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A new hiding scheme of digital image is introduced in this paper, which is robust to image processing such as JPEG compression, median filtering, adding Gauss noise, cropping, and histogram equalization. In this paper, we embed watermark into DWT domain, using integer modulo, retrieval of embedded watermark does not need original image. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the application of a two weights neural network (TWNN) to the channel equalization problem. In particular, the purpose of the paper is to improve the previously developed TWNN equalizer with training using K-means and LMS methods; reducing the TWNN network size by considering a lesser number of TWNN kernels, and developing new techniques for determining channel order which is required to specify the structure of an TWNN equalizer. A linear regression model was used for estimating the channel order. The basic idea of reducing the network size is to select the centers, based on the channel lag. This work includes the comparison of the limits of mean square error (MSE) convergence of both a linear equalizer and an TWNN equalizer. mean square error. [ABSTRACT FROM AUTHOR]

To protect the privacy of proxy blind signature holders from dissemination of signatures by verifiers, this paper introduces universal designated-verifier proxy blind signatures. In a universal designated-verifier proxy blind signature scheme, any holder of a proxy blind signature can convert the proxy blind signature into a designated-verifier signature. Given the designated-signature, only the designated-verifier can verify that the message was signed by the proxy signer, but is unable to convince anyone else of this fact. This paper also proposes an ID-based universal designated-verifier proxy blind signature scheme from bilinear group-pairs. The proposed scheme can be used in E-commerce to protect user privacy. [ABSTRACT FROM AUTHOR]

Network forensic plays an important role in the modern network environment for computer security, but it has become a time-consuming and daunting task due to the sheer amount of data involved. This paper proposes a new method for constructing incremental fuzzy decision trees based on network service type to reduce the human intervention and time-cost, and to improve the comprehensibility of the results. At the end of paper, we discuss the performance of the forensic system and present the result of experiments. [ABSTRACT FROM AUTHOR]

Auto image segmentation can segment the image without operators interfering and is an important technique in the image processing. The Boltzmann-Color-Image-Segmentation (BCIS), which could control the degree of segmentation by adjusting the temperature parameter, is designed based on the Boltzmann-theory and the Metropolis-rule in the paper. Then the criterion function of image segmentation, which could balance between the number of segmented region and the affinity of the segmented image with the original image, is presented. Based the BCIS and Criterion function, the auto color image segmentation is schemed out by using the artificial immune algorithm. Experiments showed that the color image segmentation algorithm, which we designed in the paper, had the good capabilities. [ABSTRACT FROM AUTHOR]

This paper describes the Next Generation PARLAY X with QoS / QoE in Next Generation Network (NGN). PARLAY has introduced the architecture for the development and deployment of services by service providers over 3G network. But the existing PARLAY X does not provide the open Application Programming Interface (API) for QoS / QoE. Therefore, to solve this issue, this paper suggests the PARLAY X with QoS / QoE. The object of this paper is to support the architecture and the API of the network service for QoS / QoE in NGN. The PARLAY X can provide users with QoS / QoE in network according to the detected context such as location and speed and user's preference. The architecture of the Next Generation PARLAY X is comprised of the functions for context-awareness, adaptation, and personalization. [ABSTRACT FROM AUTHOR]

A single web service is most likely inadequate to serve the customers' business needs; it takes a selection of various web services composed together to form a business process. The cost is the primary concern of many business processes. In this paper, we propose a new solution using Genetic Algorithm (GA) in cost-reduction driven web service selection. GA is utilized to optimize business process composed of many service agents (SAg), each of which corresponds to a collection of available web services provided by multiple service providers to perform a specific function. Service selection is an optimization process with taking into account the relationships among the services. Better performance has been gotten using GA in the paper than using local service selection strategy. [ABSTRACT FROM AUTHOR]

CBR is one of the most important artificial intelligence methods. In this paper, it is introduced to detect the variation of known attacks and to reduce the false negative rate in rule based IDS. After briefly describes the basic process of CBR and the methods of describing case and constructing case base by rules of IDS, this paper focuses on the CBR engine. A new CBR engine adapting to IDS is designed because the common CBR engines cannot deal with the specialties of intrusion cases in IDS. The structure of the new engine is described by class graph, and the core class as well as the similarity algorithm adopted by it is analyzed. At last, the results of testing the new engine on Snort are shown, and the validity of the engine is substantiated. [ABSTRACT FROM AUTHOR]

Application of agent technology in Intrusion Detection Systems (IDSs) has been developed. Intrusion Detection (ID) agent technology can bring IDS flexibility and enhanced distributed detection capability. However, the security of the ID agent and methods of collaboration among ID agents are important problems noted by many researchers. In this paper, coordination among the intrusion detection agents by BlackBoard Architecture (BBA), which transcends into the field of distributed artificial intelligence, is introduced. A system using BBA for information sharing can easily be expanded by adding new agents and increasing the number of BlackBoard (BB) levels. Moreover the subdivided BB levels enhance the sensitivity of ID. This paper applies fuzzy logic to reduce the false positives that represent one of the core problems of IDS. ID is a complicated decision-making process, generally involving enormous factors regarding the monitored system. A fuzzy logic evaluation component, which represents a decision agent model of in distributed IDSs, considers various factors based on fuzzy logic when an intrusion behavior is analyzed. The performance obtained from the coordination of an ID agent with fuzzy logic is compared with the corresponding non-fuzzy type ID agent. [ABSTRACT FROM AUTHOR]

Correlation of intrusion alerts is a major technique in attack detection to build attack scenario. Rule-based and data mining methods have been used in some previous proposals to perform correlation. In this paper we integrate two complementary methods and introduce fuzzy clustering in the data mining method. To determine the fuzzy similarity coefficients, we introduce a hierarchy measurement and use weighted average to compute total similarity. This mechanism can measure the semantic distance of intrusion alerts with finer granularity than the common similarity measurement . The experimental results in this paper show that using fuzzy clustering method can reconstruct attack scenario which are wrecked by missed attacks. [ABSTRACT FROM AUTHOR]