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To facilitate the transition from paper-based patient record (PPR) to computer-based patient record (CPR), engineers should try to improve the usability of CPR system. From the point of view of a physician, we reviewed PPRs written by 8 Japanese physicians. We revealed the characteristics of PPR to find out about the barrier to transition from PPR to CPR. Our findings may be helpful to the engineers who are aiming to develop a CPR system. [ABSTRACT FROM AUTHOR]

In this paper we describe the design of a hybrid search that combines simple metadata search with a traditional keyword search over unstructured context data. This paradigm provides the inquirer additional options to narrow the search with some semantic aspects through the XML metadata query. We demonstrate a paper search for a case study of the hybrid search, and describe a data integration hub to integrate those data dispersed on the Net. [ABSTRACT FROM AUTHOR]

This paper describes the benefits that small companies can obtain from the United Kingdom Department of Trade and Industry Knowledge Transfer Partnerships business support product. This provides funding for collaborations between universities and companies in order that knowledge and technology transfer between the partners can occur. Knowledge Transfer Partnerships can support a wide range of commercial activities, proving there is a solid business case to show that the government support will lead to improvements in the profitability of the company. This paper describes the Knowledge Transfer Partnerships product. It then goes on to present a case study of a business collaboration under the scheme between Powerlase Ltd, a manufacturer of laser systems, and the University of Brighton, to implement intelligent condition monitoring in the Company's products. [ABSTRACT FROM AUTHOR]

Recently, various types of data are expected to get in information processing according to multi-media technology. Especially, linguistic data are employed in fuzzy systems as well as fuzzy numerical values. In this paper we propose a text minig method based on fuzzy quantification model. In the process of text mining, we will pursue the following steps: 1) Sentences included in a text in Japanese are broken down into words. 2) It is possible to realize common understanding using fuzzy thesaurus that enables us to translate words into synonyms or into upper concepts. In this paper, we employ the method to translate words using Chinese characters or continuous letters of Katakana more then one katakana letter (Japanese alphabet letter) into keywords. The method realizes the high speed of processing without any dictionary for separating words. Fuzzy multivariate analysis is employed to analyze such processed data and to abstract a latent mutual related structure under the data. In other words, we abstract the knowledge from the given text data. At the end we apply the method to mining the text information of libraries and Web pages distributed over a web network and discussing about the application to Kansei engineering. Keywords: Text mining, fuzzy quantification analysis, library data. [ABSTRACT FROM AUTHOR]

By adopting a non-interactive information-theoretic secure verifiable secret sharing scheme in an unorthodox way, a verifiable fingerprint vault scheme is presented in this paper. Fuzzy vault scheme is a novel cryptographic construct which can increase the security of the biometric template in a biometric authentication system. It can be also used to bind the cryptographic key and the user in a cryptosystem to overcome the security problems caused by the key stolen, key illegally shared, etc. The main weakness of the scheme is the computation complexity is too high for the legitimate user to unlock the vault. In this paper, a verifiable fingerprint vault is proposed to improve the fuzzy vault scheme. It is shown that our scheme is effective. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical model that employs a new genetic algorithm for motor identification. Mechanical structures require precise motor information for high control performance. However, it is difficult to acquire accurate motor information and a genetic algorithm can be an adequate method to search unknown parameters using only angular position. The previous methods by using conventional genetic algorithms do not give the most optimal result since they cannot adjust the parameters with infinite precision. A new method is needed to identify uncertain motor information. This paper proposes a mathematical model that was searched by the newly proposed genetic algorithm. The induced motor model is verified through the real experiment. [ABSTRACT FROM AUTHOR]

This paper presents an approach to control pluggage of a coal-fired boiler. The proposed approach involves statistics, data partitioning, parameter reduction, and data mining. The proposed approach was tested on a 750 MW commercial coal-fired boiler affected with a fouling problem that leads to boiler pluggage that causes unscheduled shutdowns. The rare-event detection approach presented in the paper identified several critical time-based data segments that are indicative of the ash pluggage. [ABSTRACT FROM AUTHOR]

