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A RFID data-cleaning algorithm based on communication information among RFID readers

International Journal of u- and e- Service, Science and Technology 2015年第1期8卷 155-164页

作者： Gu, Yunhua Gao, Bao Wang, Jin Yin, Mingshu Zhang, Junyong Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology Nanjing China

For the insufficient of existing algorithms of redundant-reader elimination, the paper proposes a data-cleaning algorithm based on communication information among readers. This algorithm is no longer dependent on the tag to send information between the RFID readers, but to transmit information directly through communication information among the readers to determine which reader the tag belongs to and whether the reader is redundant or not. This paper does a lot of experiments to verify the effectiveness of the algorithm. © 2015 SERSC.

关键词： Cleaning

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Extracting Regular Behaviors from Social Media networks

Extracting Regular Behaviors from Social Media Networks

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International Conference on Multimedia Information networking and Security (MINES)

作者： Leiming Yan Jinwei Wang School of Computer & Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China

Social media network analysis has become very popular in recent years. How do real networks evolve over time? What are the normal evolving behaviors in a social media network? In order to extract behaviors occurring regularly to reveal the microscopic evolving properties in social networks, the evolving process of networks is modeled as stochastic states transition, and the evolving behaviors are described as topological structure changes of a series of sub graphs. Then, based on Maximal Frequent Sub graph mining technology, RB Miner (Regular Behaviors Miner) algorithm is proposed to identify such regular behaviors in network dataset. The empirical evaluation using both synthetic and real dataset verifies that the proposed algorithm is valid, and the regular behavior patterns show more dynamic information hidden in evolving social networks than normal frequent sub graph patterns.

关键词： Social network services Data mining Media Electronic mail Databases Markov processes

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Zhangjie Fu Jiangang Shu Jin Wang Xingming Sun School of Computer and Software & Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China

The increasing popularity of cloud computing makes the data owner to outsource sensitive data in encrypted form onto the cloud. To tackle the problem of searching over encrypted cloud data, many keyword-based searchable encryption schemes have been proposed. However, there are few document-based search schemes in this field, which are also important in real applications. In this paper, we use the simhash algorithm to realizing similarity search over encrypted document with privacy-preserving. Through our method, data users can find similar encrypted documents stored in cloud by querying a document. In addition, a trie-based index is adopted in our solution to improve search efficiency.

关键词： Indexes Fingerprint recognition Feature extraction Servers Encryption Hamming distance

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Document Attribute-Based Keyword Search over Encrypted Data

Document Attribute-Based Keyword Search over Encrypted Data

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Zhangjie Fu Jie Xi Jin Wang Xingming Sun School of Computer and Software & Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China

As the cloud computing popularizes, sensitive data need to be encrypted before outsourcing, which makes the traditional data utilization useless. So search over these encrypted documents is a very challenging task. This paper firstly descripts the framework of the searchable encryption, and then presents the existing keyword-based search technologies. At last, we propose a novel color-based keyword search scheme for encrypted office document. Two vectors on behalf of the keywords and the corresponding color are used. The scheme can return top-k set as correct as possible meeting user's requirements.

关键词： Keyword search Semantics Cloud computing XML Encryption Vectors

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Secure Storage of Data in Cloud Computing

Secure Storage of Data in Cloud Computing

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Zhangjie Fu Xinyue Cao Jin Wang Xingming Sun School of Computer and Software & Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China

Cloud storage brings convenient storage of data, at the same time there are also hidden security issues. Data storage security includes legal access to the data stored in the cloud, namely access authorization and authentication security data sharing and the encryption of stored data to ensure data confidentiality, consisting of the accessibility to effective cryptographic data and inaccessibility to the deleted cryptographic data, using tamper-proof technology to ensure the integrity of the data, as well as using tracking technology to ensure data traceability. This paper focuses on the file systems with secure data deletion. We design a file system which supports secure deletion of data. It uses CP-ABE which supports fine-grained access policy to encrypt files.

关键词： Cloud computing Encryption Access control File systems Secure storage

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Notice of Violation of IEEE Publication Principles: Data Access Control for Multi-authority Cloud Storage Systems

Notice of Violation of IEEE Publication Principles: Data Acc...

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International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP)

作者： Zhangjie Fu Lin Xin Jin Wang Xingming Sun School of Computer and Software & Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China

