• The korean journal of orthodontics
• /
• v.28 no.3 s.68
• /
• pp.431-440
• /
• 1998

While periodontal disease results in the extrusion of upper incisors with interdental spacing in adult patient, the intrusive movement should be executed for the rehabilitation in terms of esthetics and function. The present study was peformed to investigate the periodontal response following orthodontic intrusion of teeth with infrabony pocket. Bone defect and periodontal disease were produced adjacent to the both maxillary second lateral incisors in four adult dogs. Four weeks later, a flap operation was performed to eliminate inflammation and a reference notch was made on the root surface at the level of bottom of each defect. Two weeks after periodontal surgery, 4 weeks of intrusion and subsequent another 4 weeks of retention was executed on the right side of incisors while left incisors served as the control. Through the histologic analysis, following results were obtained. 1. Histologic section of control side showed the reduction of pocket depth after flap operation. However, the status of long junctional epithelium was observed while new connective tissue attachment occurred in a small area adjacent newly formed cementum 2. Epithelial attachment was less around the intruded incisor while new connective tissue attachment was much more compared to the control side. 3. Plenty of cells were observed in the connective tissue around the reference notch of the intruded incisor and the degree of the new cementum formation was higher in the intruded incisor than the control. The results of the present study suggested that an orthodontic intrusion of periodontally involved and extruded incisors could be carried out with a desirable periodontal response, provided that inflammation is under control.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 2004.07a
• /
• pp.154-154
• /
• 2004

• Information Systems Review
• /
• v.20 no.1
• /
• pp.17-39
• /
• 2018

SNS enables people to easily connect and communicate with each other. People share information, including personal information, through SNS. Users are concerned about their privacies, but they unconsciously or consciously disclose their personal information on SNS to interact with others. The privacy of a self-disclosed person can be intruded by others. A person can write, fabricate, or distribute a story using the disclosed information of another even without obtaining consent from the information owner. Many studies focused on privacy intrusion, especially from the perspective of a victim. However, only a few studies examined privacy intrusion from the perspective of an intruder on SNS. This study focuses on the intention of privacy intrusion from the perspective of an intruder on SNS and the factors that affect intention. Privacy intrusion intentions are categorized into two types. The first type is intrusion of privacy by writing one's personal information without obtaining consent from the information owner;, whereas the other type pertains to intrusion of privacy by distributing one's personal information without obtaining consent from the information owner. A research model is developed based on motivation theory to identify how these factors affect these two types of privacy intrusion intentions on SNS. From the perspective of motivation theory, we draw one extrinsic motivational factor (response cost) and four intrinsic motivational factors, namely, perceived enjoyment, experience of being intruded on privacy, experience of invading someone's privacy, and punishment behavior. After analyzing 202survey data, we conclude that different factors affect these two types of privacy intrusion intention. However, no relationship was found between the two types of privacy intrusion intentions. One of the most interesting findings is that the experience of privacy intrusion is the most significant factor related to the two types of privacy intrusion intentions. The findings contribute to the literature on privacy by suggesting two types of privacy intrusion intentions on SNS and identifying their antecedents from the perspective of an intruder. Practitioners can also use the findings to develop SNS applications that can improve protection of user privacies and legitimize proper regulations relevant to online privacy.

• Proceedings of the IEEK Conference
• /
• 2004.08c
• /
• pp.876-879
• /
• 2004

The buried fiber optic cable as a distributed intrusion sensor for detecting and locating intruders along the long perimeters is proposed. Phase changes resulting from either the pressure of the intruder on the ground immediately above the buried fiber or from seismic disturbances in the vicinity are sensed by a phase-sensitive optical time-domain reflectometer. Light pulses from a Er:fiber cw laser with a narrow, <3kHz-range, spectral width and a frequency drift of < 1 MHz/min are injected into one end of the fiber, and the backscattered light from the fiber is monitored with a photodetector. Results of preliminary studies, measurement of phase changes produced by pressure and seismic disturbances in buried fiber optic cables and simulation of ${\varphi}-OTDR$ response over long fiber paths, to establish the feasibility of the concept are described. The field experiments indicate adequate phase changes, more than 1t-rad, are produced by intruders on foot and vehicle for burial depths in the 0.2 m to 1 m range in sand, clay and fine gravel soils. The simulations predict a range of 10 km with 35 m range resolution and 30 km with 90 m range resolution. This technology could in a cost-effective manner provide enhanced perimeter security.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.4
• /
• pp.491-498
• /
• 2003