In this paper there is an intelligent human-machine speech communication system presented, which consists of the intelligent mechanisms of operator identification, word and command recognition, command syntax and result analysis, command safety assessment, technological process supervision as well as operator reaction assessment. In this paper there is also a review of the selected issues on recognition and verification of voice commands in natural language given by the operator of the technological device. A view is offered of the complexity of the recognition process of the operator's words and commands using neural networks made of a few layers of neurons. The paper presents research results of speech recognition and automatic command recognition using artificial neural networks. [ABSTRACT FROM AUTHOR]

This paper describes techniques to present human action information on an avatar-based interaction system, using real-time motion sensing and human action symbolization. Avatar-based interaction systems with computer-generated virtual environments have difficulties in acquiring user's information, i.e., enough information to represent the user as if he/she were in the environment. This mainly comes of high degrees of freedom of human body and causes the lack of reality. Since it is almost impossible to acquire all the detailed information of human actions or activities, we, instead, recognize, or estimate, what kind of actions have occurred from sensed human motion information and other available information and re-generate detailed and natural actions from the estimated results. In this paper, we describe our approach, Real-time Human Proxy, especially on representing human actions. Also we present experimental results. [ABSTRACT FROM AUTHOR]

Supporting adaptive learning is one of the key problems for hypertext-based learning applications. This paper proposed a timed Petri Net based approach that provides adaptation to learning activities by controlling the visualization of hypertext information nodes. Simple examples were given while explaining ways to realize adaptive operations. Future directions were also discussed at the end of this paper. [ABSTRACT FROM AUTHOR]

In the previous paper, we have shown the conventional capacity of higher order associative memory of sequential patterns. The definition of the capacity permits that some of the elements of the pattern are not recalled correctly. If we want to recall the patterns more correctly, then the definition is not always valid. The absolute capacity is known as the severe definition that almost all the elements of the pattern are recalled correctly. In this paper, we show the absolute capacities of higher order associative memory of sequential patterns. Further, the absolute capacities are compared with the conventional ones. Specifically, the relation between the capacity and the correlation are shown. [ABSTRACT FROM AUTHOR]

We proposed a technique for using multiagent technology in data mining intended for two or more text databases. In this paper, we discuss data mining method based on text (text mining), but our proposed method is not a method of specializing in text mining. First, we proposed data mining technique using multiagent technology. The proposed technique is applied to document databases, and discuss its results. In this paper, proposed data mining using multiagent was applied to information integration system on Web, and the effectiveness was verified. In the proposed method, the part of the database access agent was changed to the Web access agent. Also, mining agent was changed to the information extraction agent from the HTML file. [ABSTRACT FROM AUTHOR]

Keystroke dynamics is an intelligent data processing technique of analyzing the user's habitual typing patterns to identify him. Keystroke dynamics combined with password authentication has been widely used as a means to enhance user authentication system. However, the user authentication system's security does not rely solely on the keystroke dynamics. To guarantee a high level of security, more secure password authentication is needed. The design and development of a secure password authentication protocol for keystroke dynamics is discussed in this paper. We propose a new efficient password authentication protocol that is secure against all types of attacks considered in the paper. We also show that our two-party protocol is extended to a three-party protocol, where each user only shares a password with a trusted server. As a result, our protocols with keystroke dynamics can provide a secure and intelligent means of authentication and access control of computer users. [ABSTRACT FROM AUTHOR]

The information security of computer networks has become a serious global issue and also a hot topic in computer networking researches. Many approaches have been proposed to tackle these problems, especially the denial of service (DoS) attacks. The Multiple Classifier System (MCS) is one of the approaches that have been adopted in the detection of DoS attacks recently. For a MCS to perform better than a single classifier, it is crucial for the base classifiers which embedded in the MCS to be diverse. Both resampling, e.g. bagging, and feature grouping could promote diversity of base classifiers. In this paper, we propose an approach to select the reduced feature group for each of the base classifiers in the MCS based on the mutual information between the features and class labels. The base classifiers being combined using the weighted sum is examined in this paper. Different feature grouping methods are evaluated theoretically and experimentally. [ABSTRACT FROM AUTHOR]

