• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.51-57
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• 2021

In this paper, we propose a method to find the DoF(Depth of field) that is blurred in an image by focusing and out-focusing the camera through a efficient convolutional neural network. Our approach uses the RGB channel-based cross-correlation filter to efficiently classify the DoF region from the image and build data for learning in the convolutional neural network. A data pair of the training data is established between the image and the DoF weighted map. Data used for learning uses DoF weight maps extracted by cross-correlation filters, and uses the result of applying the smoothing process to increase the convergence rate in the network learning stage. The DoF weighted image obtained as the test result stably finds the DoF region in the input image. As a result, the proposed method can be used in various places such as NPR(Non-photorealistic rendering) rendering and object detection by using the DoF area as the user's ROI(Region of interest).

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.65-71
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• 2013

In this paper, we address fault detection observer design problem of T-S fuzzy systems with sensor fault. To detect fault, T-S fuzzy model-based observer is used. By introducing $\mathfrak{H}$_ performance index, an observer is designed as sensitive to fault as possible. The fault is then detected by a fault decision logic. The design conditions are derived in terms of linear matrix inequalities. An illustrative example is provided to verify the effectiveness of the proposed fault detection technique.

• Korean Journal of Veterinary Research
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• v.23 no.1
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• pp.105-110
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• 1983

The studies carried out to investigate the detection method of Fasciola eggs from positive cattle feces in the intradermal reaction method with laborsaving composition of sieves and Kim's sedimental tube method. The results obtained are summarized as follows: 1. The detection method of Fasciola eggs was improved by 3 meshes (100mesh, 150mesh, 250mesh) for filteration of fecal fluid contained Fasciola eggs. 2. Third type of tube in the 3 kinds of sedimental tube had the highest recovers rate of Fasciola eggs. Thus, this type of tube was selected and called as Kim's sedimental tube. 3. A-II, A-III, B-III and C-III type by Kim's sedimental tube method had the recovery rates of eggs in the 1st drop as ranged 99 to 100% and, A-I, B-II, C-II as 71 to 91%. 4. These Type of tubes were useful to detect Fasciola eggs and to shorten the time of the diagnostic procedures. 5. The Kim's sedimental tube method showed high recovery rates and convenient procedures as compared with other detection methods reported. In addition, the EPG value can also be obtained by this method. Therefore, it is desirable that the Kim's sedimental tube method could be recommended to clinicians.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7B
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• pp.592-600
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• 2008

In this paper, a Hybrid Scaling based DTW (HS-DTW) mechanism is proposed for detection of periodic shrew TCP attacks. A low-rate TCP attack which is a type of shrew DoS (Denial of Service) attacks, was reported recently, but it is difficult to detect the attack using previous flooding DoS detection mechanisms. A pattern matching method with DTW (Dynamic Time Warping) as a type of defense mechanisms was shown to be reasonable method of detecting and defending against a periodic low-rate TCP attack in an input traffic link. This method, however, has the problem that a legitimate link may be misidentified as an attack link, if the threshold of the DTW value is not reasonable. In order to effectively discriminate between attack traffic and legitimate traffic, the difference between their DTW values should be large as possible. To increase the difference, we analyze a critical problem with a previous algorithm and introduce a scaling method that increases the difference between DTW values. Four kinds of scaling methods are considered and the standard deviation of the sampling data is adopted. We can select an appropriate scaling scheme according to the standard deviation of an input signal. This is why the HS-DTW increases the difference between DTW values of legitimate and attack traffic. The result is that the determination of the threshold value for discrimination is easier and the probability of mistaking legitimate traffic for an attack is dramatically reduced.

