Cong Wang

Beijing University of Posts and Telecommunications, Peping, Beijing, China

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Publications (51)27.84 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, a class of protocols for quantum private comparison is investigated. The main feature is that the symmetry of quantum states is utilized. First of all, we design a new protocol for quantum private comparison via the $$\chi $$¿-type state as a special example. Then, through the in-deep research and analysis on the quantum carrier, it is found that lots of quantum states with the symmetrical characteristic can be utilized to perform the protocol successfully. It is an attractive advantage in the practical application. What is more, two players are only required to be equipped with the unitary operation machines. It means that our protocols can easily be realized and have a broad scope of application. Finally, the analyses on the protocols' security, which are mainly ensured by the symmetry of quantum states and the property of the decoy state, are given in detail.
    Quantum Information Processing 01/2014; 13(1):85-100. · 1.75 Impact Factor
  • Gang Xu, Cong Wang, Yi-Xian Yang
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    ABSTRACT: We propose a new protocol of hierarchical quantum information splitting (HQIS) via two four-qubit cluster state. In the protocol, a boss can asymmetrically distribute an arbitrary two-qubit state, which has not been investigated by the previous papers, to the distant agents in a network. The asymmetric distribution leads to that the agents' authorities for getting the secret state are hierarchical. In other word, they have different authorities for the boss's secret state. Moreover, the symmetry feature of cluster state reflects our protocol will have a better extendibility. Thus, we further propose a multiparty HQIS protocol. In our HQIS protocol, the agents only need the single-qubit measurement, which is an appealing advantage in practically implementation. Meanwhile, the present protocol can be modified to implement the threshold-controlled teleportation.
    Quantum Information Processing 01/2014; 13(1):43-57. · 1.75 Impact Factor
  • Cong Wang, Gang Xu, Yi-xian Yang
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    ABSTRACT: In this paper, we carry out an in-depth analysis of the quantum private comparison (QPC) protocol with the semi-honest third party (TP). The security of QPC protocol using the EPR pairs is re-examined. Unfortunately, we find that TP can use the fake EPR pairs to steal all the secret information. Furthermore, we give two simple and feasible solutions to improve the original QPC protocol. It is shown that the improved protocol is secure, which can resist various kinds of attacks from both the outside eavesdroppers and the inside participants, even the semi-honest TP.
    International Journal of Quantum Information 09/2013; 11(04). · 0.92 Impact Factor
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    ABSTRACT: In this paper, we explore the issue that how many messages can be transmitted through one scalar chaotic time series. A scheme is proposed for modulating multiple messages into the system. Based on the adaptive parameter estimation method, provided that some special conditions are satisfied, such as the long-time persistent excitation condition or the long-time linearly independent condition, the carried information could be recovered at the receiver. This scheme has potential application in chaotic optical communication (COC). Its feasibility and effectiveness are demonstrated by numerical examples.
    The European Physical Journal B 02/2013; 86(2):39. · 1.28 Impact Factor
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    ABSTRACT: Users of a Web site usually perform their interest-oriented actions by clicking or visiting Web pages, which are traced in access log files. Clustering Web user access patterns may capture common user interests to a Web site, and in turn, build user profiles for advanced Web applications, such as Web caching and prefetching. The conventional Web usage mining techniques for clustering Web user sessions can discover usage patterns directly, but cannot identify the latent factors or hidden relationships among users' navigational behaviour. In this paper, we propose an approach based on a vector space model, called Random Indexing, to discover such intrinsic characteristics of Web users' activities. The underlying factors are then utilised for clustering individual user navigational patterns and creating common user profiles. The clustering results will be used to predict and prefetch Web requests for grouped users. We demonstrate the usability and superiority of the proposed Web user clustering approach through experiments on a real Web log file. The clustering and prefetching tasks are evaluated by comparison with previous studies demonstrating better clustering perfor-mance and higher prefetching accuracy.
    Knowledge and Information Systems 10/2012; 33(1):89-115. · 2.23 Impact Factor
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    ABSTRACT: On the basis of the properties of the Jordan matrix, we proposed a secret sharing scheme which can realize both the (t,n)(t,n) threshold and the adversary structure and share a large secret while each participant has a short share. At the same time, the scheme can prevent the participants from cheating. The shares can be kept secret in the process of reconstruction and do not need to be renewed when the shared secret is changed. If nn participants want to share a large secret using a short share such that tt or more participants can reconstruct the shared secret and there are some subsets that each contain at least tt participants that cannot reconstruct the shared secret, our scheme will be effective.
    Computers & Mathematics with Applications 08/2012; 64(4):611–615. · 2.07 Impact Factor
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    ABSTRACT: journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright
    Applied Soft Computing 08/2012; 12(8):2387-2393. · 2.68 Impact Factor