Theoretic methods for travel speed estimation are common in the traffic literature, but treatments of how to account delay caused by traffic signal are less common. This paper is an attempt to improve conventional technique for evaluating travel speed in signalized intersection networks. To do so, this paper employs new concept which is associated with the vehicles' trajectory in the time-space diagram. The most useful advantage of the algorithm proposed in this paper is that, the traffic analysts can reduce much tedious works for screening and selecting a bunch of speed data. [ABSTRACT FROM AUTHOR]

In this paper we present a novel approach that customize the BDI model to define a so-called "RBDIA: Rapport-Belief-Desire-Intention-Adaptation" as a generic method to support progress from individual autonomous agent concept towards a collaborative multiple agents. Rapport here refers to the component that connects an agent to its environment, whereas Adaptation module incorporates mechanisms of learning. The contribution of this paper is twofold: first, we develop a novel modeling approach that enable us to combine the internal and social structures of collaborative multigent, and second the proposed methodology is applied to a real-world application for assistance in product development process. We believe that the five proposed tiers for multiagent systems (MAS) development serves for mastering the complexity and the difficulty of setting up effective autonomous collaborative MAS. [ABSTRACT FROM AUTHOR]

Knowledge-based video retrieval is able to provide the retrieval result that corresponds with conceptual demand of user because of performing automatic indexing with audio-visual data, closed-caption, and so on. In this paper, we present the automatic indexing method of Korean closed-caption for knowledge-based video retrieval and the retrieval scheme using the indexed database. In the experiment, we have applied the proposed method to news video with the closed-caption generated by Korean stenographic system, and have empirically confirmed that the proposed method could provide the retrieval result that corresponds with more meaningful conceptual demand of user. [ABSTRACT FROM AUTHOR]

Multimedia information and communication network are two key elements of a distributed multimedia system. This paper researches distributed multimedia system from the points of view of both multimedia data and network channels. A dynamic model SCUDM for distributed multimedia system is proposed and a scheduling algorithm MCD is put forward. Simulation experiment shows that algorithm MCD has an advantage over algorithm EDF on the network utilization. [ABSTRACT FROM AUTHOR]

The issue of how to provide location-based service (LBS) for transportation users has attracted many researchers. In a country wide system, there are needs for processing geographic information of road network in different scales and transportation information at the same time. In this paper, we propose an integrated method for representing multi-level of transportation information in addition to multi-scale of road map. Based on the datasets generated by this method, queries in LBS applications can be responded efficiently. [ABSTRACT FROM AUTHOR]

Face recognition system needs the method of locating facial components like eyes, mouth, etc, for extracting features used in recognition process. In this paper we propose a method of locating eyes using context-aware binarization. The proposed method consists of binarization, connected region segmentation, eye candidate area extraction by heuristic rules that use geometric information, eye candidate pair detection, and eye area pair determining by ranking method. Binarization plays an important role in this system that converts a source image to a binary image suitable for locating eyes. We consider edge detection based and segmentation based binarization methods. However, each method cannot be a solution in general environment because these are influenced by the factorssuch as light direction, contrast, brightness, and spectral composition. We propose a hybrid binarization using the concept of illumination context-awareness that mixes two binarization methods in general environment. We apply this methodology to eye location, and we achieved encouraging experiment results in general environment. [ABSTRACT FROM AUTHOR]

The main problem addressed in this paper is simplification of transforming the knowledge from natural language description to fuzzy rules control system. The proposed fuzzy system build on the observation of human pilot reaction and on few very simple rules is very promising. Our fuzzy control system allow to control the helicopter in the hover yet can be generalize to other aspect of helicopter flight. [ABSTRACT FROM AUTHOR]

Spot matching is a challenging problem in two dimensional protein gel electrophoresis (2DGE) chromatography images analysis. It is necessary to provide a robust solution to the problem of querying and matching large scale for various size of 2DGE images. In this paper, we have developed a novel maximum relation spanning tree (MRST) algorithm which is capable of performing fast and accurate matching without the need for landmarks to be manually selected. In the matching process, we employ fuzzy similarity measuring technique to conclude the final decision of matching and location. The resultant system performs up to 94% correct matching for 225 2DGE test images. The additive value is the foundation of querying fractional gel images with large format gel images database. [ABSTRACT FROM AUTHOR]

