• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.9-15
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• 2013

Recently, Intrusion detection system is an important technology in computer network system because of has seen a dramatic increase in the number of attacks. The most of intrusion detection methods do not detect intrusion on real-time because difficult to analyze an auditing data for intrusions. A network intrusion detection system is used to monitors the activities of individual users, groups, remote hosts and entire systems, and detects suspected security violations, by both insider and outsiders, as they occur. It is learns user's behavior patterns over time and detects behavior that deviates from these patterns. In this paper has rule-based component that can be used to encode information about known system vulnerabilities and intrusion scenarios. Integrating the two approaches makes Intrusion Detection System a comprehensive system for detecting intrusions as well as misuse by authorized users or Anomaly users (unauthorized users) using RFM analysis methodology and monitoring collect data from sensor Intrusion Detection System(IDS).

• Journal of Digital Convergence
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• v.16 no.5
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• pp.399-406
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• 2018

Much research has been done using the KDDCup99 data set to study intrusion detection using artificial intelligence. Previous studies have shown that the performance of the SMO (SVM) algorithm is superior. However, intrusion detection studies of new intrusion types not used in training are insufficient. In this paper, a model was created using the instances of weka's SMO and KDDCup99 training data set, kddcup.data.gz. We tested existing instances(292,300) of the corrected.gz file and new intrusions(18,729). In general, intrusion labels not used in training are not tested, so new intrusion labels were changed to normal. Of the 18,729 new intrusions, 1,827 were classified as intrusions. 1,827 instances classified as new intrusions are buffer_overflow. Three, neptune. 392, portsweep. 164, ipsweep. 9, back. 511, imap. 1, satan. Dogs, 645, nmap. 102.

• The korean journal of orthodontics
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• v.48 no.6
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• pp.367-376
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• 2018

Objective: This study was performed to investigate the changes in alveolar bone after maxillary incisor intrusion and to determine the related factors in deep-bite patients. Methods: Fifty maxillary central incisors of 25 patients were evaluated retrospectively. The maxillary incisors in Group I (12 patients; mean age, $16.51{\pm}1.32years$) were intruded with a base-arch, while those in Group II (13 patients; mean age, $17.47{\pm}2.71years$) were intruded with miniscrews. Changes in the alveolar envelope were assessed using pre-intrusion and post-intrusion cone-beam computed tomography images. Labial, palatal, and total bone thicknesses were evaluated at the crestal (3 mm), midroot (6 mm), and apical (9 mm) levels. Buccal and palatal alveolar crestal height, buccal bone height, and the prevalence of dehiscence were evaluated. Two-way repeated measure ANOVA was used to determine the significance of the changes. Pearson's correlation coefficient analysis was performed to assess the relationship between dental and alveolar bone measurement changes. Results: Upper incisor inclination and intrusion changes were significantly greater in Group II than in Group I. With treatment, the alveolar bone thickness at the labial bone thickness (LBT, 3 and 6 mm) decreased significantly in Group II (p < 0.001) as compared to Group I. The LBT change at 3 mm was strongly and positively correlated with the amount of upper incisor intrusion (r = 0.539; p = 0.005). Conclusions: Change in the labial inclination and the amount of intrusion should be considered during upper incisor intrusion, as these factors increase the risk of alveolar bone loss.

• The Journal of Engineering Geology
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• v.27 no.1
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• pp.1-7
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• 2017

Seawater intrusion was evaluated using electrical conductivity, chemical proxies, and oxygen isotopic compositions in coastal area. It seems that groundwater in the area where the electrical conductivity is over $3,000{\mu}S/cm$ is influenced by seawater. However, it is very difficult that seawater intrusion is distinguished from other contaminants using the electrical conductivity. The chemical proxies and oxygen and hydrogen isotopic compositions can quantitatively estimate seawater intrusion. However, these method is a costly disadvantage. Therefore, firstly, groundwater contamination by seawater intrusion was evaluated using electrical conductivity and then the additional chemical and isotopic analysis were conducted in areas where possibility of contamination by seawater intrusion is high. These systematic analytical method can reduce analytical cost to quantitatively evaluate influence of seawater intrusion on coastal groundwater and may improve efficiency of analytical method for seawater intrusion.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.595-604
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• 2004

