• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.237-242
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• 2003

In this paper, we propose a new adaptive intrusion detection algorithm based on clustering: Kernel-ART, which is composed of the on-line clustering algorithm, ART (adaptive resonance theory), combining with mercer-kernel and concept vector. Kernel-ART is not only satisfying all desirable characteristics in the context of clustering-based IDS but also alleviating drawbacks associated with the supervised learning IDS. It is able to detect various types of intrusions in real-time by means of generating clusters incrementally.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.456-463
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• 2021

In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.10-17
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• 2010

In a passive sonar, the improvement of detection performance by using noise cancellation is usually a important problem. In this paper, we have analyzed the own-ship noise cancellation in the two operation modes which are used in the HMS system. In the operator mode, an adaptive line enhancer(ALE) is applied to improve the tonal detection by using broadband noise cancellation and the normalized least mean square(NLMS) algorithm is applied to the design of an adaptive filter. The reference input that is correlated with a primary input can be used to remove the noise incident on the observation directionin the automatic mode. Computer simulations with real sea that data show that the proposed adaptive noise canceller has good performance in passive detection under HMS operation.

• The Journal of the Acoustical Society of Korea
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• v.22 no.6
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• pp.489-495
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• 2003

Single towed line array receiver contains an ambiguity on conjugate bearings because of lacking aperture in transverse direction. To solve the left/right bearing ambiguity of line array receiver this paper proposed using single line array with fixed cardioid beam. Fixed cardioid beam has problem about back beam gain exists for steering beam inherent. Back beam is makes form on direction that is different from actually source so that reduced the performance of left/right bearing discrimination. In this paper, line way with adaptive cardioid beam for resolve problem of back beam gain is proposed. So the proposed method has more improved left/right bearing discrimination than fixed cardioid beam, Simulation results show the performance of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.62-70
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• 2000

Intelligent vehicles are equipped with radar sensors for collision avoidance. We present a method of suppressing mutual interference among pulse-type radars, where all the radars are standardized. We developed a method of separating the true self-reflection from the false one by controlling the pulse emission of a radar in anorhogonal ON, OFF pattern. Interference signal identified in OFF-intervals is recorded to indicate the positions of the expected ghosts in ON-intervals. PFA and PM are derived for a radar system with I-Q demodulation scheme, where Gaussian noise alone is Rayleigh-distributed and Gaussian noise plus reflected radar pulse are Rician-distributed. The value of the threshold adaptively updated in order to prevent the deterioration of PM. In the experimental result, PFA decreases by an order of 10,000, when compared with the conventional M of N majority voting method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.254-257
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• 2002

인터넷 보급의 확산과 전자상거래의 활성화와 유.무선 인터넷의 보급에 따른 악의적인 사이버 공격의 시도의 성공사례가 증가하고 있다. 미로 인해 점차 더 많은 문제가 야기될 것으로 예상된다. 현재 일반적인 인터넷상의 시스템은 악의적인 공격에 적절하게 대응해오지 못하고 있으며, 다른 범용의 시스템들도 기존의 백신 프로그램에 의존하며 그 공격에 대응해오고 있다. 따라서 새로운 침입에 대하여는 대처하기 힘든 단점을 가지고 있다. 본 논문에서는 생체 자율분산시스템의 일부분인 T세포의 positive selection과 negative selection을 이용한 자기/비자기 인식 알고리즘을 제안한다. 제안한 알고리즘은 네트워크 환경에서 침입탐지 시스템에 적용하여 기존에 알려진 침입뿐만 아니라 새로운 침입에 대해서도 대처할 수 있다

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.16-19
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• 2014

In this paper, the beacon signals of WiFi doppler frequency detection based WiFi-AP was designed with the subcarrier between a transmitter and a receiver of WLAN(wireless LAN). We can use such signals to identify human moving as an antenna array and tracking of RF beam. This wireless security services with the combination of WiFi doppler frequency and adaptive beacon time signal was proposed for wireless detection and motion based services.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.15-25
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• 2014

In this paper, we propose a loitering detection using trajectory probability distribution and local direction descriptor for intelligent surveillance system. We use a background modeling method for detecting moving object and extract the motion features from each moving object for making feature vectors. After that, we detect the loitering behavior person using K-Nearest Neighbor classifier. We test the proposed method in real world environment and it can achieve real time and robust detection results.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.451-456
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn't make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.75-81
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• 2004

Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn`t make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.