Wireless networks and mobile applications have grown very rapidly and have made a significant impact on computer systems. Especially, the usage of mobile phones and PDA is increased very rapidly. Added functions and values with these devices are thus greatly developed. If some regularity can be known from the user mobility behavior, then these functions and values can be further expanded and used intelligently. This paper thus attempts to mine appropriate linguistic mobility patterns for being used by mobile-system managers in future strategy planning. The location areas in which mobile users visit and their duration times can be found from the log data stored in the home-location-register module. Since the duration times are numeric, fuzzy concepts are used to process them and to form linguistic mobility patterns. [ABSTRACT FROM AUTHOR]

Mining generalized association rules among items in the presence of taxonomy and with nonuniform minimum support has been recognized as an important model in the data mining community. In real applications, however, the work of discovering interesting association rules is an iterative process; the analysts have to continuously adjust the constraint of minimum support to discover real informative rules. How to reduce the response time for each remining process thus becomes a crucial issue. In this paper, we examine the problem of maintaining the discovered multi-supported generalized association rules when the multiple minimum support constraint is refined and propose a novel algorithm called RGA_MSR to accomplish the work. By keeping and utilizing the set of frequent itemsets and negative border, and adopting vertical intersection counting strategy, the proposed RGA_MSR algorithm can significantly reduce the computation time spent on rediscovery of frequent itemsets and has very good performance. [ABSTRACT FROM AUTHOR]

In the past, a number of researches have been devoted to web mining. However, only page browsing behaviors have been studied. The actions performed in the pages were omitted. To the best of our knowledge, no previous researches were able to find out page-action browsing sequences. This paper proposes an algorithm, called WebPAN, to analyze customers' browsing pages and their action paths. The algorithm's efficiency was examined in our prototype. This study would help website managers to restructure their website layouts or advertisement positions more correctly in electronic commerce. [ABSTRACT FROM AUTHOR]

Knowledge acquisition is known to be a critical bottleneck in building expert systems. In past decades, various methods and systems have been proposed to efficiently elicit expertise from domain experts. However, in building a medical expert system, disease symptoms are usually treated as time-irrelevant attributes, such that much important information is abandoned and hence the performance of the constructed expert systems is significantly affected. To cope with this problem, in this paper, we propose a time scale-oriented approach to eliciting medical knowledge from domain experts. The novel approach takes the time scale into consideration, such that the variant of disease symptoms in different time scales can be precisely expressed. An application to the development of a medical expert system has depicted the superiority of our approach. [ABSTRACT FROM AUTHOR]

This paper discusses learning contents design from the viewpoint of knowledge level and symbol level. The purpose of study is to develop a foundation for share and reuse of IESs on a global platform. SCORM2004 is becoming de facto standard so we choice it as the basis of the platform. On the platform we aim to build an environment for authors to clarify pedagogical meaning of learning contents based an ontology for IESs. This approach will allow us to share and reuse academic and technical expertise in the field of AIED research on common platform. [ABSTRACT FROM AUTHOR]

The objective in this paper is to construct a mechanism for generating the answers for mathematical exercises automatically. A mathematical exercise is decomposed into several small exercises that are called sub-exercises. An answer of an exercise is a collection of answers of its sub-exercises. If the inclusive relations among exercises are managed, answers for exercises can be generated easily. In our approach, the inclusive relations of exercises are represented as a solution network. The solution network is structured as a tree. In the solution network, nodes correspond to the exercises and links indicate inclusive relations of exercises. By traversing the solution network from the node corresponds to the target exercise and detecting its sub-exercises, the answer of the target exercise is able to be generated automatically. [ABSTRACT FROM AUTHOR]

Shinshu University Graduate School of Science and Technology on the Internet (SUGSI) is established in 2002 as the first Internet University in Japan. In SUGSI, students can learn every lecture using a CAI system featuring drills on the web, and get supervising about a master's thesis from faculty adviser via network. Therefore, students can complete a master course and get a master's degree without commuting to the school. We manage SUGSI on day school system, and we developed some student support systems as well as learning contents with CAI. In this paper, we mention about the learning system of SUGSI: its CAI contents, a student management system, and the profile of enrolled students such as their age structure and their learning style. [ABSTRACT FROM AUTHOR]