• ETRI Journal
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• v.44 no.2
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• pp.346-354
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• 2022

The SYN flooding attack is widely used in cyber attacks because it paralyzes the network by causing the system and bandwidth resources to be exhausted. This paper proposed a self-information approach for detecting the SYN flooding attack and provided a detection algorithm with a hierarchical policy on a detection time domain. Compared with other detection methods of entropy measurement, the proposed approach is more efficient in detecting the SYN flooding attack, providing low misjudgment, hierarchical detection policy, and low time complexity. Furthermore, we proposed a detection algorithm with limiting system resources. Thus, the time complexity of our approach is only (log n) with lower time complexity and misjudgment rate than other approaches. Therefore, the approach can detect the denial-of-service/distributed denial-of-service attacks and prevent SYN flooding attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.4
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• pp.97-110
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• 2004

As modem web services become enormously complex, web attacks has become frequent and serious. Existing security solutions such as firewalls or signature-based intrusion detection systems are generally inadequate in securing web services, and analysis of raw web log data is simply impractical for most organizations. Visual display of "interpreted" web logs, with emphasis on anomalous web requests, is essential for an organization to efficiently track web usage patterns and detect possible web attacks. In this paper, we discuss various issues related to effective real-time visualization of web usage patterns and anomalies. We implemented a software tool named SAD (session anomaly detection) Viewer to satisfy such need and conducted an empirical study in which anomalous web traffics such as Misuse attacks, DoS attacks, Code-Red worms and Whisker scans were injected. Our study confirms that SAD Viewer is useful in assisting web security engineers to monitor web usage patterns in general and anomalous web sessions in particular.articular.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.65-68
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• 2021

본 연구에서는 Dilated U-Net 기반의 이미지 복원기법을 통해 콘크리트 균열 추출 성능 개선 방안을 제안한다. 콘크리트 균열은 구조물의 미관상의 문제뿐 아니라 추후 큰 안전사고의 원인이 될 수 있어 초기대응이 중요하다. 현재는 점검자가 직접 육안으로 검사하는 외관 검사법이 주로 사용되고 있지만, 이는 정확성 및 비용, 시간, 그리고 안전성 면에서 한계를 갖고 있다. 이에 콘크리트 구조물 표면에 대해 획득한 영상 처리 기법을 사용한 검사 방식 도입의 관심이 늘어나고 있다. 또한, 딥러닝 기술의 발달로 딥러닝을 적용한 영상처리의 연구 역시 활발하게 진행되고 있다. 본 연구는 콘크리트 균열 추개선출 성능 개선을 위해 Dilated U-Net 기반의 이미지 복원기법을 적용하는 방안을 제안하였고 성능 검증 결과, 기존 U-Net 기반의 정확도가 98.78%, 조화평균 82.67%였던 것에 비해 정확도 99.199%, 조화평균 88.722%로 성능이 되었음을 확인하였다.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.179-191
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• 2024

With the advancement of modern technology, cyber-attacks are always rising. Specialized defense systems are needed to protect organizations against these threats. Malicious behavior in the network is discovered using security tools like intrusion detection systems (IDS), firewall, antimalware systems, security information and event management (SIEM). It aids in defending businesses from attacks. Delivering advance threat feeds for precise attack detection in intrusion detection systems is the role of cyber-threat intelligence (CTI) in the study is being presented. In this proposed work CTI feeds are utilized in the detection of assaults accurately in intrusion detection system. The ultimate objective is to identify the attacker behind the attack. Several data sets had been analyzed for attack detection. With the proposed study the ability to identify network attacks has improved by using machine learning algorithms. The proposed model provides 98% accuracy, 97% precision, and 96% recall respectively.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.594-600
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• 2010

Many studies are DDoS in Internet network, but the study is the fact that is not enough in a voice network. Therefore, we designed the extended TRW algorithm that was a DDoS attack traffic detection algorithm for the voice network which used an IP data network to solve upper problems in this article and evaluated it. The algorithm that is proposed in this paper analyzes TRW algorithm to detect existing DDoS attack in Internet network and, design connection and end connection to apply to a voice network, define probability function to count this. For inspect the algorithm, Set a threshold and using NS-2 Simulator. We measured detection rate by an attack traffic type and detection time by attack speed. At the result of evaluation 4.3 seconds for detection when transmitted INVITE attack packets per 0.1 seconds and 89.6% performance because detected 13,453 packet with attack at 15,000 time when transmitted attack packet.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.151-159
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• 2006

This paper studied active response policy generation scheme in intrusion detection system. We considered seven requirements of intrusion detection system for active response with components as the preceding study We presented the scheme which I can generate signature with a base with integrate one model with NIDS and ADS. We studied detection of the Unknown Attack which was active, and studied scheme for generated to be able to do signature automatically through Unknown Attack detection.