• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.267-277
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• 2022

Due to the increasing proportion of cloud and remote working environments, various information security incidents are occurring. Insider threats have emerged as a major issue, with cases in which corporate insiders attempting to leak confidential data by accessing it remotely. In response, insider threat detection approaches based on machine learning have been developed. However, existing machine learning methods used to detect insider threats do not take biases and variances into account, which leads to limited performance. In this paper, boosting-type ensemble learning algorithms are applied to verify the performance of malicious insider detection, conduct a close analysis, and even consider the imbalance in datasets to determine the final result. Through experiments, we show that using ensemble learning achieves similar or higher accuracy to other existing malicious insider detection approaches while considering bias-variance tradeoff. The experimental results show that ensemble learning using bagging and boosting methods reached an accuracy of over 98%, which improves malicious insider detection performance by 5.62% compared to the average accuracy of single learning models used.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.345-353
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• 2011

An 1.485 Gbit/s video signal transmission system using the carrier frequency of H-band(220~325 GHz) was implemented and demonstrated for the first in domestic. The RF front-end was composed of Schottky barrier diode sub-harmonic mixers(SHM) and frequency triplers, and diagonal horn antennas for transmitter and receiver, respectively. The transmitted carrier frequency of 246 GHz was implemented in the H-band, and LO frequencies of H-band SHM is 120 GHz and 126 GHz for transmit and receive chains, respectively. The modulation scheme is ASK(Amplitude Shift Keying) where IF frequency is 5.94 GHz and the envelop detection was used in heterodyne receiver architecture, and direct detection receiver using ZBD(Zero Bias Detector) was implemented as well. The 1.485 Gbit/s video signal with HD-SDI format was successfully transmitted over wireless link distance of 5 m and displayed on HDTV at the transmitted average output power of 20 ${\mu}W$.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.3
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• pp.278-284
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• 2010

In this paper, a millimeter-wave detector using zero-bias schottky diode is designed and fabricated at W-band. It consists of LNA(Low Noise Amplifier) and detector module to improve sensitivity. LNA case with a highly stop-band characteristic is designed to prevent the oscillation by LNA MMIC chip. Diode detector of planar structure is fabricated for the easy connection with LNA module and zero bias Schottky diode is utilized. In practice, the fabricated diode detector have shown the detection voltage of 20~500 mV to the RF input power of -45~-20 dBm. The proposed W-band detector can be applicable to the passive millimeter image system.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.63-69
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• 2006

Islanding phenomenon of utility-connected PV power conditioning systems(PV PCS) can cause a variety of problems and must be prevented. If the real and reactive powers supplied by PV PCS are closely matched to those of load, islanding detection by passive methods becomes difficult. The active frequency drift(AFD) method, called the frequency bias method, enables islanding detection by forcing the frequency of the voltage in the islanding to drift up or down. In this paper, non-detection zone(NDZ) of AFD is analyzed for the islanding detection method of utility-connected PV PCS by simulation tool PSIM.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.334-343
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• 2011

This paper presents a new approach for mobile robot heading detection using MEMS Gyro north finding method in the indoor environment. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, a single axis MEMS gyroscope to sense the angle between the robot heading direction and the north is used. To reach enough estimation accuracy and reduce detection time, the least square method (LSM) for the signal fitting and parameter estimation is applied. Through a turn-table, we setup a carouseling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2594-2599
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• 2003

We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.176-183
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• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2526-2531
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• 2005

A practical pinch torque estimator based on the Kalman filter is proposed for low-cost anti-pinch window control systems. To obtain the accurate angular velocity from Hall-effect sensor measurements, the angular velocity calculation algorithm is executed with additional procedures for removing the measurement noises. Apart from the previous works using the angular velocity estimates and torque estimates for detecting the pinched condition, the torque rate is augmented to the system model and the proposed pinch estimator is derived by applying the steady-state Kalman filter recursion to the model. The motivation of this approach comes from the idea that the bias errors in torque estimates due to the motor parameter uncertainties can be almost eliminated by introducing the torque rate state. For detecting the pinched condition, a systematic way to determine the threshold level of the torque rate estimates is also suggested via the deterministic estimation error analysis. Simulation results are given to certify the pinch detection performance of the proposed algorithm and its robustness against the motor parameter uncertainties.

• Journal of IKEEE
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• v.23 no.4
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• pp.1134-1139
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• 2019

One of the most important applications of computer vision algorithms is the detection of threat objects in x-ray security images. However, in the practical setting, this task is complicated by two properties inherent to the dataset, namely, the problem of class imbalance and visual complexity. In our previous work, we resolved the class imbalance problem by using a GAN-based anomaly detection to balance out the bias induced by training a classification model on a non-practical dataset. In this paper, we propose a new method to alleviate the visual complexity problem by using a KNN-based automatic cropping algorithm to remove distracting and irrelevant information from the x-ray images. We use the cropped images as inputs to our current model. Empirical results show substantial improvement to our model, e.g. about 3% in the practical dataset, thus further outperforming previous approaches, which is very critical for security-based applications.

• Food Science and Biotechnology
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• v.18 no.5
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• pp.1118-1123
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• 2009

Event-specific real-time polymerase chain reaction (PCR) detection method for genetically modified (GM) maize MIR604 was developed based on integration junction sequences between the host plant genome and the integrated transgene. In this study, 2 primer pairs and probes were designed for specific amplification of 100 and 111 bp DNA fragments from the zSSIIb gene (the maize endogenous reference gene) and MIR604. The quantitative method was validated using 3 certified reference materials (CRMs) with levels of 0.1, 1, and 10% MIR604. The method was also assayed with 14 different plants and other GM maize. No amplification signal was observed in real-time PCR assays with any of the species tested other than MIR604 maize. As a result, the bias from the true value and the relative deviation for MIR604 was within the range from 0 to 9%. Precision, expressed as relative standard deviation (RSD), varied from 2.7 to 10% for MIR604. Limits of detections (LODs) of qualitative and quantitative methods were all 0.1%. These results indicated that the event-specific quantitative PCR detection system for MIR604 is accurate and useful.