Self-directed navigation involving knowledge construction in learning Web contents, called navigational learning, is not so easy for learners since they often fail to notice the pages to be learned and semantic relationships between the pages navigated. It is accordingly necessary to enhance their awareness of the incompleteness of knowledge that they have constructed. We call such awareness unknown awareness. However, it is hard for learners to gain it by themselves. We have developed the system, which enables them to compare their navigation history to others, and which can select some navigation histories more appropriate for the history comparison from a repository. This paper describes a case study with the system whose purpose is to ascertain if the history comparison contributes to providing an unknown awareness. [ABSTRACT FROM AUTHOR]

This research paper aims to develop a simple Web mail system for senior citizens to make the best use of their empirical knowledge as social properties, which is one plan of an informationization promotion project by industrial-government-academic cooperation begun in 2004. A simple Web mail system is made for trial purposes as a concrete example for senior citizens based on their needs, and an indicator of grappling with the current state in development and future problems is described. [ABSTRACT FROM AUTHOR]

In this paper, a food intake measuring system for medical applications is proposed. The system measures the differences of food images between pre-eaten and post-eaten, and accurately calculates the intake of calorie and nutrition. It can be an assistant of dietitians. The whole operation procedures and each component are introduced. The verification experiments of the system performance are also executed. [ABSTRACT FROM AUTHOR]

We developed the Health Support Intelligent System for Diabetic Patients (HSISD) as a web-based system. Nowadays mobile phones are widely used in our daily life and become the most popular personal communication tool. To make HSID more familiar, we add the application software for operating in mobile phone and enable data entry and patient authentification by mobile phone. In this paper, we describe the questionnaire system and the authentication system based on mobile phone technology. [ABSTRACT FROM AUTHOR]

We developed the Remote Monitoring Intelligent System (RMIS) of Local Area Network (LAN) to realize the secure Internet environment. The RMIS has various agents which work to exchange the information related to computers condition with the network environment. We shall be able to control the quality and quantity in the network communication by their agents. In this paper, we propose the scheduling method of data transmission by Recurrent Neural Networks(RNNs) to avoid traffic jam in the network. Especially, our proposed RNN enables to expect the condition of network at each network device instead of time series data. In order to verify the effectiveness of our proposed method, we report the examination results. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to propose preprocessing procedures from handwritten medical records, of which words are omitted, to translate contents of the records into formatted data such as XML data. From the viewpoint, we performed an experiment, which physicians freely described patients' problems to reveal the characteristics in the handwritten record. As a result, we obtained five characteristics. Based on these characteristics, we considered eight preprocessing steps. Then, we confirmed that our proposed preprocessing worked well from a computational experiment although not all sub-procedures are effective due to lack of a large amount of corpora. [ABSTRACT FROM AUTHOR]

In this paper we introduce a framework for an advanced medical education in a table-type VR environment, which is based on an efficient deformable modeling for the interactive manipulation of soft tissues and a realistic motion simulation for dynamic human organs. The proposed framework includes two data storages with 3D/4D models and the 2D anatomic information, and various functional modules that are used to effectively explain human organs by visualizing and synchronizing with the components in the data storages. In our VR environment, a table-type virtual workbench is effectively used for the collaborative and realistic presentation to a group of learners and the video-based tracking environment provides the convenience for a user to select and to manipulate a subject of learning. [ABSTRACT FROM AUTHOR]

In this paper a physiological modeling and simulation system for aerobic circulation in fitness exercise is presented, where the cardiovascular system model predicts pulsatile blood flows in response to exercising levels. Designing a circulatory monitor and simulator to allow interaction of human with health enhancement devices enables to develop intelligent fitness machines. The modeling and simulation system for the human circulation model is vital to realize the safe and effective machines. In order to construct the better architecture of assisting framework, the modeling and simulation system for human circulation model previous to fitness work could contribute to make the effective schemes for rehabilitation, dieting, health enhancement, or physical strengthening. [ABSTRACT FROM AUTHOR]

