained by optimizing classification-based objective functions on the publicly available CASIA WebFace database. Based on constructed face pairs dataset from CASIA WebFace and LFW datasets, we then fine-tune the whole network parameters under the guide of the learned knowledge, which is obtained from the highly successful Joint Bayesian model. This guided learning procedure, which can also be seen as a metric learning technique, can further update network parameters for discriminating face pairs. In the testing process, the outputs by this unified network are discriminated with a threshold value to produce the ultimate prediction for the face verification task. Comprehensive evaluations over the LFW dataset well demonstrate the encouraging face verification performance of our proposed framework.

关键词： Face verification Convolutional neural network Joint Bayesian model

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An intelligent agent-based method for task allocation in competitive cloud environments

An intelligent agent-based method for task allocation in com...

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作者： Kong, Yan Zhang, Minjie Ye, Dayong Zhu, Jinxiu Choi, Junho Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science and Software Engineering University of Wollongong Wollongong2522 Australia Research Institute of Ocean and offshore engineering Hohai Universtiy Nantong226300 China Division of Undeclared Majors Chosun University Gwangju61452 Korea Republic of

In market-based cloud environments, both resource consumers and providers are self-interested;additionally, they can come and leave the environment freely. Therefore, the environment is competitive and uncertain. Because of the competition, participants may cheat in making deals, and this represents that the environment is insecure to resource providers who intend to earn profits through renting their resources to the tasks of resource consumers. Against this, in this paper, intelligent agents are designed to strategically quote for the tasks that they are interested in, on behalf of resource providers. Agents could quote according to the messages it obtained and the information learnt and predicted from the messages, to minimize the influence of insecure factors, such as cheating, competition, and dynamism. The experimental evaluation shows that the proposed method outperforms both a well-known multiresource negotiation-based task allocation method and a max-sum belief propagation–based method. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Intelligent agents

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Compressive Sensing Sparse Sampling Method for Composite Material Based on Principal Component Analysis

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第2期35卷 282-289页

作者： Sun Yajie Gu Feihong Ji Sai Wang Lihua Jiangsu Engineering Centre of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 P. R. China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing 210044 P. R. China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 P. R. China School of Information and Control Nanjing University of Information Science and Technology Nanjing 210014 P. R. China

Signals can be sampled by compressive sensing theory with a much less rate than those by traditional Nyquist sampling theorem,and reconstructed with high probability,only when signals are sparse in the time domain or a transform *** signals are not sparse in real world,but can be expressed in sparse form by some kind of sparse *** used sparse transformations will lose some information,because their transform bases are generally *** this paper,we use principal component analysis for data reduction,and select new variable with low dimension and linearly correlated to the original variable,instead of the original variable with high dimension,thus the useful data of the original signals can be included in the sparse signals after dimensionality reduction with maximize ***,the loss of data can be reduced as much as possible,and the efficiency of signal reconstruction can be ***,the composite material plate is used for the experimental *** experimental result shows that the sparse representation of signals based on principal component analysis can reduce signal distortion and improve signal reconstruction efficiency.

关键词： principal component analysis compressive sensing sparse representation signal reconstruction

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Coverless image steganography based on SIFT and BOF

Coverless image steganography based on SIFT and BOF

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作者： Yuan, Chengsheng Xia, Zhihua Sun, Xingming School of Computer and Software Nanjing University of Information Science and Technology China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology China

In order to realize secret communication, conventional steganography techniques can embed the secret message into carrier images by modifying the content and structure of carrier images. Although steganography techniques provide us with some more secure communication, the modification traces will be detected through using these brand-new steganalysis tools. Thereby, in order to eliminate the influence of modification traces, we propose a novel coverless image steganography scheme based on scale invarient feature transform and bag of feature. Different from conventional steganography, images have already contained the concealing information, so we can transmit natural images, whose features are the same with the secret information, to receivers. Firstly, the robust feature hash sequences are constructed with our protocol of feature. Then, the secret message is converted into bitstreams. Finally, these images with the seceret information are chosen and sent to receivers through using inverted index. Throughout the process, original images are never modified in our scheme, so our method can resist the analysis of existing steganalysis tools. Numerical experiments also indicate that our scheme has a desirable robustness to the common image attacks.

关键词： Steganography

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Short text classification technology based on KNN+hierarchy SVM 12th

Short text classification technology based on KNN+hierarchy ...

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12th International Conference on Future Information Technology, FutureTech 2017

作者： Yin, Chunyong Shi, Lingfeng Wang, Jin School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China College of Information Engineering Yangzhou University Yangzhou China

ISBN: (纸本)9789811050404

A short text classification method based on combination of KNN and hierarchical SVM is proposed. First, the KNN algorithm is improved to get the K nearest neighbor class labels quickly, so as to effectively filter the candidate classes of documents. And then classify them from top to bottom using a multi-class sparse hierarchical SVM classifier. By this way, the document can be classified efficiently. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Classification (of information)

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Improved data stream clustering algorithm for anomaly detection 12th

Improved data stream clustering algorithm for anomaly detect...