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    ABSTRACT: Clustering divides data into meaningful or useful groups (clusters) without any prior knowledge. It is a key technique in data mining and has become an important issue in many fields. This article presents a new clustering algorithm based on the mechanism analysis of chaotic ant swarm (CAS). It is an optimization methodology for clustering problem which aims to obtain global optimal assignment by minimizing the objective function. The proposed algorithm combines three advantages into one: finding global optimal solution to the objective function, not sensitive to clusters with different size and density and suitable to multi-dimensional data sets. The quality of this approach is evaluated on several well-known benchmark data sets. Compared with the popular clustering method named k-means algorithm and the PSO-based clustering technique, experimental results show that our algorithm is an effective clustering technique and can be used to handle data sets with complex cluster sizes, densities and multiple dimensions.
    Applied Soft Computing. 08/2012; 12(8):2387–2393.
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    ABSTRACT: Clustering divides data into meaningful or useful groups (clusters) without any prior knowledge. It is a key technique in data mining and has become an important issue in many fields. This article presents a new clustering algorithm based on the mechanism analysis of Bacterial Foraging (BF). It is an optimization methodology for clustering problem in which a group of bacteria forage to converge to certain positions as final cluster centers by minimizing the fitness function. The quality of this approach is evaluated on several well-known benchmark data sets. Compared with the popular clustering method named k-means algorithm, ACO-based algorithm and the PSO-basedclustering technique, experimental results show that the proposed algorithm is an effective clustering technique and can be used to handle data sets with various cluster sizes, densities and multiple dimensions.
    Journal of Intelligent Information Systems 04/2012; 38(2):321-341. · 0.83 Impact Factor
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    ABSTRACT: Clustering divides data into meaningful or useful groups (clusters) without any prior knowledge. It is a key technique in data mining and has become an important issue in many fields. This article presents a new clustering algorithm based on the mechanism analysis of Bacterial Foraging (BF). It is an optimization methodology for clustering problem in which a group of bacteria forage to converge to certain positions as final cluster centers by minimizing the fitness function. The quality of this approach is evaluated on several well-known benchmark data sets. Compared with the popular clustering method named k-means algorithm, ACO-based algorithm and the PSO-based clustering technique, experimental results show that the proposed algorithm is an effective clustering technique and can be used to handle data sets with various cluster sizes, densities and multiple dimensions.
    Journal of Intelligent Information Systems 01/2011; · 0.83 Impact Factor
  • Jianyi Liu, Li Zhu, Cong Wang
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    ABSTRACT: A query suggestion algorithm is presented based on query logs mining and semantic. First construct a weighted Query-URL bipartite graph from query log data. Then compute the semantic similarity of queries by distance of queries nodes and synonymy similarity to extracting semantic related queries based on graph path. Experiments show that the algorithm is more effective than substring extending algorithm and log mining algorithm in recall and precision.
    01/2011;
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    ABSTRACT: In this paper we present a novel technique to capture Web users' behaviour based on their interest-oriented actions. In our approach we utilise the vector space model Random Indexing to identify the latent factors or hidden relationships among Web users' navigational behaviour. Random Indexing is an incremental vector space technique that allows for continuous Web usage mining. User requests are modelled by Random Indexing for individual users' navigational pattern clustering and common user profile creation. Clustering Web users' access patterns may capture common user interests and, in turn, build user profiles for advanced Web applications, such as Web caching and prefetching. We present results from the Web user clustering approach through experiments on a real Web log file with promising results. We also apply our data to a prefetching task and compare that with previous approaches. The results show that Random Indexing provides more accurate prefetchings.
    New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Shenzhen, China, May 24-27, 2011, Revised Selected Papers; 01/2011
  • Cong Wang, Jianyi Liu
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    ABSTRACT: Various approaches are presented to solve the spreading spam problem. However, most of these approaches can not flexibly and dynamically adapt to spam. This paper proposes a novel approach to counter spam based on trusted behavior recognition during transfer sessions. A behavior recognition of email transfer patterns which enables normal servers to detect malicious connections before email body delivered, contributes much to save network bandwidth wasted by spam emails. An integrated Anti-Spam framework is designed combining the trusted behavior recognition with Bayesian Analysis. The effectiveness of both the trusted Behavior recognition and the integrated filter are evaluated.
    Web Information Systems and Mining (WISM), 2010 International Conference on; 11/2010
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    ABSTRACT: This article devises a clustering technique for detecting groups of Web users from Web access logs. In this technique, Web users are clustered by a new clustering algorithm which uses the mechanism analysis of chaotic ant swarm (CAS). This CAS based clustering algorithm is called as CAS-C and it solves clustering problems from the perspective of chaotic optimization. The performance of CAS-C for detecting Web user clusters is compared with the popular clustering method named k-means algorithm. Clustering qualities are evaluated via calculating the average intra-cluster and inter-cluster distance. Experimental results demonstrate that CAS-C is an effective clustering technique with larger average intra-cluster distance and smaller average inter-cluster distance than k-means algorithm. The statistical analysis of resulted distances also proves that the CAS-C based Web user clustering algorithm has better stability. In order to show the utility, the proposed approach is applied to a pre-fetching task which predicts user requests with encouraging results.
    Nonlinear Dynamics 08/2010; 61(3):347-361. · 3.01 Impact Factor
  • Xuyan Tu, Cong Wang, Ruifan Li
