{"title":"An Improved Image Encryption Scheme Based on Line Maps","authors":"Juan Li, Yong Feng, Xuqiang Yang","doi":"10.1109/IAS.2009.67","DOIUrl":"https://doi.org/10.1109/IAS.2009.67","url":null,"abstract":"In order to avoid the flaw while keeping all the merits of image encryption scheme based on line maps, an improved image encryption scheme is proposed, which extended the original 2D scheme to 3D. An image with size N×M is firstly depicted by a 3D bit matrix, and then it is supposed as composed of 8×M vectors with size N. Line maps are used to stretch the vectors to an array, while the fold map is used to transform the array to a same sized 3D matrix. Simulation results show that the improved image encryption scheme complete pixel permutation and confusion simultaneously, it enhance the security of the original cipher.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127351588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Infrared Face Recognition Based on Radiant Energy and Curvelet Transformation","authors":"Zhihua Xie, Shiqian Wu, Guodon Liu, Zhijun Fang","doi":"10.1109/IAS.2009.24","DOIUrl":"https://doi.org/10.1109/IAS.2009.24","url":null,"abstract":"In this paper, a infrared face recognition method using radiant energy conversion and Curvelet transformation is proposed. Firstly, to get the stable feature of thermal face, thermal images are converted into radiant energy images according to Stefan-Boltzmann's law. Secondly, Curvelet transform has better directional and edge representation abilities than widely used wavelet transformation and other classic transformations. Inspired by these attractive attributes of Curvelets in sparse representation of the images, we introduce the idea of decomposing images into their curvelet subbands to extract the principal representative feature, which saves the computational complexity and storage units. Finally, the nearest neighbor classifier is chosen to get the system recognition result. The experiments illustrate that compared with traditional PCA based systems, the proposed system has better performance and requires fewer computations and memory units.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127355122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A New Authenticated Key Agreement Protocol for Wireless Mobile Networks","authors":"Shin-Jia Hwang, M. Chai","doi":"10.1109/IAS.2009.58","DOIUrl":"https://doi.org/10.1109/IAS.2009.58","url":null,"abstract":"For secure communications over wireless mobile networks, Lu et al proposed their secure authentication key agreement protocol. However, Lu et al’s protocol is vulnerable against Chang and Chang’s parallel guessing attack. To remove the parallel guessing attacks, Chang and Chang also proposed their improvement. However, Chang and Chang’s protocol is still vulnerable against their parallel guessing attack. So our new authenticated key agreement protocol for wireless mobile networks is proposed.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124796444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance Analysis of Chinese Webpage Categorizing Algorithm Based on Support Vector Machines (SVM)","authors":"Xiao Gang, Jiancang Xie","doi":"10.1109/IAS.2009.316","DOIUrl":"https://doi.org/10.1109/IAS.2009.316","url":null,"abstract":"Categorizing web automatically for users is a key technique of information society, and the key point of this technique is web training and categorization. This paper researches one of the important algorithm in this field—support vector machines (SVM). By analyzing and simulating 4 kinds of kernel function and 3 ways of feature selection, polynomial kernel function and document frequency is chosen for the best way in SVM algorithm. Meanwhile, pre-process algorithm is given in this paper in order to improve the efficiency of categorization. By simulation, importing pre-process method to SVM enhances the capability of the web categorization both in precision and time-consumption.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123451694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Tsai, Mingchun Wang, Ting-Yuan Chang, Pei-Yan Pai, Y. Chan
{"title":"An Adaptable Threshold Decision Method","authors":"M. Tsai, Mingchun Wang, Ting-Yuan Chang, Pei-Yan Pai, Y. Chan","doi":"10.1109/IAS.2009.96","DOIUrl":"https://doi.org/10.1109/IAS.2009.96","url":null,"abstract":"Otsu’s thresholding method (OTM) is one of the most commonly used thresholding methods. Unfortunately, the threshold obtained by OTM is biased in favor of the class, whose standard deviation or quantity of data is larger. Besides, one may adopt distinct thresholds in different applications for a same data set. Accordingly, this paper proposes an adaptable threshold decision method (ATDM) to provide the most appropriate thresholds for assorted applications. This paper also proposes a PSO (particle swarm optimization) based parameter detector (PBPD) to decide the fittest parameters which are used by ATDM. Image segmentation extracts the regions of interest from an image for follow-up analyses, and thresholding is one important technique for image segmentation. This paper will employ ATDM to detect the object contours in an image in order to investigate the performance of ATDM. The experiments show that ATDM can give impressive segmentation results.