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2nd IEEE International Conference on computer and Communications, ICCC 2016

作者： Zhou, Yu Zhao, Bo Han, Jin Jun, Zheng School of Computer Science and Software Engineering East China Normal University Shanghai China School of Software and Microelectronics Peking University Beijing China Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology China

ISBN: (纸本)9781467390262

Compared with traditional cryptography, biometric cryptosystems provide more convenient and safe protection of keys. In this paper, an effective scheme for biometric cryptosystems based on the intersections of hyper-plane and hashed discrete space is proposed. Only genuine feature vectors, which are located on the hyper-plane, find the correct solution. Several tricks are provided to ensure the security of proposed scheme. Experiments have shown that our method achieved approximate performance compared with one of the latest methods based on fuzzy vault. However, our method is less complex than fuzzy vault based methods. © 2016 IEEE.

关键词： Cryptography

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Classification based on brain storm optimization algorithm 11th

Classification based on brain storm optimization algorithm

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Xue, Yu Tang, Tao Ma, Tinghuai Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9789811036101

As one of the important issues of data classification, classification has attracted the attention of many researchers in the field of data mining. Different from clustering research issues, in classification research issues, evolutionary clustering algorithms (EAs) were only used to improve the performance of classifiers either by optimizing the parameters or structure of the classifiers, or by pre-processing the inputs of the classifiers. Lots of evolutionary algorithms are employed to solve unsupervised classification, i.e., clustering. In this article, we will create a new mathematical model for supervised classification problem and use brain storm optimization algorithm (BSO) to search the global optimal solution, which resolved the problem of supervised classification with new ideas. The main objective is to find a better method. By using a new classification algorithm based on BSO, we are looking forward to optimizing the result. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Storms

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A practical RFID grouping authentication protocol in multiple-tag arrangement with adequate security assurance 18

A practical RFID grouping authentication protocol in multipl...

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18th International Conference on Advanced Communications Technology, ICACT 2016

作者： Shen, Jian Tan, Haowen Ren, Yongjun Liu, Qi Wang, Baowei Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology China Jiangsu Technology and Engineering Center of Meteorological Sensor Network Nanjing University of Information Science and Technology China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology China School of Computer and Software Nanjing University of Information Science and Technology China

ISBN: (纸本)9788996865063

Radio Frequency Identification (RFID) is considered to be an authentication technology of great potential. Due to the bright future of low-cost RFID tags in practical situations, the authentication towards multiple tags and tag groups has become the research hotspot. However, there are many concerns about the security risks and privacy issues in lightweight RFID authentication scenarios. Many researches achievements have been made focusing on the existence of single tag in one object, while the arrangement that multiple tags attached to one object is out of consideration. In this paper, we propose a practical RFID grouping authentication protocol in multiple-tag arrangement with adequate security assurance. In our assumption, one object to be authenticated is attached with a group of RFID tags. The feedback towards various cases of the RFID tags is timely provided, which is necessary in practical situations. Additionally, the probable position and status of the object can be ascertained with a number of tags combined with the object. Moreover, the protocol is proved to offer enough security assurances and have resistance to various attacks under the security analysis. The regular operation of RFID system will not be severely damaged by the incidents occurred during the authentication process. © 2016 Global IT Research Institute (GiRI).

关键词： Authentication

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Splicing Detection for Color Images based on QDCT Markov

Splicing Detection for Color Images based on QDCT Markov

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第十三届全国信息隐藏暨多媒体信息安全学术大会

作者： WANG Jinwei LIU Renfeng Jiangsu Network Monitoring Engineering Center Department of Computer and SoftwareNanjing University of Information Science and Technology Nanjing

With the increasing amount of splicing images, many detecting methods of splicing images are *** this paper, we propose a splicing detection scheme based on quaternion discrete cosine transform (QDCT).Compared to most of existing methods, the proposed scheme uses the correlation among three channels of the color image, hence decreases the loss of the image's inherent color ***, Markov features from color images are extracted in QDCT ***, SVM is used to detect the splicing *** accuracy of the proposed scheme reaches 98.75% and 96.78% in CASIA1 and CASIA2, *** experimental result is better than most of the existing methods.

