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Novel Intrusion Detection Method based on Triangular Matrix Factorization
QI Yingchun,NIU Ling 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.7
In order to deal with the issue of network attacks and enhance the security of the network environment, intrusion detection is gaining more and more attention all over the world. In this paper, a novel intrusion detection method based on improved triangular matrix factorization is presented. As a type of famous mathematical tool, triangular matrix factorization has a good ability to reduce the large amount of high dimensional data. However, the traditional triangular matrix factorization has its inherent drawbacks such as the difficulty of setting the parameter adaptively, so the model of an improved version of triangular matrix factorization together with its concrete algorithm is proposed in this paper firstly. Then, improved triangular matrix factorization is employed to convert the high dimensional data of the network into low dimensional vectors of several matrices, with which the anomaly detection can be realized. Experimental results indicate that the proposed method is promising, and it does significantly enhance the detection accuracy and computational efficiency compared with other current popular ones.
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Image Retrieval Based on Deep Belief Networks
Sun Ting,Qi Yingchun 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.1
According to the local and global feature of image, matching the image from a lot image library, this is the image retrieval task; however, the image retrieval need to search the information in the database, we need to find a method for efficient information retrieval. Deep belief network according to the characteristic of the initiative, through the method of training a multilayer neural network to process large amounts of data, and it is very efficient, in this article, as to the characteristics of image local features and global features, it gives a deep belief network image retrieval algorithm, the experiment verify the effectiveness of the algorithm.
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Wireless Sensor Network 3-Dimensional Positioning Method
Yiran Wang,Yingchun Qi 보안공학연구지원센터 2015 International Journal of Smart Home Vol.9 No.5
In wireless sensor network, determine the position of the node position or events is very important to its surveillance activities, however, in the traditional wireless sensor network, are using two-dimensional spatial positioning technology, aiming at this problem, this article will wireless sensor network (WSN) 2 d algorithm is extended to 3 d space, analyzes the main factors affecting the positioning accuracy of wireless sensor network. In order to further improve the stability and precision of the algorithm, by introducing the Newton's method, gives the quasi-newton three-dimensional node localization hybrid localization algorithm. The simulation analysis shows that the proposed hybrid algorithm can under the same conditions with high positioning accuracy and stability, at the same time the CRLB are obtained. The simulation results show that the proposed algorithm can get g Latin American community, simulation analysis of the localization method is effective
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Medical Image Fusion via Non-Subsampled Contourlet Transform
Niu Ling,Qi Yingchun 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.7
Due to the obvious advantages, the technology of medical imaging has been widely utilized in the medical areas. Commonly, the medical images of different imaging mechanism are able to guide the radiologist for the precise diagnosis of disease and for more effective interventional treatment procedures. Consequently, the fusion of different medical images of the same scene is necessary. This paper proposes a novel fusion technique for medical images based on non-subsampled contourlet transform (NSCT). Due to the better competence of image information capturing, NSCT is utilized to conduct the multi-scale and multi-directional decompositions of source images. In addition, the models of both region average energy and region coefficient deviation are used for the fusion for low-frequency sub-images and high-frequency ones, respectively. In comparison with several current typical fusion techniques, the proposed one has remarked superiorities in terms of both subjective and objective evaluations.
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