The paper describes basic properties of a sentence generator which requires minimal input information. Input is a set of unstructured semantic concepts, and the generator produces sentences which are compatible with this set by utilizing information from a statistical language model. Output is filtered by a simple context-free grammar. The system is trained on text from electronic medical records, and it is able to produce well-formed sentences in cases involving simple medication prescriptions and symptom descriptions. Basic complexity aspects of the problem are described, and suggestions for efficient implemented generators which manage to produce sentences within acceptable time limits, despite the complexity of the approach, are presented in the final sections. [ABSTRACT FROM AUTHOR]

Cancelable biometrics has been proposed for canceling and re-issuing biometric templates and for protecting privacy in biometrics systems. Recently, new cancelable biometric approaches are proposed based on BioHashing, which are random transformed feature-based cancelable biometrics. In this paper, we consider the accuracy of one of the cancelable biometrics based on BioHashing and face. Through this analysis, as an illustration, we would like to raise an issue to be considered in cancelable biometrics: accuracy may be traded for biometrics being cancelable. [ABSTRACT FROM AUTHOR]

This paper proposes "A General Fuzzy Min-max neural network with Compensatory Neurons architecture"(GFMCN) for pattern classification and clustering. The network is capable of handling labeled and unlabeled data simultaneously, on-line. The concept of compensatory neurons is inspired from reflex system of the human brain. Fuzzy min-max neural network based architectures use fuzzy hyperbox sets to represent the data cluster or classes. An important stage in the training phase of these techniques is to manage the hyperbox overlaps and containments. In case of GFMCN, compensatory neurons are trained to handle the hyperbox overlap and containment. Inclusion of these neurons with a new learning approach has improved the performance significantly for labeled as well as unlabeled data. Moreover accuracy is almost independent of the maximum hyperbox size. The advantage of GFMCN is that it can learn data in a single pass (on-line). The performance of GFMCN is compared with "General Fuzzy Min-max neural network" proposed by Gabrys and Bargiela on several datasets. [ABSTRACT FROM AUTHOR]

Directed mutation has shown to improve the efficiency of evolutionary algorithms significantly for a broad spectrum of optimization problems. When the first mutation operators of this kind, however, suffered from the asymmetry parameter influencing the mutation strength, in the meantime there are several new directed mutation operators available which overcome this drawback. The aim of this paper is to give an overview of all different operators in one single place. Their characteristics will be presented and their advantages and disadvantages are discussed. At the end a comparison and a summary is provided. [ABSTRACT FROM AUTHOR]

The paper is motivated by a ranking problem arising e.g. in financial institutions. This ranking problem is reduced to a system of inequalities that may be solved by applying the perceptron learning theorem. Under certain additional assumptions the associated probabilities are derived by exploiting Bayes' Theorem. It is shown that from these a posteriori probabilities the original classifier may be recovered. On the other hand, assuming that perfect classification is possible, a maximum likelihood solution is derived from the classifier. Some experimental results are given. [ABSTRACT FROM AUTHOR]

In this paper it is studied how to measure human feelings. Since human feelings are not simple and very complicated and it is not easy to evaluate them. Generally human feelings are considered nonlinear and methods for paired comparison are useful to deal with nonlinear problems. For the reason it is studied how to use paired comparison for measuring human feelings. Among many methods for paired comparison Case V of Thurston's method is perceived. For the measurement obtained by Case V of Thurston's method for paired comparison is useful because the units of the measurement are the standard deviations of the standard normal distributions Here it is discussed to measure human feelings using paired comparison. [ABSTRACT FROM AUTHOR]

