• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.118-125
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• 2004

The purpose of this study is to decide an appropriate neighborhood and a transition rule of cellular automata by analyzing the past growth process of urban areas in Gimhae. With cellular automata which can manage the change based on the dynamic model and time, this study analyzes the urban growth of Gimhae from 1987 to 2001. Also, through the simulation of different types for neighborhood and transition rules, we can find the appropriate neighborhood and the transition rule for Gimhae. In conclusion, the forecast of physical urban growth pattern is more accurate under conditions when the number of matrixes for the neighborhood is small, the shape of the neighborhood is rectangular, "${\alpha}$" value, which control the pace of urban growth, is low and the transition possibility ($P_{ij}$) is high.