• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.91-102
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• 2012

Network port scan attack is the method for finding ports opening in a local network. Most existing IDSs(intrusion detection system) record the number of packets sent to a system per unit time. If port scan count from a source IP address is higher than certain threshold, it is regarded as a port scan attack. The degree of risk about source IP address performing network port scan attack depends on attack count recorded by IDS. However, the measurement of risk based on the attack count may reduce port scan detection rates due to the increased false negative for slow port scan. This paper proposes a method of summarizing 4 types of information to differentiate network port scan attack more precisely and comprehensively. To integrate the riskiness, we present a risk index that quantifies the risk of port scan attack by using PCA. The proposed detection method using risk index shows superior performance than Snort for the detection of network port scan.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.147-155
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• 2002

In the stereolithography process, the accuracy of product depends on laser power, scan speed, scan width, scan pattern, layer thickness, resin characteristics and so on. Therefore, appropriate process parameters are required for an accurate prototype. This paper presents a method to determine the key process parameters, i.e., laser scan speed, hatching space, and layer thickness based on scan length, scan area, and layer slope. In order to determine these parameters, three neural networks are employed to represent operator’s experience and knowledge. Optimum values on scan speed, hatching space and layer thickness are recommended to improve the surface roughness and build time on the developed SLA machine.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.6
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• pp.482-489
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• 2014

This paper suggests the new network scanning algorithm that makes use of measurement pilot of IEEE 802.11k. The purpose of suggesting this algorithm is to improve the existing network scanning schemes. After introducing new algorithm, this paper shows the difference of time property and energy property between former scanning schemes and new scheme with simulation results. Passive scan has a merit of low-power consumption but it takes too long time to fulfill whole scanning. On the contrary, an advantage of active scan is speed but it consumes more battery power than passive scan. By using measurement pilot's smaller interval than beacon interval, the suggested algorithm can consume less power than active scan does, and also make shorter scanning delay than passive scan does.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.443-452
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• 2004

For stereo lithography process, accuracy of prototypes is related to laser power, scan speed, scan width, scan pattern, layer thickness, resin characteristics and etc. An accurate prototype is obtained by using appropriate process parameters. In order to determine these parameters, the stereolithography (SLA) machine using neural network was developed and efficiency of the developed SLA machine was compared with that of the traditional SLA. Optimum values for scan speed, hatching spacing and layer thickness improved the surface roughness and build time for the developed SLA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.201-206
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• 2007

In this paper, we propose the efficient low power test methodology of NoC(Network-on chip) for the test of core-based systems that use this platform. To reduce the power consumption of transferring data through router channel, the scan vectors are partitioned into flits by channel width. The don't cares in unspecified scan vectors are mapped to binary values to minimize the switching rate between flits. Experimental results for full-scanned versions of ISCAS 89 benchmark circuits show that the proposed method leads to about 35% reduction in test power.

• Convergence Security Journal
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• v.7 no.1
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• pp.63-75
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• 2007

Most of computer systems to be connected to network have been exposed to some network attacks and became to targets of system attack. System managers have established the IDS to prevent the system attacks over network. The previous IDS have decided intrusions detecting the requested connection packets more than critical values in order to detect attacks. This techniques have False Positive possibilities and have difficulties to detect the slow scan increasing the time between sending scan probes and the coordinated scan originating from multiple hosts. We propose the port scan detection rules detecting the RST/ACK flag packets to request some abnormal connections and design the data structures capturing some of packets. This proposed system is decreased a False Positive possibility and can detect the slow scan, because a few data can be maintained for long times. This system can also detect the coordinated scan effectively detecting the RST/ACK flag packets to be occurred the target system.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.543-550
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• 2001

In this paper, an improved detection system for the network vulnerability scan attacks is proposed. The proposed system improves the methodology for detecting the network vulnerability scan attacks and provides a global detection and response capability that can counter attacks occurring across an entire network enterprize. Through the simulation, we show that the proposed system can detect vulnerable port attacks, coordinated attacks, slow scans and slow coordinated attacks. We also show our system can achieve more global and hierarchical response to attacks through the correlation between server and agents than a stand-alone system can make.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.1-10
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• 2003

In this paper, we propose a secure communication framework for interaction and information sharing between a server and agents in DS-NVSA(Detection System of Network Vulnerability Scan Attacks) proposed in〔1〕. For the scalability and interoperability with other detection systems, we design the proposed IDMEF and IAP that have been drafted by IDWG. We adapt IDMEF and IAP to the proposed framework and provide SKTLS(Symmetric Key based Transport Layer Security Protocol) for the network environment that cannot afford to support public-key infrastructure. Our framework provides the reusability of heterogeneous intrusion detection systems and enables the scope of intrusion detection to be extended. Also it can be used as a framework for ESM(Enterprise Security Management) system.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3043-3050
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• 2022

In Korea, all nuclear power plants (NPPs) participate in annual performance tests including in vivo measurements using the FastScan, a stand type whole body counter (WBC), manufactured by Canberra. In 2018, all Korean NPPs satisfied the testing criterion, the root mean square error (RMSE) ≤ 0.25, for the whole body configuration, but three NPPs which participated in an additional lung configuration test in the fission and activation product category did not meet the criterion. Due to the low resolution of the FastScan NaI(Tl) detectors, the conventional peak analysis (PA) method of the FastScan did not show sufficient performance to meet the criterion in the presence of interfering radioisotopes (RIs), ¹³⁴Cs and ¹³⁷Cs. In this study, we developed an artificial neural network (ANN) to improve the performance of the FastScan in the lung configuration. All of the RMSE values derived by the ANN satisfied the criterion, even though the photopeaks of ¹³⁴Cs and ¹³⁷Cs interfered with those of the analytes or the analyte photopeaks were located in a low-energy region below 300 keV. Since the ANN performed better than the PA method, it would be expected to be a promising approach to improve the accuracy and precision of in vivo FastScan measurement for the lung configuration.

• The Journal of the Acoustical Society of Korea
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• v.37 no.2
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• pp.118-128
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• 2018

In this paper, we have studied how to search an underwater object by learning the image generated by the side scan sonar in the convolution neural network. In the method of human side analysis of the side scan image or the image, the convolution neural network algorithm can enhance the efficiency of the analysis. The image data of the side scan sonar used in the experiment is the public data of NSWC (Naval Surface Warfare Center) and consists of four kinds of synthetic underwater objects. The convolutional neural network algorithm is based on Faster R-CNN (Region based Convolutional Neural Networks) learning based on region of interest and the details of the neural network are self-organized to fit the data we have. The results of the study were compared with a precision-recall curve, and we investigated the applicability of underwater object detection in convolution neural networks by examining the effect of change of region of interest assigned to sonar image data on detection performance.