Digital fingerprinting is a technique to protect digital contents from illegal reproduction and redistribution by marking unique information for individual user. A powerful but simple attack to diminish fingerprint signals is averaging. While several fingerprinting schemes against collusion attacks were proposed, they often do not fully account for multimedia data. In this paper, we propose a zero-based code modulation method which fully reflects marking assumption concept to embedding and detection of signals and anti-collusion code working mechanism as well. By manipulating 0-bit information of binary codes, detection accuracy and code separation under averaging attacks were enhanced. To demonstrate our method, we used an averaging-resilient fingerprint code based on GD-PBIBD theory and applied it video fingerprinting systems. Through the experimental results, we convince our method improves averaging resiliency of fingerprinting systems. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel reversible information hiding scheme based on vector quantization (VQ) technique. First, VQ technique is used to encode the host image to form an index table. In the embedding phase, what the secret is hidden into the index table depends on the group id including the most closed codeword. And then, the modified index table is generated. In order to restore the original, we develop a flipping index table according to the original index table and the modified one. Finally, the stego-image could be constructed by combining the modified index table with the flipping one as well. Experimental results show that the performance of the proposed scheme is better than other VQ-based information hiding scheme in terms of the image quality and the distortion of the stego-image. Besides, in the proposed scheme, the original index table of the host image could be restored completely. [ABSTRACT FROM AUTHOR]

A secure steganographic paradigm of binary image, which is fulfilled by simulating normal scanning process, is suggested in the paper. The indeterministic parts of scanning can be calculated by checking the differences between repeated scans. The information hiding is realized with reference to this indeterminism. We also provide a novel scheme to put this secure paradigm into practice by using the error control embedding technique. A more efficient practical method is presented based on morphological theory and the Matrix encoding strategy is utilized to improve the embedding performance. [ABSTRACT FROM AUTHOR]

Mobile agent technology is an evolving paradigm that combines the inherent characteristics of intelligent agents, namely, adaptability, reactivity and autonomy with mobility. These characteristics of mobile agents provide an excellent means of meeting the distributed and heterogeneous requirements for many electronic commerce applications involving low bandwidth and intermittently connected networks. However, the lack of security in the form of code confidentiality renders this paradigm unsuitable for commercial software. In this paper, we address the problem of mobile agent security by proposing a novel method of mobile agent obfuscation using the concept of opaque predicates to prevent adversaries from observing the control flow of agent code. We discuss about the efficiency of our proposed methodology by demonstrating that to an adversary, the problem of determining the outcome of such opaque predicates is often intractable. [ABSTRACT FROM AUTHOR]

In this paper, we describe biometric watermarking techniques for secure user verification on the remote, multimodal biometric system employing both fingerprint and face information, and compare their effects on verification accuracy quantitatively. To hide biometric data with watermarking techniques, we first consider possible two scenarios. In the Scenario 1, we use a fingerprint image as a cover work and hide facial features into it. On the contrary, we hide fingerprint features into a facial image in the Scenario 2. Based on the experimental results, we confirm that the Scenario 2 is superior to the Scenario 1 in terms of the verification accuracy of the watermarked image. Keywords: Biometrics, Biometric Watermarking, Multimodal Biometric System [ABSTRACT FROM AUTHOR]

Information hiding technology embeds information using the redundancy of information contained in cover data. Therefore, many information-hiding techniques for cover data with a lot of redundancy, such as images or sound signals, have been proposed. Most proposed information hiding techniques that set document to cover data tampered with layouts between spacing and words. In this paper, a new information hiding technique for agglutinative languages like Japanese or Korean that have no spaces between morphemes is proposed. By the proposed technique, digital documents are set to cover data and secret data is embedded by making the position of the new-line code inserted into document correspond to secret data. The technique can also be applied to plain text like an e-mail, which does not have layout information. Because the technique does not change the content of the cover data at all, the technique can be used not only as steganography aiming at performing secret communication but also as digital watermarking. Moreover, the technique has the feature whereby embedded data remains also in the printing output. [ABSTRACT FROM AUTHOR]

In parity assignment-based steganography for palette images, all colors in a host image are divided into two subsets, and each pixel is used to carry one secret bit. This paper describes an analytic method against the parity assignment-based steganographic techniques. By finding the rule of color modifications, a steganalyst can attempt to recover the original histogram in a way that is a reverse of data embedding. Because of the abnormal colors in the original image, an excessive operation will cause some negative values in the recovered histogram. This provides a clue for revealing the presence of secret message and estimating the length of embedded bit sequence. [ABSTRACT FROM AUTHOR]