关键词： splicing detection color images QDCT Markov

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Multi-objective layout optimization of a satellite module using the Wang-Landau sampling method with local search

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Frontiers of Information Technology & Electronic engineering 2016年第6期17卷 527-542页

作者： Jing-fa LIU Liang HAO Gang LI Yu XUE Zhao-xia LIU Juan HUANG Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science&TechnologyNanjing 210044China School of Computer&Software Nanjing University of Information Science&TechnologyNanjing 210044China School of Mathematics and Statistics Nanjing University of Information Science&TechnologyNanjing 210044China Office of lnformationization Construction and Management Nanjing University of Information Science&TechnologyNanjing 210044China

The layout design of satellite modules is considered to be NP-hard. It is not only a complex coupled system design problem but also a special multi-objective optimization problem. The greatest challenge in solving this problem is that the function to be optimized is characterized by a multitude of local minima separated by high-energy barriers. The Wang-Landau(WL) sampling method, which is an improved Monte Carlo method, has been successfully applied to solve many optimization problems. In this paper we use the WL sampling method to optimize the layout of a satellite module. To accelerate the search for a global optimal layout, local search(LS) based on the gradient method is executed once the Monte-Carlo sweep produces a new layout. By combining the WL sampling algorithm, the LS method, and heuristic layout update strategies, a hybrid method called WL-LS is proposed to obtain a final layout scheme. Furthermore, to improve significantly the efficiency of the algorithm, we propose an accurate and fast computational method for the overlapping depth between two objects(such as two rectangular objects, two circular objects, or a rectangular object and a circular object) embedding each other. The rectangular objects are placed orthogonally. We test two instances using first 51 and then 53 objects. For both instances, the proposed WL-LS algorithm outperforms methods in the literature. Numerical results show that the WL-LS algorithm is an effective method for layout optimization of satellite modules.

关键词： Packing Layout design Satellite module Wang-Landau algorithm

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Towards Efficient Content-aware Search over Encrypted Outsourced Data in Cloud

Towards Efficient Content-aware Search over Encrypted Outsou...

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Annual IEEE International Conference on computer Communications

作者： Zhangjie Fu Xingming Sun Sai Ji Guowu Xie College of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Department of Computer Science and Engineering University of California Riverside

ISBN: (纸本)9781467399548

With the increasing adoption of cloud computing, a growing number of users outsource their datasets into cloud. The datasets usually are encrypted before outsourcing to preserve the privacy. However, the common practice of encryption makes the effective utilization difficult, for example, search the given keywords in the encrypted datasets. Many schemes are proposed to make encrypted data searchable based on keywords. However, keyword-based search schemes ignore the semantic representation information of users retrieval, and cannot completely meet with users search intention. Therefore, how to design a content-based search scheme and make semantic search more effective and context-aware is a difficult challenge. In this paper, we proposed an innovative semantic search scheme based on the concept hierarchy and the semantic relationship between concepts in the encrypted datasets. More specifically, our scheme first indexes the documents and builds trapdoor based on the concept hierarchy. To further improve the search efficiency, we utilize a tree-based index structure to organize all the document index vectors. Our experiment results based on the real world datasets show the scheme is more efficient than previous scheme. We also study the threat model of our approach and prove it does not introduce any security risk.

关键词： Dataset outsourcing Scheme Consumers CLOUDS Clouds Semantics Context awareness Searches

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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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Combiningwavelet transform and LBP related features for fingerprint liveness detection

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2016年第3期43卷 290-298页

作者： Xia, Zhihua Yuan, Chengsheng Sun, Xingming Sun, Decai Rui, L. Jiangsu Engineering Center of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology School of Computer and SoftwareNanjing University of Information Science and Technology Nanjing China College of Information Science and Technology Bohai University China

