Yonggwan Won

A flexible database security system using multiple access control policies

Due to various requirements for user access control to large databases in hospitals and banks, database security has been emphasized. There are many security models for database systems using a wide variety of policy-based access control methods. However, they are not functional enough to meet the requirements for the complicated and various types of access control. We propose a database security system that can individually control user access to data groups of various sizes and is suitable for the situation where a users access privilege to arbitrary data is changed frequently. Data group(s) in different sizes d is defined by the table name(s), attribute(s) and/or record key(s), and the access privilege is defined by security levels, roles and polices. The proposed system operates in two phases. The first phase is composed of a modified MAC (mandatory access control) model and RBAC (role-based access control) model. A user can access any data that has lower or equal security levels, and that is accessible by the roles to which the user is assigned. All types of access mode are controlled in this phase. In the second phase, a modified DAC (discretionary access control) model is applied to recontrol the read mode by filtering out the nonaccessible data from the result obtained at the first phase. For this purpose, we also defined the user group s that can be characterized by security levels, roles or any partition of users. The policies represented in the form of Block(s,d,r) were also defined and used to control access to any data or data group(s) that is not permitted in read mode. With this proposed security system, more complicated read access to various data sizes for individual users can be flexibly controlled, while other access mode can be controlled as usual. An implementation example for a database system that manages specimen and clinical information is presented.

Segmentation of Protein Spots in 2D Gel Electrophoresis Images with Watersheds Using Hierarchical Threshold

2D Gel Electrophoresis (2DGE) image is the most widely used method for the isolation of the objective protein by comparative analysis of the protein spot pattern in the gel plane. The process of protein analysis is the method, which compares the protein pattern that is spread in the gel plane with the contrast group and finds interesting protein spot by image analysis. Previous 2DGE image analysis is composed of gaussian fitting, and segments protein spots by watersheds, a morphological segmentation. Watersheds have a benefit that is fast in global threshold, but induces under-segmentation and over-segmentation of spot area when gray level is continuous. The drawback was somewhat solved by marker point institution, but needs the split and merge process. This paper introduces a novel segmentation of protein spots by watersheds using hierarchical threshold, which can resolve the problem of marker-driven watersheds.

Performance Comparison of TCP Traffic over Mobile IPv4 and IPv6 Networks and a Mobile Network Deployment Approach

In order to help ISPs to deploy a mobile IP network into current Internet environment with satisfying users mobility requirements, this paper evaluates and compares the performance of MIPv4 and MIPv6 networks. This paper shows that TCP performance in MIPv6 network outperforms that of MIPv4 network in terms of amount of dropped packets and lasting the connection with mobile node and corresponding node. And so, in this paper, we design a simple deployment approach, which all mobile node operates in MIPv6 networks under fixed IPv4 network environments

Image Pattern Recognition in Natural Environment Using Morphological Feature Extraction

The gray-scale morphological Hit-or-Miss transform is theoretically invariant to vertical translation of the input function, which is analogous to gray-value shift of the input images. Designing optimal structuring elements for the Hit-or-Miss transform operator is achieved by neural network learning methodology using a shared-weight neural network (SWNN) architecture. Early stage of the neural network system performs feature extraction using the operator, while the late stage does classification. In experimental studies, this morphological feature-based neural network (MFNN) system is applied to location of human face and automatic recognition of vehicle license plate to examine the property of the operator. The results of the experimental studies show that the gray-scale morphological Hit-or-Miss transform operator is reducing the effects of lighting variation.

Comparative Evaluation of TCP Performances on MIPv4 and MIPv6 Protocols in Mobile Mesh Networks

In order to apply a mobile IP protocol into current pervasive computing environment with satisfaction of users mobility requirements, this paper evaluates and compares TCP performance on mobile IPv4 and mobile IPv6 protocols in mobile mesh networks for ubiquitous computing environments. Through comparative simulations, this paper shows that TCP performance on the MIPv6 protocol outperforms the performance on the MIPv4 protocol in terms of amount of dropped packets and lasting the connection with mobile node and corresponding node.

Immune-Based Framework for Exploratory Bio-information Retrieval from the Semantic Web

This paper proposes an immune-based framework for adaptive query expansion in the semantic web, where exploratory queries, common in biological information retrieval, can be answered more effectively. The proposed technique has a metaphor with negative selection and clonal expansion in immune systems. This work is differentiated from the previous query expansion techniques by its data-driven adaptation. It utilizes target databases as well as the ontology to expand queries. This data-driven adaptive feature is especially important in exploratory information retrieval where the querying intention itself can be dynamically changed by relevance feedback.