By the help of expansion of computer network and rapid growth of Internet, the information infrastructure is now able to provide a wide range of services. Especially open architecture - the inherent nature of Internet - has not only got in the way of offering QoS service, managing networks, but also made the users vulnerable to both the threat of backing and the issue of information leak. Thus, people recognized the importance of both taking active, prompt and real-time action against intrusion threat, and at the same time, analyzing the similar patterns of in-trusion already known. There are now many researches underway on Intrusion Detection System(IDS). The paper carries research on the in-trusion detection system which hired supervised learning algorithm and Fuzzy membership function especially with Neuro-Fuzzy model in order to improve its performance. It modifies tansigmoid transfer function of Neural Networks into fuzzy membership function, so that it can reduce the uncertainty of anomaly intrusion detection. Finally, the fuzzy logic suggested here has been applied to a network-based anomaly intrusion detection system, tested against intrusion data offered by DARPA 2000 Intrusion Data Sets, and proven that it overcomes the shortcomings that Anomaly Intrusion Detection usually has.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.705-710
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• 2003

Recently, most interchanges of information have been performed in the internet environments. So, the technuque, which is used as intrusion deleting tool for system protecting against attack, is very important. But, the skills of intrusion detection are newer and more delicate, we need preparations for defending from these attacks. Currently, lots of intrusion detection systemsmake the midel of intrusion detection rule using experienced data, based on this model they have the strategy of defence against attacks. This is not efficient for defense from new attack. In this paper, a new model of intrusion detection is proposed. This is hybrid statistical learning model using likelihood ratio test and statistical learning theory, then this model can detect a new attack as well as experienced attacks. This strategy performs intrusion detection according to make a model by finding abnomal attacks. Using KDD Cup-99 task data, we can know that the proposed model has a good result of intrusion detection.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.717-726
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• 2003

In this paper, we analyze the associated rule based deductive algorithm which creates the rules automatically for intrusion detection from the vast packet data. Based on the result, we also suggest the deductive algorithm which creates the rules of intrusion pattern fast in order to apply the intrusion detection systems. The deductive algorithm proposed is designed suitable to the concept of clustering which classifies and deletes the large data. This algorithm has direct relation with the method of pattern generation and analyzing module of the intrusion detection system. This can also extend the appication range and increase the detection speed of exiting intrusion detection system as the rule database is constructed for the pattern management of the intrusion detection system. The proposed pattern generation technique of the deductive algorithm is used to the algorithm is used to the algorithm which can be changed by the supporting rate of the data created from the intrusion detection system. Fanally, we analyze the possibility of the speed improvement of the rule generation with the algorithm simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.680-683
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• 2001

As the rapid information communication technique, internet users have been continuously increasing every year, but on the other hand many damages have occurred on the internet because of dysfunction for computer system intrusion. To reduce damages, network and system security mechanism is variously developed by researcher, IDS(Intrusion Detection System) is commercialized to security technique. In this paper we describe for intrusion detection based on network, we design and implement IDS to detect illegal intrusion using misuse detection model. Implemented IDS can detect various intrusion types. When IDS detected illegal intrusion, we implemented for administrator to be possible management and control through mechanisms of alert message transmission, mail transmission, mail at the remote.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5B
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• pp.489-499
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• 2003

This paper is a study about Honey-pot Model using CPN(Colored Petri Nets) that is a method of intrusion detection. Suggested Honey-pot model consists of two parts : \circled1 security kernel module for active induction of hacker's intrusion, intrusion detection and behavior pattern analysis. \circled2 virtual module for activity of induced hackers. However, suggested model was compared and analysed with conventional Denning model and Shieh nodel. The Honey-pot model using CPN can classify the characteristic of intrusion pattern, modeling intrusion pattern and pattern matching procedure, detect DDoS attack through multi hosts, and provide basis of study model for analysing intrusion pattern, finally.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.99-104
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• 2004

A combination of drilling, geophysical well logging, and electrical soundings was performed to evaluate seawater intrusion in Baeksu-eup, Youngkwang-gun, Korea. The survey area extends for over 24 $km^2$. To delineate the extent of seawater intrusion, 60 vertical electrical soundings (VES) have been carried out. Twelve wells were also drilled for the collection of hydrogeological, geochemical, and geophysical well logging data, to delineate the degree and vertical extent of seawater intrusion. To map the spatial distribution of seawater in this coastal aquifer, geophysical data and hydrogeochemical results were used, and the relation between the resistivity of groundwater and equivalent NaCl concentration was found. Layer parameters derived from VES data, various in-situ physical properties from geophysical well logging, and the estimated equivalent NaCl concentration were very useful for quantitative evaluation of seawater intrusion. Our approach for evaluating seawater intrusion can be considered a valuable attempt at enhancing the use of geophysical data.