Fingerprint authentication system may verify the identity of the user according to the features of fingerprint. It has been widely used in government departments and national security departments. However, there are some security and privacy problems: Fingerprint authentication system may be easily tricked by fake fingers which are produced through using common artificial materials, such as silicon, wood glue and latex. Thus, designing a fingerprint liveness detection module is necessary for authentication system. In this paper, in order to obtain the optimal set of features and recognize fake fingerprints, a new software-based liveness detection approach using a novel fingerprint parameterization based on wavelet transform and local binary pattern (LBP) related features is applied. The performance of our proposed approach has been evaluated through a comparison with several state-of-the-art techniques for fingerprint liveness detection. In addition, the liveness detection method presented in this paper has an extra advantage over previously studied techniques, since only a fingerprint image is needed to judge whether it is real or fake. Experiments have been carried out by adopting standard databases which are taken from the Liveness Detection Competition 2011 and 2013. Besides that, we have also analyzed the performance of our method for the different combination of wavelet decomposition coefficients during the process of training. Finally, classification accuracy of feature vectors is predicted based on a SVM classifier. Experimental results demonstrate that our method can detect the fingerprint liveness with higher classification accuracy. In addition, this study also confirms that multi- resolution analysis is a useful tool for the extraction of texture feature during fingerprint images processing.

关键词： Support vector machines

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Multi-keyword ranked search over encrypted cloud data supporting semantic extension

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2016年第8期11卷 107-120页

作者： Xia, Zhihua Chen, Li Sun, Xingming Liu, Jianxiao Jiangsu Engineering Center of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology School of Computer & Software Nanjing University of Information Science & Technology Nanjing210044 China College of informatics Huazhong Agricultural University Hubei China

With the emergence of cloud computing, many data owners outsource their local data to cloud server so as to enjoy high-quality data storage services. For the protection of data privacy, sensitive data has to be encrypted before outsourcing, which makes effective data utilization a challenging task. Although existing searchable encryption technologies enable data users to conduct secure search over encrypted data, the functionality of these schemes need to be further improved. In this paper, we construct a secure and efficient multi-keyword ranked search scheme which supports both the semantic extension search and the multi-keyword ranked search. The semantic extension is achieved through the mutual information statistical analysis of keywords. And the multi-keyword ranked search is achieved through a balanced binary tree whose nodes are the vectors of term frequency (TF) values. The splitting operation and secure transformation are utilized to encrypt the vectors of index and query. Note that, the encrypted vectors can be well used to calculate accurate relevance scores. Phantom terms are added to the index vector to blind the search results to resist statistical attacks. Due to the use of tree-based index structure, the proposed scheme can achieve the sub-linear search time. Finally, the experiments are conducted to demonstrate the efficiency of the proposed scheme. © 2016 SERSC.

关键词： Vectors

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Twice-Hadamard-CNOT attack on Li et al.＇s fault-tolerant quantum private comparison and the improved scheme

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Frontiers of physics 2015年第2期10卷 73-78页

作者：季赛王芳刘文杰袁晓敏 Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science & Technology Nanjing 210044 China

Recently, Li et al. presented a two-party quantum private comparison scheme using Greenberger-- Horne-Zeitinger （GHZ） states and error-correcting code （ECC） lint. J. Theor. Phys. 52, 2818 （2013）], claiming it is fault-tolerant and could be performed in a non-ideal scenario. However, there ex- ists a fatal loophole in their private comparison scheme under a special attack, namely the twice- Hadamard-CNOT attack. Specifically, a malicious party may intercept the other party＇s particles and execute Hadamard operations on the intercepted particles as well as on his or her own particles. Then, the malicious party could sequentially perform a controlled-NOT （CNOT） operation between intercepted particles and the auxiliary particles, as well as between his or her own particles and the auxiliary particles prepared in advance. By measuring the auxiliary particles, the secret input will be revealed to the malicious party without being detected. For resisting this special attack, a feasible improved scheme is proposed by introducing a permutation operator before the third party （TP） sends the particle sequences to each participant.

关键词： quantum private comparison GHZ state twice-Hadamard-CNOT attack improvedscheme

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