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    ABSTRACT: Recently, neuroscientists emphasized the manifold ways of perception and proposed Isomap for manifold learning. Favorable results have been achieved using Isomap for data description and visualization. However, since the unsupervised Isomap is developed based on minimizing the reconstruction error with multidimensional scaling (MDS) without using the class specific information, it may not be optimal from the perspective of pattern classification. Therefore, an improved version of Isomap, namely SKFD-Isomap, is proposed using class information to construct the neighborhood, and kernel Fisher discriminant (KFD) to achieve the nonlinear embedding. A nearest neighbor classifier is then applied in the subspace for classification. Experimental results show the effectiveness of the proposed approach. Full Text at Springer, may require registration or fee
    International Federation for Information Processing Digital Library; Artificial Intelligence Applications and Innovations;. 01/2010;
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    ABSTRACT: The purpose of TPM authorization mechanism is to authenticate the owner of a TPM or to authorize the use of an instance of a TPM capability. The TPM treats knowledge of the AuthData as complete proof of ownership of the entity. The main specification defines an authorized user must provide the parent key AuthData before loading its child key and provide the child key AuthData before using it. All users had to manage more and more AuthData values with the rapid increasing of keys. We have designed and analyzed a new hierarchical key AuthData management Scheme for trusted platform. In our scheme, each authorized user just needs to keep one single AuthData, and the computational requirement for generating or deriving an AuthData is just at the level of modular exponentiation and hash operation. Moreover, the lower level AuthData values can be easily derived from higher level AuthData along the same chain, but it is infeasible reversely. Even if more lower level AuthData values can’t be colluded to calculate the higher level AuthData. The result of performance evaluation and security analysis demonstrates that our proposed method is feasible and security.
    Multimedia Information Networking and Security, International Conference on. 01/2010;
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    ABSTRACT: Keyword extraction is an important application in the area of information technology. Automatic keyword extraction can help people know what is the article primarily talking about without reading the long passage carefully. This paper mainly introduced a keyword extraction algorithm using pagerank on Synonym. Firstly, the content in a single document is represented as a weighted synonym co-occurrence network. Then pagerank algorithm is using on this synonym network to assign the rank for each synonym group. Finally, several synonym groups with top rank are picked out as keywords of the document. The algorithm is tested on the corpus of blog pages, and the experiment results prove practical and effective.
    01/2010;
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    ABSTRACT: A large and growing number of web pages display contextual advertising based on keywords automatically extracted from the text of the page, and it has been become a rapidly growing business in recent years. We describe a system that learns how to extract keywords from web pages for advertisement targeting. Firstly a text network for a single webpage is build, then PageRank is applied in the network to decide on the importance of a word, finally top-ranked words are selected as keywords of the webpage. The algorithm is tested on the corpus of blog pages, and the experiment result proves practical and effective.
    Web Information Systems and Mining - International Conference, WISM 2010, Sanya, China, October 23-24, 2010. Proceedings; 01/2010
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    ABSTRACT: This article devises a clustering technique for detecting groups of Web users from Web access logs. In this technique, Web users are clustered by a new clustering algorithm which uses the mechanism analysis of chaotic ant swarm (CAS). This CAS based clustering algorithm is called as CAS-C and it solves clustering problems from the perspective of chaotic optimization. The performance of CAS-C for detecting Web user clusters is compared with the popular clustering method named k-means algorithm. Clustering qualities are evaluated via calculating the average intra-cluster and inter-cluster distance. Experimental results demonstrate that CAS-C is an effective clustering technique with larger average intra-cluster distance and smaller average inter-cluster distance than k-means algorithm. The statistical analysis of resulted distances also proves that the CAS-C based Web user clustering algorithm has better stability. In order to show the utility, the proposed approach is applied to a pre-fetching task which predicts user requests with encouraging results. KeywordsClustering-Chaotic ant swarm (CAS)-Web access logs-Web user clustering
    Nonlinear Dynamics 01/2010; 61(3):347-361. · 3.01 Impact Factor
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    ABSTRACT: Similar to conventional NAT technology, NAT-PT gateways break traditional TCP/IP's end-to-end argument property which result in IPSec can not be applied in NAT-PT environment, and would fall flat when the pool of IPv4 addresses is exhausted. A solution by adding IP transform message, modifying the address mapping tables and session tables, using port transform strategy with inner host computer character in IKE negotiation was proposed which implemented bidirectional communication among the nodes of IPv4 and IPv6, and made NAT-PT compatible with ESP and AH. Performance analysis shows that the proposed scheme is feasible and effective.
    Network Infrastructure and Digital Content, 2009. IC-NIDC 2009. IEEE International Conference on; 12/2009

Publication Stats

78 Citations
27.84 Total Impact Points

Institutions

  • 2003–2014
    • Beijing University of Posts and Telecommunications
      • • School of Software Engineering
      • • State Key Laboratory of Switching and Networking
      • • Department of Information Engineering
      Peping, Beijing, China
  • 2012
    • Chinese Academy of Sciences
      Peping, Beijing, China
  • 2005
    • University of Science and Technology, Beijing
      Peping, Beijing, China
    • Beijing Institute Of Technology
      Peping, Beijing, China