Notice of Violation of IEEE Publication Principles "Data Access Control for Multi-Authority Cloud Storage Systems" by Zhangjie Fu, Lin Xin, Jin Wang, Xingming Sun in the Proceedings of the Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, August 2014, pp. 714-717 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper copies original content from the papers cited below. The original content was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission. "DAC-MACS: Effective Data Access Control for Multi-Authority Cloud Storage Systems" by Kan Yang, Xiaohua Jia, Kui Ren, Bo Zhang in the Proceedings of the IEEE INFOCOM, April 2013, pp. 2895-2903 "Secure Data Deletion from Persistent Media" by Joel Reardon, Hubert Ritzdorf, David Basin, Srdjan Capkun Proceedings of the ACM SIGSAC Conference on computer and Communications Security, 2013, pp. 271-284 "Policy-based Secure Deletion" by Christian Cachin, Kristiyan Haralambiev, Hsu-Chun Hsiao, Alessandro Sorniotti in the Proceedings of the ACM SIGSAC Conference on computer and Communications Security 2013, pp. 259-270 Ciphertext-Policy Attribute-based Encryption (CPABE) is one of the most suitable technologies for data access control in cloud storage systems. This paper firstly presents the Attribute-based Encryption (ABE), secure deletion and secret-sharing schemes. Then we construct a CP-ABE model using secret-sharing methods to insure its security. At last, we propose an improved scheme on Data Access Control for Multi-Authority Cloud Storage Systems DAC-MACS to insure the security of the central authority (CA).

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A new combination prediction model for short-term wind farm output power based on meteorological data collected by WSN

International Journal of Control and Automation

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International Journal of Control and Automation 2014年第1期7卷 171-180页

作者： Ma, Li Li, Bo Yang, Zhen Bin Du, Jie Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science and Technology Nanjing 210044 China CMA Public Meteorological Service Centre Beijing 100081 China

The prediction of wind farm output power is considered as an effective way to increase the wind power capacity and improve the safety and economy of power system. It is one of the hot research topics on wind power. The wind farm output power is related to many factors such as wind speed, temperature, etc., which is difficult to be described by some mathematical expression. In this paper, Back Propagation (BP) neural network algorithm is respectively combined with genetic algorithm (GA) and particle swarm optimization (PSO) to establish the combination prediction model of the short-term wind farm output power based on meteorological data collected by Wireless Sensor network (WSN). The meteorological data is used to determine the input variables of the BP neural network. Meanwhile, the GA and the PSO is respectively used to adjust the value of BP's connection weight and threshold dynamically. Then the trained GA-BP and PSO-BP neural network are used to predict the wind power by combination method. The experiment results show that our method has better prediction capability compared with that using BP neural network, GA-BP neural network and PSO-BP neural network alone. © 2014 SERSC.

关键词： Wireless sensor networks

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Fast Mesh Reconstruction from Single View Based on GCN and Topology Modification

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computer Systems Science & engineering 2023年第5期45卷 1695-1709页

作者： Xiaorui Zhang Feng Xu Wei Sun Yan Jiang Yi Cao Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing210044China Department of Electrical and Computer Engineering University of WindsorWindsorONN9B 3P4Canada

3D reconstruction based on single view aims to reconstruct the entire 3D shape of an object from one *** existing methods reconstruct the mesh surface of complex objects,the surface details are difficult to predict and the reconstruction visual effect is poor because the mesh representation is not easily integrated into the deep learning framework;the 3D topology is easily limited by predefined templates and inflexible,and unnecessary mesh self-intersections and connections will be generated when reconstructing complex topology,thus destroying the surface details;the training of the reconstruction network is limited by the large amount of information attached to the mesh vertices,and the training time of the reconstructed network is too *** this paper,we propose a method for fast mesh reconstruction from single view based on Graph Convolutional network(GCN)and topology *** use GCN to ensure the generation of high-quality mesh surfaces and use topology modification to improve the flexibility of the ***,a feature fusion method is proposed to make full use of the features of each stage of the image *** use 3D open dataset ShapeNet to train our network and add a new weight parameter to speed up the training *** experiments demonstrate that our method can not only reconstruct object meshes on complex topological surfaces,but also has better qualitative and quantitative results.

关键词： 3D surface reconstruction deep learning GCN topology modification end-to-end framework

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Learning from crowdsourced labeled data: a survey

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Artificial Intelligence Review 2016年第4期46卷 543-576页

作者： Zhang, Jing Wu, Xindong Sheng, Victor S. School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China School of Computer Science and Information Engineering Hefei University of Technology Hefei 230009 China Department of Computer Science University of Central Arkansas Conway 72035 AR United States Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China

With the rapid growing of crowdsourcing systems, quite a few applications based on a supervised learning paradigm can easily obtain massive labeled data at a relatively low cost. However, due to the variable uncertainty of crowdsourced labelers, learning procedures face great challenges. Thus, improving the qualities of labels and learning models plays a key role in learning from the crowdsourced labeled data. In this survey, we first introduce the basic concepts of the qualities of labels and learning models. Then, by reviewing recently proposed models and algorithms on ground truth inference and learning models, we analyze connections and distinctions among these techniques as well as clarify the level of the progress of related researches. In order to facilitate the studies in this field, we also introduce open accessible real-world data sets collected from crowdsourcing systems and open source libraries and tools. Finally, some potential issues for future studies are discussed. © 2016, Springer Science+Business Media Dordrecht.

关键词： Crowdsourcing Ground truth inference Label quality Learning from crowds Learning model quality Multiple noisy labeling

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Digital continuity guarantee of electronic record based on data usability in big data environment 4th

Digital continuity guarantee of electronic record based on d...

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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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