Efficient and Automatic Faces Detection Based on Skin-Tone and Neural Network Model

In this paper, we consider the problem of detecting the faces without constrained input conditions such as backgrounds, luminance and different image quality. We have developed an efficient and automatic faces detection algorithm in color images. Both the skin-tone model and elliptical shape of faces are used to reduce the influence of environments. A pre-built skin color model is based on 2D Gaussian distribution and sample faces for the skin-tone model. Our face detection algorithm consists of three stages: skin-tone segmentation, candidate region extraction and face region decision. First, we scan entire input images to extract facial color-range pixels by pre-built skintone model from YCbCr color space. Second, we extract candidate face regions by using elliptical feature characteristic of the face. We apply the best-fit ellipse algorithm for each skin-tone region and extract candidate regions by applying required ellipse parameters. Finally, we use the neural network on each candidate region in order to decide real face regions. The proposed algorithm utilizes the momentum backpropagation model to train it for 20*20 pixel patterns.The performance of the proposed algorithm can be shown by examples. Experimental results show that the proposed algorithm efficiently detects the faces without constrained input conditions in color images.

Proteomic pattern classification using bio-markers for prostate cancer diagnosis

Decision trees (DTs) and multi-layer perceptron (MLP) neural networks have long been successfully used to various pattern classification problems. Those two classification models have been applied to a number of diverse areas for the identification of ‘biologically relevant molecules. Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDITOF MS) is a novel approach to biomarker discovery and has been successfully used in projects ranging from rapid identification of potential maker proteins to segregation of abnormal cases from normal cases. SELDI-TOF MS can contain thousands of data points. This high dimensional data causes a more complex neural network architecture and slow training procedure. In the approach we proposed in this paper, a decision tree is first applied to select possible biomarker candidates from the SELDI-TOF MS data. At this stage, the decision tree selects a small number of discriminatory biomarker proteins. This candidate mass data defined by the peak amplitude values is then provided as input patterns to the MLP neural network which is trained to classify the mass spectrometry patterns. The key feature of this hybrid approach is to take advantage of both models: use the neural network for classification with significantly lowdimensional mass data obtained by the decision tree. We applied this bioinformatics tool to identify proteomic patterns in serum that distinguish prostate cancer samples from normal or benign ones. The results indicate that the proposed method for mass spectrometry analysis is a promising approach to classify the proteomic patterns and is applicable for the significant clinical diagnosis and prognosis in the fields of cancer biology.

A Flexible Database Security System Using Multiple Access Control Policies

Due to various requirements for user access control to large databases in hospitals and banks, database security has been emphasized. There are many security models for database systems using a wide variety of policy-based access control methods. However, they are not functional enough to meet the requirements for the complicated and various types of access control. We propose a database security system that can individually control user access to data groups of various sizes and is suitable for the situation where a users access privilege to arbitrary data is changed frequently. Data group(s) in different sizes d is defined by the table name(s), attribute(s) and/or record key(s), and the access privilege is defined by security levels, roles and polices. The proposed system operates in two phases. The first phase is composed of a modified MAC (mandatory access control) model and RBAC (role-based access control) model. A user can access any data that has lower or equal security levels, and that is accessible by the roles to which the user is assigned. All types of access mode are controlled in this phase. In the second phase, a modified DAC (discretionary access control) model is applied to recontrol the read mode by filtering out the nonaccessible data from the result obtained at the first phase. For this purpose, we also defined the user group s that can be characterized by security levels, roles or any partition of users. The policies represented in the form of Block(s,d,r) were also defined and used to control access to any data or data group(s) that is not permitted in read mode. With this proposed security system, more complicated read access to various data sizes for individual users can be flexibly controlled, while other access mode can be controlled as usual. An implementation example for a database system that manages specimen and clinical information is presented.

A distributed architecture of the indirect IP lookup scheme for high-speed routers

In order that routers forward a packet to its destination, they perform IP address lookup which determines the next hop of an incoming IP packet by its destination address. Hence, IP address lookup is an important issue in designing high speed routers. For implementing a fast IP lookup scheme in high speed routers, this paper proposes a distributed architecture of the indirect IP lookup scheme which consists of several IP lookup engines. Also, we propose a simple rule for partitioning route entries among several IP lookup engines. And we evaluate the performance of the proposed scheme in terms of the memory required for storing lookup information and the number of memory accesses on constructing the forwarding table. With additional hardware support, the proposed scheme can drastically reduce the amount of required memory and the number of memory accesses for constructing the forwarding table.