• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.115-140
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• 2021

This study divided the keyword sets searched from LISTA database focusing on the overseas open access fields into two types (controlled keywords and uncontrolled keywords), and examined the results of performing an intellectual structure analysis based on profiling for the each keyword type. In addition, these results were compared with those of an intellectual structural analysis based on co-word analysis. Through this, I tried to investigate whether similar results were derived from profiling, another method of intellectual structure analysis, and to examine the differences between co-word analysis and profiling results. As a result, there was a similar difference to the co-word analysis in the results of intellectual structure analysis based on profiling for each of the two keyword types. Also, there were also noticeable differences between the results of intellectual structural analysis based on profiling and co-word analysis. Therefore, intellectual structure analysis using keywords should consider the characteristics of each keyword type according to the research purpose, and better results can be expected to be used based on profiling than co-word analysis to more clearly understand research trends in a specific field.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.66-73
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• 2017

Due to the recent rapid changes in society and wide spread of information devices, diverse digital information is utilized in a variety of economic and social analysis. Information related to the crime statistics by type of crime has been used as a major factor in crime. However, statistical analysis using only the structured data has the difficulty in the investigation by providing limited information to investigators and users. In this paper, structured data and unstructured data are analyzed by applying Korean Natural Language Processing (Ko-NLP) and the Latent Semantic Analysis (LSA) technique. It will provide a crime profile optimum system that can be applied to the crime profiling system or statistical analysis.

• Korean Journal of Forensic Psychology
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• v.13 no.1
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• pp.75-97
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• 2022

Profiling is recognized as a representative application area of domestic criminal psychology, and the National Police Agency profiler is firmly established as a profession. However, compared to the social awareness, the recognition and utilization within the police is not high. In this study, we tried to identify factors affecting the intention to use profiling by identifying the perception of investigators who request and use profiling from a profiler when a violent incident occurs. To this end, the relationship between the perception of the importance of factors considered by investigators in the criminal investigation process and the attitude toward profiling on the intention to use profiling was verified through the path model. As a result of a survey of 340 police investigators, the investigator's perception of the importance of investigation elements was divided into two factors: the importance of normative investigative elements (evidence collection and legal judgment, etc.) and factual investigative elements (criminal analysis, criminal information system analysis, etc.). Among them, the importance of factual investigative elements were found to have a positive effect on the intention to use it by mediating the attitude toward profiling. On the other hand, in the case of the importance of normative investigative elements, it was found to have a negative effect on the attitude toward profiling. These results suggest that the perception that investigators have about investigation, which is their main work area, plays a role in determining whether to request profiling as well as attitude towards profiling. Based on the research results, strategies necessary to activate the use of profiling were discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.987-995
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• 2022

Deep learning-based profiling side-channel analysis has been many proposed. Deep learning-based profiling analysis is a technique that trains the relationship between the side-channel information and the intermediate values to the neural network, then finds the secret key of the attack device using the trained neural network. Recently, cross-device profiling side channel analysis was proposed to consider the realistic deep learning-based profiling side channel analysis scenarios. However, it has a limitation in that attack performance is lowered if the profiling device and the attack device have not the same chips. In this paper, an environment in which the profiling device and the attack device have not the same chips is defined as the different-device, and a novel deep learning-based profiling side-channel analysis on different-device is proposed. Also, MCNN is used to well extract the characteristic of each data. We experimented with the six different boards to verify the attack performance of the proposed method; as a result, when the proposed method was used, the minimum number of attack traces was reduced by up to 25 times compared to without the proposed method.

• Journal of Korean Society of Archives and Records Management
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• v.12 no.2
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• pp.29-50
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• 2012

This study aims to analyze electronic records research domains and trends and to suggest future direction of electronic records research in Korea. One hundred and sixty one articles published in seven domestic journals from 1999 to 2011 were statistically analysed to find out the productivity of electronic records research. Analysis of intellectual structure using descriptor profiling and author profiling as a technique of text mining were performed with those same papers. Some proposals on the future research direction in this field were made.

• Mass Spectrometry Letters
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• v.4 no.1
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• pp.10-17
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• 2013

Recent developments in MS-based glycomics and glycoproteomics have rapidly advanced the field and pushed the boundaries of glyco-analysis into new territories. This review will lay out current workflows and strategies for characterization of the glycoproteome, including (in order of increasing complexity and information content) preliminary site mapping, compositional glycan profiling, isomer-specific glycan profiling, glycosite-specific glycopeptide profiling, and finally, glycoproteomic profiling.

• Smart Media Journal
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• v.11 no.11
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• pp.84-91
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• 2022

Baseboard Management Controller(BMC) supports server monitoring, maintenance, and control functions using various communication interfaces. However, if an unexpected problem occurs during the device driver initialization process, the BMC may not operate normally. Therefore, a boot process profiling tool that accurately analyzes the device driver initialization process and provides a function to check the analysis result is essential. Existing boot process profiling tools do not specifically provide the device driver initialization process and results required for BMC boot process analysis, forcing developers to use a combination of tools to analyze the boot process in detail. In this paper, we propose an integrated profiling tool for BMC's booting process. The proposed tool provides device driver initialization process analysis, CPU and memory usage analysis, and kernel version management functions. Users can easily analyze the booting process using the proposed tool, and the analysis result can be used to shorten the booting time. Also, the proposed tool is implemented in Linux-based BMC, and it is shown that the proposed tool is more efficient than the existing profiling tool.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.6
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• pp.147-154
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• 2000

A numerical procedure to analyze 3-dimensional elastohydrodynamic lubrication was applied on the cam-roller contact of the valve mechanism for a marine diesel engine. Both the pressure distribution and the film thickness between the cam and roller follower were calculated for each time step of the whole cycle. The pressure spike is shown at the outlet of the roller edge and it is getting higher as the external load is increased. An effective profiling method for the roller edge was suggested using the results of elastohydrodynamic lubrication analysis and the peak pressure was removed completely with the new profiling.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.39-49
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• 2020

In this paper, we show that the Chinese standard block cipher SM4 is vulnerable to the side channel attacks and present a countermeasure to resist them. We firstly validate that the secret key of SM4 can be recovered by differential power analysis(DPA) and correlation power analysis(CPA) attacks. Therefore we analyze the vulnerable element caused by power attack and propose a first order masking-based countermeasure to defeat DPA and CPA attacks. Although the proposed countermeasure unfortunately is still vulnerable to the profiling power attacks such as deep learning-based multi layer perceptron(MLP), it can sufficiently overcome the non-profiling attacks such as DPA and CPA.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1291-1300
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• 2020

Recently, a deep learning-based non-profiling side-channel analysis was proposed. The deep learning-based non-profiling analysis is a technique that trains a neural network model for all guessed keys and then finds the correct secret key through the difference in the training metrics. As the performance of non-profiling analysis varies greatly depending on the neural network training model design, a correct model design criterion is required. This paper describes the two types of loss functions and eight labeling methods used in the training model design. It predicts the analysis performance of each labeling method in terms of non-profiling analysis and power consumption model. Considering the characteristics of non-profiling analysis and the HW (Hamming Weight) power consumption model is assumed, we predict that the learning model applying the HW label without One-hot encoding and the Correlation Optimization (CO) loss will have the best analysis performance. And we performed actual analysis on three data sets that are Subbytes operation part of AES-128 1 round. We verified our prediction by non-profiling analyzing two data sets with a total 16 of MLP-based model, which we describe.