• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.551-556
• /
• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.22 no.3
• /
• pp.515-524
• /
• 2012

Fault attacks are a powerful side channel analysis extracting secret information by analyzing the result after injecting faults physically during the implementation of a cryptographic algorithm. First, this paper analyses vulnerable points of existing Digital Signature Algorithm (DSA) schemes secure against fault attacks. Then we propose a new signature algorithm immune to all fault attacks. The proposed DSA scheme is designed to signature by using two nonce and an error diffusion method.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.1
• /
• pp.88-95
• /
• 2006

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They we difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.701-704
• /
• 2005

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But They are difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PID controller based on a cell-mediated immune response and a gradient descent learning. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• IE interfaces
• /
• v.23 no.2
• /
• pp.147-155
• /
• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

• Proceedings of the KOSOMBE Conference
• /
• v.1992 no.05
• /
• pp.129-132
• /
• 1992

Cellular kinetics formulate the basis of tumor immune system dynamics which may be synthesized mathematically as cascades of bilinear systems which are connected by nonlinear dynamical terms. In this manner, a foundation for the control of syngeneic tumors is presented. We have analyzed the mechanisms of controlling the infiltration of lymphocytes into tumor tissues. Simulated anneal ins, a general-purpose method of multivariate optimization, is applied to combinatorial optimization, which is to find the minimum of a given function depending on many parameters. We compare the results of the different methods including the global optimization algorithm, known as simutated annealing.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.115.1-115
• /
• 2001

According as many people use a computer newly, damage of computer virus and hacking is rapidly increasing by the crucial users. A computer virus is one of program on computer and has abilities of self reproduction and destruction like a virus of biology. And hacking is to rob a person´s data in a intruded computer and to delete data in a person´s computer from the outside. To block hacking that is intrusion of a person´s computer and the computer virus that destroys data, a study for intrusion-detection of system and virus detection using a biological immune system is in progress. In this paper, we make a mood of positive selection and negative selection of self-recognition process that is ability of ...

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.5
• /
• pp.411-416
• /
• 2002

Recently, the trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online internet, so it is expected to make a problem more and more. Currently, the general security system based on Internet couldn't cope with the attack properly, if ever, other regular systems have depended on common softwares to cope with the attack. In this paper, we propose the positive selection mechanism and negative selection mechanism of T-cell, which is the biological distributed autonomous system, to develop the self/non-self recognition algorithm, the anomalous behavior detection algorithm, and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. The proposed algorithm can cope with new intrusion as well as existing one to intrusion detection system in the network environment.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.10
• /
• pp.159-166
• /
• 2009

A nature immunity system responds sensitively to an external invasion with various functions in a lot of bodies, besides it there is a function to remember information to have been currently infected. we propose a hybrid model similar to immune system which combine with the antibody which applied genetic algorithm as select antibody and the arbitrary abnormal system call sequence that applied negative selection of a nature immunity system. A proposed model uses an arbitrary abnormal system Kol sequence in order to reduce a positive defect and a negative defect. Data used to experiment are send mail data processed UNM (University of New Maxico). The negative defect that an experiment results proposal model judged system call more abnormal than the existing negative selection to normal system call appeared 0.55% low.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.2
• /
• pp.173-181
• /
• 2001

This paper presents an artificial life algorithm which is remarkable in the area of engineering for functions optimization. As artificial life organisms have a sensing system, they can find the resource which they want to find and metabolize. And the characteristics of artificial life are emergence and dynamic interaction with environment. In other words, the micro-interaction with each other in the artificial lifes group results in emergent colonization in the whole system. In this paper, therefore, artificial life algorithm by using above characteristics is employed into functions optimization. The optimizing ability and convergent characteristics of this proposed algorithm is verified by using three test functions. The numerical results also show that the proposed algorithm is superior to genetic algorithms and immune algorithms for the multimodal functions.