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12th International Conference on Future Information Technology, FutureTech 2017

作者： Yin, Chunyong Zhang, Sun Wang, Jin School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China College of Information Engineering Yangzhou University Yangzhou China

ISBN: (纸本)9789811050404

Intrusion detection provides important protection for network security and anomaly detection as a type of intrusion detection, can recognize the pattern of normal behaviors and label the behaviors which departure from normal pattern as abnormal behaviors. We think that the traditional methods based on dataset do not satisfy the needs of dynamic network environment. The network data stream is temporal and cannot be treated as static dataset. The concept and distribution of data objects is variety in different time stamps and the changing is unpredictable. Therefore, we propose an improved data stream clustering algorithm and design the frame of anomaly detection according to the improved algorithm. It can modify the established model with the changing of data stream and detect abnormal behaviors in time. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Intrusion detection

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Application of an improved data stream clustering algorithm in intrusion detection system 12th

Application of an improved data stream clustering algorithm ...

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12th International Conference on Future Information Technology, FutureTech 2017

作者： Yin, Chunyong Xia, Lian Wang, Jin School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China College of Information Engineering Yangzhou University Yangzhou China

ISBN: (纸本)9789811050404

With the continuous development of computer network technology, traditional intrusion detection system is short of good adaptability. Aiming at the traditional intrusion detection system is difficult to adapt to the increasing amount of data demand for real-time processing capability, this paper proposes a clustering algorithm based on sliding window data streams, based on which we build the IDS network security defense model. The experiment results show that the model is able to adapt to the high-speed network intrusion detection requirements. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Data mining

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A duplicate data detection approach based on MapReduce and HDFS

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Recent Patents on computer Science 2017年第2期10卷 140-148页

作者： Wei, Fang Xue-Zhi, Wen Yu, Zheng Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210066 China Department of Electrical & Computer Engineering University of Florida GainesvilleFL32611 United States

Background: With the surge in the volume of collected data, deduplication will undoubtedly become one of the problems faced by researchers. There is significant advantage for deduplication to reduce storage, network bandwidth, and system scalability of coarse-grained redundant data. Since the conventional methods of deleting duplicate data include hash comparison and binary differential incremental. They will lead to several bottlenecks for processing large scale data. And, the traditional Simhash similarity method has less consideration on the natural similarity of text in some specific fields and cannot run in parallel program with large scale text data processing efficiently. This paper examines several most important patents in the area of data detection. Then, this paper will focus on large scale of data deduplication based on MapReduce and HDFS. Methods: We propose a duplicate data detection approach based on MapReduce and HDFS, which uses the Simhash similarity computing algorithm and SSN algorithm, and explain our distributed duplicate detection workflow. The important technical advantages of the invention include generating a checksum for each processed record and comparing the generated checksum to detect duplicate record. It produces the fingerprints of short text with Simhash similarity algorithm. It clusters the fingerprint results using Shared Nearest Neighbor (SNN) algorithm. The whole parallel progress is implemented using MapReduce programming model. Results: From the experimental results, we conclude that our proposed approach obtains MapReduce job schedules with significantly less executing time, making it suitable for processing large scale datasets in real applications. The experimental results show the proposed approach has better performance and efficiency. Conclusion: In this patent, we propose a duplicate data detection approach based on MapReduce and HDFS, which uses the Simhash similarity computing algorithm and SSN algorithm. The results

关键词： MapReduce

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Error analysis of time delay based on ultrasonic phased array structural health monitoring

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Journal of computers (Taiwan) 2018年第4期29卷 176-184页

作者： Ji, Sai Gu, Feihong Sun, Yajie Wang, Jin Jiangsu engineering Centre of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China School of Information Engineering Yangzhou University Yangzhou225002 China

Ultrasonic phased array technology becomes significant in structural health monitoring with its flexible beam deflection and strong focusing performance. The transducer is used to complete the multiple directions scanning of the structure. During the process of beam scanning, the signal exciting from each element needs to add a time delay in time domain, due to the difference to the distance from each element to the far field target point, so that the excitation signal can reach the target point and the far field at the same time. Besides, in the process of receiving and transmitting process, it also needs to add a time delay for the response signal, so that the sensor can receive the reflection signal from the preset deflection angle. Therefore, the error will be generated in the calculation of time delay. Making the anti-rust aluminum plate as the experimental object, the process of ultrasonic phased array structural health monitoring will be introduced. And then the reason of time delay error will be pointed out and analyzed. © 2018 computer Society of the Republic of China. All Rights Reserved.

关键词： Time delay

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