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123599685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Low Bit Rate ROI-Based SAR Image Compression","authors":"Xiao-Hong Yuan, Zhaoda Zhu, Gong Zhang","doi":"10.1109/IAS.2009.179","DOIUrl":"https://doi.org/10.1109/IAS.2009.179","url":null,"abstract":"Due to large amount of collected data, image compression is both necessary and important for SAR system. Conventional image compression algorithms are incapable of attaining the desired compression while retaining the image fidelity required for processing at the ground station. In this paper, we present a ROI-based SAR image compression system for low bit rate. Region of interest is identified by a multiresolution constant false alarm rate (CFAR) detector and it is encoded with a higher bit rate than background. Performance was tested over the public MSTAR target chips. Results show that SNR of target area with proposed algorithm are higher than that with conventional algorithm and contextual information is preserved.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125310792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast Fractal Image Coding Using Ambient-Cross Sum of Normalized Block","authors":"Gao-ping Li","doi":"10.1109/IAS.2009.154","DOIUrl":"https://doi.org/10.1109/IAS.2009.154","url":null,"abstract":"Fractal image coding has a fatal drawback of being time consuming in encoding process. In response to this problem, this paper proposed an effective method to limit the searching space, which is mainly based on a newly defined concept of ambient-cross sum of normalized block and a related inequality. In detail, after the codebook blocks are sorted according to their ambient-cross sum features, for an input range block being encoded, the encoder uses the bisection search method to find out the initial-matched block (i.e., the domain block having the closest ambient cross sum features to the input range block being encoded). And then the encoder confines efficiently the searching scope of similarity matching to the vicinity of the initial-matched block. Simulation results show that the proposed scheme gives significant improvement in speed and quality as compared to the baseline algorithm with full search.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125352892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A New JPEG Resistant Color Image Watermarking Algorithm Based on Quantization Index Modulation","authors":"Jie Nie, Zhiqiang Wei, Z. Li","doi":"10.1109/IAS.2009.59","DOIUrl":"https://doi.org/10.1109/IAS.2009.59","url":null,"abstract":"A new color image watermarking algorithm with resistance to JPEG lossy compression based on Quantization Index Modulation (QIM) is proposed in this paper. As it is known, QIM method can achieve a good balance between the embedding bit rate, robustness and distortion between the original image and the composited image by modulating the source signal into different clusters. The corresponding DCT coefficients margins of any two color channels selected from the three as the source signal is substantiated could achieve a high level embedding robustness and a low level distortion in this paper. However, JPEG lossy compression could bring a destructive influence to the watermark since it discards pretty much image information. In this paper, a compensation function is designed to correct the errors caused by JPEG compression. Experiments show the algorithm proposed has a good performance to resist the high compression ratio JPEG lossy compression and other attacks.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125507045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Resistant Secret Sharing Scheme","authors":"Chinchen Chang, Yen-Chang Chen, Chia-Chen Lin","doi":"10.1109/IAS.2009.324","DOIUrl":"https://doi.org/10.1109/IAS.2009.324","url":null,"abstract":"In this paper, we proposed a novel (2, 2) secret sharing scheme applied for grayscale images. This scheme can produce two noise-like shared images that help avoid a secret image being grabbed. The construction phase of shared image consists of producing two shared images of the secret image by a (7, 4) Hamming code operation. To prevent attackers from forging shared images, a logo is embedded into the shared images first by using Tian’s reversible data embedding scheme. Later, the embedded secret image is shuffling by Torus automorphism to enhance its security. Experimental results show that the nois-like shared images can be successfully generated by our proposed scheme.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115174305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Lung Segmentation for Chest Radiograph by Using Adaptive Active Shape Models","authors":"Jiann-Shu Lee, Hsing-Hsien Wu, Ming-Zheng Yuan","doi":"10.1109/IAS.2009.353","DOIUrl":"https://doi.org/10.1109/IAS.2009.353","url":null,"abstract":"In this paper, we proposed an automatic lung segmentation method. We designed a ROI based method to estimate a proper initial lung boundary for ASM deformation by deriving the translation and the scaling parameters from the lung ROI. An adaptive ASM, using k-means clustering and silhouette-based cluster validation technique, was proposed to adapt to the lung shape change so that the lung shape variation among people can be overwhelmed. The experiments indicated that the segmentation performance of the adaptive ASM is superior to the traditional ASM approaches.","PeriodicalId":240354,"journal":{"name":"2009 Fifth International Conference on Information Assurance and Security","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116377282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}