• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.77-91
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• 2019

Recent Linux operating systems having been increasingly used, ranging from automotive consoles, CCTV, IoT devices, and mobile devices to various versions of the kernel. Because these devices can be used as strong evidence in criminal investigations, there is a risk of destroying evidence through file deletion. Ext filesystem forensics has been studied in depth because it can recovery deleted files without depending on the kind of device. However, studies have been carried out without consideration of characteristics of file system which may vary depending on the kernel. This problem can lead to serious situations, such as those that can impair investigative ability and cause doubt of evidence ability, when an actual investigation attempts to analyze a different version of the kernel. Because investigations can be performed on various distribution and kernel versions of Linux file systems at the actual investigation site, analysis of the metadata changes that occur when files are deleted by Linux distribution and kernel versions is required. Therefore, in this paper, we analyze the difference of metadata according to the Linux kernel as a solution to this and recovery deleted file. After that, the investigating agency needs to consider the metadata change caused by the difference of Linux kernel version when performing Ext filesystem forensics.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.259-270
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• 2021

Recently, interests in the use of Sharing Bike is increasing in consideration of eco-friendly transportation and safety from viruses. As the technology for collecting and storing data is improved with the development of ICTs, research on mobility using the Sharing Bike Data is also actively progressing. Therefore, this paper analyzes the properties of Sharing Bike Data and cases of researches on it through literature review, and based on the results of the review, data of Eoulling, the Sharing Bike System of Sejong City is analyzed as a way to utilize Sharing Bike Data. Most of the selected literature used structured data, and analyzed it through statistical methods or data mining. Through data analysis, it identified the current status, found out problems of the Sharing Bike System, proposed a solution to solve them, developed plans to activate the use of Sharing Bike. This provides basic data for efficient management and operation plans for Sharing Bike System. Ultimately, it will be possible to explore ways to improve mobility in urban spaces by utilizing Sharing Bike Data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.