• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.804-807
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• 2012

Cloud service provider has to protect client's information securely since all the resources are offered by the service provider, and a large number of users share the resources. In this paper, a NoSQL-based anomaly detection system is proposed in order to enhance the security of mobile cloud services. The existing integrated security management system that uses a relational database can not be used for real-time processing of data since security log from a variety of security equipment and data from cloud node have different data format with unstructured features. The proposed system can resolve the emerging security problem because it provides real time processing and scalability in distributed processing environment.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.2
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• pp.198-210
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• 1999

산업 및 통신기술이 급속히 발전함에 따라, 다양한 형태의 침입기법을 통해 클라이언트-서버 구조의 정보 공유 및 서비스 개념으로 운영되는 시스템상에서 중요한 정보에 대한 유출 및 파괴로 인한 역기능이 심각할 정도로 증가하고 있다. 따라서, 정보시스템에서의 정보의 불법유출을 방지하고 문서나 시스템에 대한 불법행위를 감지할 수 있는 감사추적 기법이 요구된다. 이 논문에서는 능동데이타베이스의 능동규칙을 기존 기법보다 효과적으로 침입자를 감지할수 있는 새로운 감사추적 및 분석시스템 모델을 제안하였다. 이 모델은 시스템사용자에 의해서 발생되는 감사자료의 비정상 여부를 판단할수 있는 기법과 유형별 침입자를 감지하는 알고리즘을 제시하여 정상적인 사용자의 이탈된 행동을 판단할 수 있는 바업을 제시한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.797-808
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• 2012

In smart work environment, a company provides employees a flexible work environment for tele-working using mobile phone or portable devices. On the other hand, such environment are exposed to the risks which the attacker can intrude into computer systems or leak personal information of smart-workers' and gain a company's sensitive information. To reduce these risks, the security administrator needs to analyze the usage patterns of employees and detect abnormal behaviors by monitoring VPN(Virtual Private Network) access log. This paper proposes a decision support system that can notify the status by using visualization and similarity measure through clustering analysis. On average, 88.7% of abnormal event can be detected by this proposed method. With this proposed system, the security administrator can detect abnormal behaviors of the employees and prevent account theft.

• Korean Journal of Psychosomatic Medicine
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• v.19 no.2
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• pp.101-108
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• 2011

Objectives:We conduct this study to investigate the common features between Attention Deficit Hyperactivity Disorder(ADHD) and epileptic patients compared to normal control. Methods:Epileptic patients were recruited from the department of pediatic in Jesus Hospital. ADHD patients were recruited from the department of neuropsychiatry in Jesus Hospital. We excluded mental retardation or brain organic pathology. We use ADHD Diagnostic System and Korean-Child Behavior Checklist(K-CBCL) to assess features of ADHD. Electroencephalogram(EEG) of ADHD, epileptic patients and normal control were analyzed and compared. Results:Compared to normal control group, inattention, reaction time deviation were increased in both ADHD and epilepsy group. EEG abnormalities(control 13.8%, epilepsy 97.1%, ADHD 40%) in three groups were reported. Conclusion:There are common features of ADHD and epileptic patients.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.319-326
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• 2016

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. In this paper, we propose a new Kinect camera-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The moving-pigs are labeled as regions of interest. 3) A contour method is proposed and applied to solve the touching-pigs problem in the Kinect-depth image. The experimental results with the depth videos obtained from a pig farm located in Sejong illustrate the efficiency of the proposed method.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.301-308
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• 2004

Misuse IDS is known to have an acceptable accuracy but suffers from high rates of false alarms. We show a behavior based alarm reduction with a memory-based machine learning technique. Our extended form of IBL, (XIBL) examines SNORT alarm signals if that signal is worthy sending signals to security manager. An experiment shows that there exists an apparent difference between true alarms and false alarms with respect to XIBL behavior This gives clear evidence that although an attack in the network consists of a sequence of packets, decisions over Individual packet can be used in conjunction with misuse IDS for better performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.597-602
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• 2014

We propose hybrid-sensing system for human tracking. This system uses laser scanners and image sensors and is applicable to wide and crowded area such as hallway of university. Concretely, human tracking using laser scanners is at base and image sensors are used for human identification when laser scanners lose persons by occlusion, entering room or going up stairs. We developed the method of human identification for this system. Our method is following: 1. Best-shot images (human images which show human feature clearly) are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the color histograms of best-shot images. It becomes possible to conduct human identification even in crowded scenes by estimating best-shot images. In the experiment in the station, some effectiveness of this method became clear.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• Korean Journal of Psychosomatic Medicine
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• v.7 no.2
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• pp.252-255
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• 1999

Numbers of patients who have chronic pain seem to be increasing even in the psychiatric practice. One report in Korea showed more than 40% of psychiatric patients who visited out-patient clinic were suffered from chronic pain and one third of those patients were needed treatment for the on-going pain. For evaluating and treating those patients the charateristics of illness behavior should be understood. Abnormal Illness behavior was found as one of the most influential factors which led symptoms complicated and chronified. This symposium was planned to illustrate how to manage the patients whose pain are associated with arthropathy and connective tissue diseases, neuropathic pain and headache more effectively and efficiently. So, It is hoped to get fruitful knowledges for the management of chronic pain in the scope of consultation-liaison psychiatry.

• Journal of Oral Medicine and Pain
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• v.19 no.2
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• pp.111-123
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• 1994

저자는 1990년부터 1993년 사이에 부산대학병원 구강내과에 내원하여 두 개하악장애로 진단되어 보존적 치료를 시행받은 884명의 환자를 대상으로 Solberg의 악관절장애조사 설문지를 작성케한 후, 성, 연령, 병력기간, 진단명, SCL-90-R, 치료에 대한 반응에 따라 환자군을 세분하여 각 환자군의 설문지 문항별 응답양태 및 이에 따른 예후예측을 분석한 바 다음과 같은 결론을 얻었다. 1. 악기능 및 예후악화요인 문항에서는 여성이 높은 응답수를 보인 반면, 기여요인 및 습관문항에 서는 남성이 높은 응답수를 나타내었다. 2. 고령층의 환자에서 행동 및 예후악화요인이 두드러졌다. 3. 만성군이 급성군에 비해 전 문항에서 높은 응답수를 나타내었다. 4. 혼합군 및 근육장애혼자가 관절장애환자에 비해 설문지 전 문항에서 많은 응답을 하였다. 5. SCL-90-R에서 비정상인 환자가 정상군의 환자에 비해 악기능을 제외한 전 문항에서 높은 응답수를 보였다. 6. 치료에 무반응인 환자가 성공한 환자에 비해 습관요인 문항을 제외한 설문지 전체에서 많은 응답을 하였다.