The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using FCM(Fuzzy Cognitive Maps) that can detect intrusion by the DoS attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The SPuF(Syn flooding Preventer using Fussy cognitive maps) model captures and analyzes the packet informations to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance comparison, the "KDD′99 Competition Data Set" made by MIT Lincoln Labs was used. The result of simulating the "KDD′99 Competition Data Set" in the SPuF model shows that the probe detection rates were over 97 percentages.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.3
• /
• pp.755-778
• /
• 2024

In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

• Convergence Security Journal
• /
• v.22 no.2
• /
• pp.27-42
• /
• 2022

In the era of the Fourth Industrial Revolution, digital transformation to increase the effectiveness of industry is becoming more important to achieving the goal of industrial innovation. The digital new deal and smart defense are required for digital transformation and utilize artificial intelligence, big data analysis technology, and the Internet of Things. These changes can innovate the industrial fields of national defense, society, and health with new intelligent services by continuously expanding cyberspace. As a result, work productivity, efficiency, convenience, and industrial safety will be strengthened. However, the threat of cyber-attack will also continue to increase due to expansion of the new domain of digital transformation. This paper presents the risk scenarios of cyber-attack threats in the Fourth Industrial Revolution. Further, we propose a preemptive intrusion response model to bolster the complex security environment of the future, which is one of the fundamental alternatives to solving problems relating to cyber-attack. The proposed model can be used as prior research on cyber security strategy and technology development for preemptive response to cyber threats in the future society.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.6
• /
• pp.1294-1301
• /
• 2005

In this paper, we investigate the problems of existing solutions for intrusion detection and propose an agent network based on stationary and mobile agents on agent system to solve them. The proposed agent network can detect intrusions, collect their information and execute active responses against intruders by introducing various stationary and mobile agents. It will show a new approach of active responses against more intelligent and distributed intrusions.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.04a
• /
• pp.416-418
• /
• 2003

기존의 침입탐지 시스템(IDS)은 침입 단계를 고려하지 않고 독립적이고 단편적인 공격 정보를 제공하기 때문에 관리자나 침입대응 시스템(intrusion response system)이 정보들을 이해하고 적당한 행동을 취하기가 매우 힘들다. 본 논문은 기존 침입 탐지시스템이 제공하는 정보들이 갖는 한계를 극복하기 위하여 모든 침입은 독립되어 존재하는 것이 아니라 서로 다른 공격의 연속으로 이루어 진다는 점에 근거하여 단편적인 공격 정보들의 상관성을 활용하기 위한 기법을 제안한다. 이미 알려진 공격 단계에 대한 상관성 정보를 그래프 형태로 표현하고 공격정보에 따라 전이하는 토큰을 이용하여 단편적인 공격들의 상관성을 분석함으로써 활용하기 용이한 분석 정보를 제공하는 것을 목표로 한다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.2
• /
• pp.148-153
• /
• 2003

A DoS(Denial of Service) attack appears in the form of the intrusion attempt and Syn Flooding attack is a typical example. The Syn Flooding attack takes advantage of the weak point of 3-way handshake between the end-points of TCP which is the connection-oriented transmission service and has the reliability This paper proposes a NIIP(Network based Intelligent Intrusion Prevention) model. This model captures and analyzes the packet informations for the detection of Syn Flooding attack. Using the result of analysis of decision module, the decision module, which utilizes FCM(Fuzzy Cognitive Maps), measures the degree of danger of the DoS and trains the response module to deal with attacks. This model is a network based intelligent intrusion prevention model that reduces or prevents the danger of Syn Flooding attack.