In order to set up universal criteria for measuring and evaluating network security and survivability,this paper presents a novel index *** index system was built according to the Protection-Detection-Response (PDR) s...
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ISBN:
(纸本)9781457713675
In order to set up universal criteria for measuring and evaluating network security and survivability,this paper presents a novel index *** index system was built according to the Protection-Detection-Response (PDR) security model and the Resistance-Recognition-Recovery (R3) survivability principle of network in the presence of attacks,failures,or *** all the 24 metrics in the index system are used to cover the characters of network security and *** index system is organized with threelayer structure like a *** first layer,*** node,is called network security and *** second layer includes three indexes,*** metric,awareness metric,and recovery *** third layer includes 20 indexes abstracted from different network layers,survivability characters,and survivability methods and so *** novel index system is quantifiable,universal,consistent,compatible,and fine-scale,which is suitable for different network *** last,a case for how to using these index system to measure network security and survivability is also given.
The image patches learned by recent works are usually only bar-like or Gabor-like patterns. However those simple patterns are not meaningful enough to capture higher level information. In this study, we try to learn m...
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The image patches learned by recent works are usually only bar-like or Gabor-like patterns. However those simple patterns are not meaningful enough to capture higher level information. In this study, we try to learn more complex image patterns from unaligned images. We propose Scale And Shift Invariant Sparse Coding (SASISC), which aligns basis patches at proper locations and scales to reconstruct the whole image. The experiment results on unaligned images show that SASISC can explain the images much better than the original sparse coding, and can extract more complex image patterns.
FOX is a family of symmetric block ciphers from MediaCrypt AG that helps to secure digital media, communications, and storage. The high-level structure of FOX is the so-called (extended) Lai–Massey scheme. This paper...
FOX is a family of symmetric block ciphers from MediaCrypt AG that helps to secure digital media, communications, and storage. The high-level structure of FOX is the so-called (extended) Lai–Massey scheme. This paper presents a detailed fault analysis of the block cipher FOX64, the 64-bit version of FOX, based on a differential property of two-round Lai–Massey scheme in a fault model. Previous fault attack on FOX64 shows that each round-key (resp. whole round-keys) could be recovered through 11.45 (resp. 183.20) faults on average. Our proposed fault attack, however, can deduce any round-key (except the first one) through 4.25 faults on average (4 in the best case), and retrieve the whole round-keys through 43.31 faults on average (38 in the best case). This implies that the number of needed faults in the fault attack on FOX64 can be significantly reduced. Furthermore, the technique introduced in this paper can be extended to other series of the block cipher family FOX.
The mission critical network infrastructures are facing potential large region threats, both intentional (like EMP attack, bomb explosion) and natural (like earthquake, flooding). The available research on region fail...
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Robot navigation has been of great importance especially under unknown or keep-changing environment. In order to solve this kind of problems, many algorithms have been brought up. D*Lite is generally considered as one...
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Visual cryptography scheme (VCS) is a secure method that encrypts a secret image by subdividing it into shadow images. Due to the nature of encryption VCS is categorized into two types: the deterministic VCS (DVCS...
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Visual cryptography scheme (VCS) is a secure method that encrypts a secret image by subdividing it into shadow images. Due to the nature of encryption VCS is categorized into two types: the deterministic VCS (DVCS) and the probabilistie VCS (PVCS). For the DVCS, we use m (known as the pixel expansion) subpixels to represent a secret pixel. The PVCS uses only one subpixel to represent a secret pixel, while the quality of reconstructed image is degraded. A well-known construction of (k, n)-PVCS is obtained from the (k, n)-DVCS. In this paper, we show another construction of (k, n)-PVCS by extending the (k, k)-PVCS.
Depth maps are used for synthesis virtual view in free-viewpoint television (FTV) systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts ...
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Depth maps are used for synthesis virtual view in free-viewpoint television (FTV) systems. When depth maps are derived using existing depth estimation methods, the depth distortions will cause undesirable artifacts in the synthesized views. To solve this problem, a 3D video quality model base depth maps (D-3DV) for virtual view synthesis and depth map coding in the FTV applications is proposed. First, the relationships between distortions in coded depth map and rendered view are derived. Then, a precisely 3DV quality model based depth characteristics is develop for the synthesized virtual views. Finally, based on D-3DV model, a multilateral filtering is applied as a pre-processed filter to reduce rendering artifacts. The experimental results evaluated by objective and subjective methods indicate that the proposed D-3DV model can reduce bit-rate of depth coding and achieve better rendering quality.
Selecting the best views for 3D objects is useful for many applications. However, with the existing methods applied in CAD models, the results neither exhibit the 3D structures of the models fairly nor conform to huma...
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Selecting the best views for 3D objects is useful for many applications. However, with the existing methods applied in CAD models, the results neither exhibit the 3D structures of the models fairly nor conform to human's browsing habits. In this paper, we present a robust method to generate the canonical views of CAD models, and the above problem is solved by considering the geometry and visual salient features simultaneously. We first demonstrate that for a CAD model, the three coordinate axes can be approximately determined by the scaled normals of its faces, such that the pose can be robustly normalized. A graph-based algorithm is also designed to accelerate the searching process. Then, a convex hull based method is applied to infer the upright orientation. Finally, four isometric views are selected as candidates, and the one whose depth image owns the most visual features is selected. Experiments on the Engineering Shape Benchmark (ESB) show that the views generated by our method are pleasant, informative and representative. We also apply our method in the calculation of model rectilinearity, and the results demonstrate its high performance.
Color mapping plays a critical role in visualization of time-varying data and also sets a challenge for researchers due to the consistency of mapping and great changes in time-varying data. In order to solve this prob...
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Color mapping plays a critical role in visualization of time-varying data and also sets a challenge for researchers due to the consistency of mapping and great changes in time-varying data. In order to solve this problem and generate feature-prominent animation, we present a two phase optimization technique using bilateral filtering and global energy functions. In the first phase, for each time step, we use a weighted mapping function which combines linear mapping and feature histogram. In the second phase, an optimization function taking global color mapping and minimum color difference into consideration is designed. So users can clearly distinguish between data in variable time steps and easily understand the corresponding relationships between different structures. The experiments' results show that our method can achieve high quality visualization for both static and time-varying data.
Holistic-based methods, especially principal component analysis(PCA) and linear discriminant analysis(LDA), are very popularly used in face recognition. In last several years, the direct LDA(D-LDA) method was suggeste...
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Holistic-based methods, especially principal component analysis(PCA) and linear discriminant analysis(LDA), are very popularly used in face recognition. In last several years, the direct LDA(D-LDA) method was suggested to overcome the so-call “small simple size” problem. Besides, the researchers suggest bidirectional PCA(BDPCA) method, which may be more real-time and effective than PCA, and proposed BDPCA plus LDA (BDPCA+LDA). In the same way, we suggest bidirectional D-LDA(BDDLDA) should be faster than D-LDA, and proposed BDPCA plus BDDLDA (BDPCA+BDDLDA). In this paper, we present a real-time face recognition system for operating system authentication based on BDPCA+BDDLDA. A face database, which was collected with a CCD camera on the laptop, is used to evaluate this system. Experimental results show that this practical system is real-time and effective.
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