• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.191-198
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• 2022

With the ever-increasing frequency of public sector and smalls-cale industries going live on the internet in developing countries, their security of which, while crucial, is often overlooked in most cases. This is especially true in Government services, whilst essential, are poorly monitored if at all. This is due to lack of funds and personnel. Most available software which can help these organizations monitor their services are either expensive or very outdated. Thus, there is a need for any developing country to develop a networking monitoring system. However, developing a network monitoring system is still a challenge and expensive and out sourcing network monitoring system to third party is a security threat. Therefore, in this article we propose a method to anonymize network logs and outsource networking monitoring system to third-party without breach in integrity of their network logs.

• Journal of the Korean Wood Science and Technology
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• v.31 no.3
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• pp.17-23
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• 2003

As a fundamental study of developing sawdust board from thinning softwood logs from three species (Pinus densiflora S. et Z., Larix leptolepis G. and Pinus koraiensis S. et Z.), this study examined the effect of board density and resin content on physical and mechanical properties of sawdust board. As the board density increase, thickness swelling, bending strength, and Brinell hardness increased while water absorption decreased. With increasing the resin content, the bending strength and hardness increased while water absorption and thickness swelling decreased. The board made of L. leptolepis was slightly low in its water absorption, and the one made of P. koraiensis was a little high in its bending strength, while there was no definite difference between each kind of trees in their hardness values.

• Journal of the Korean Wood Science and Technology
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• v.30 no.3
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• pp.104-108
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• 2002

Nail withdrawal tests were conducted on clear wood of domestic small diameter logs. Nails were driven into the cross and longitudinal sections of each specimen, then nail withdrawal tests were performed. Nail withdrawal loads are strongly dependent on the direction of nail positions. The average load values for the nail withdrawal both in cross section and longitudinal section are higher in high specific gravity (SG) wood of sawtooth oak (Quercus acutissima Carr.) than those in low SG wood of Korean red pine (Pinus densiflora Sieb. et Zucc.) and pitch pine (Pinus rigida Mill.). The average ratio of the nail withdrawal loads for side-grain and end-grain are higher in the low SG wood than that in the high SG of wood. Both linear and non-linear regression analyses were conducted on nail withdrawal load with SG, good correlations were obtained between nail withdrawal load and SG.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.17-26
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• 2023

A smart city is a massive internet of things (IoT) environment, where all terminal devices are connected to a network to create and share information. In accordance with massive IoT environments, millions of IoT devices are connected, and countless data are generated in real time. However, since heterogeneous IoT devices are used, collecting the logs for each IoT device is difficult. Due to these issues, when an IoT device is invaded or is engaged in malicious behavior, such as infection with malware, it is difficult to respond quickly, and additional damage may occur due to information leakage or stopping the IoT device. To solve this problem, in this paper, we propose identifying the attack technique used for initial access to IoT devices through MITRE ATT&CK, collect the logs that can be generated from the identified attack technique, and use them to identify the cause of malware infection.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.235-236
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• 2014

• Proceedings of the Korean Society of Plant Pathology Conference
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• 1999.10a
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• pp.54.1-54
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• 1999

• The Journal of Engineering Geology
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• v.8 no.2
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• pp.163-173
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• 1998

Suite of log analysis techniques consisting of geophysical well log, geological core log, and physical core log have been made to understand the well log responses and to determine the lithology of a test borehole-PABH1 located in Pungam sedimentary basin, Sosok, Hongchon-gun, Kangwon Province. Geological core logging has been precisely made over the cores taken between 64 and 124 meters, and 11 groups of rock types were deduced. Using the core samples divided by 11 groups, geophysical property measurements consisting of resistivity, natural gamma and density were made. Each rock group in the area is shown to have its characteristic physical response from geophysical well log and geophysical core logs. The outstanding physical responses particularly shown from siltstone, coarse sandstone to conglomerate, and granitic gneiss in the area were effectively used as keybeds in correlating the geophysical well logs to the result of geological core logs.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.275-279
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• 2009

Many countries including the US and ED oblige telecommunication service providers to retain communication logs for a certain amount of time. The retained data are used for the purpose of the investigation, detection, or prosecution of serious crimes, but of huge size. In order to efficiently extract information such as a correlation between criminals and suspects, we must eliminate unnecessary data that occupy a large portion of communication logs. In this paper, we propose how to measure the proximity between communication objects using communication logs. The proximity let the collected data be analyzed efficiently: analyzing the data in the decreasing order of proximities or removing the data with low proximities before analyzing. The experimental results show that there is a correlation between proximities of our proposed measurement and estimation by people.

• Journal of KIISE:Databases
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• v.36 no.5
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• pp.374-385
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• 2009

Flash memory becomes increasingly popular as data storage for various devices because of its versatile features such as non-volatility, light weight, low power consumption, and shock resistance. Flash memory, however, has some distinct characteristics that make today's disk-based database technology unsuitable, such as no in-place update and the asymmetric speed of read and write operations. As a result, most traditional disk-based database systems may not provide the best attainable performance on flash memory. To maximize the database performance on flash memory, some approaches have been proposed where only the changes made to the database, i.e., logs, are written to another empty place that has born erased in advance. In this paper, we propose an efficient log management scheme for flash-based database systems. Unlike the previous approaches, the proposed approach stores logs in specially allocated blocks, called log blocks. By evenly distributing logs across log blocks, the proposed approach can significantly reduce the number of write and erase operations. Our performance evaluation shows that the proposed approaches can improve the overall system performance by reducing the number of write and erase operation compared to the previous ones.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.129-137
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• 2016

To identify the cause of the error and maintain the health of system, an administrator usually analyzes event log data since it contains useful information to infer the cause of the error. However, because today's systems are huge and complex, it is almost impossible for administrators to manually analyze event log files to identify the cause of an error. In particular, as OpenStack, which is being widely used as cloud management system, operates with various service modules being linked to multiple servers, it is hard to access each node and analyze event log messages for each service module in the case of an error. For this, in this paper, we propose a novel message-based log analysis method that enables the administrator to find the cause of an error quickly. Specifically, the proposed method 1) consolidates event log data generated from system level and application service level, 2) clusters the consolidated data based on messages, and 3) analyzes interrelations among message groups in order to promptly identify the cause of a system error. This study has great significance in the following three aspects. First, the root cause of the error can be identified by collecting event logs of both system level and application service level and analyzing interrelations among the logs. Second, administrators do not need to classify messages for training since unsupervised learning of event log messages is applied. Third, using Dynamic Time Warping, an algorithm for measuring similarity of dynamic patterns over time increases accuracy of analysis on patterns generated from distributed system in which time synchronization is not exactly consistent.