• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1738-1756
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• 2020

To improve the accuracy and realism of the virtual surgical simulation system, this paper proposes an optimized mass-spring model with shape restoration ability based on volume conservation to simulate soft tissue deformation. The proposed method constructs a soft tissue surface model that adopts a new flexion spring for resisting bending and incorporates it into the mass-spring model (MSM) to restore the original shape. Then, we employ the particle swarm optimization algorithm to achieve the optimal solution of the model parameters. Besides, the volume conservation constraint is applied to the position-based dynamics (PBD) approach to maintain the volume of the deformable object for constructing the soft tissue volumetric model base on tetrahedrons. Finally, we built a simulation system on the PHANTOM OMNI force tactile interaction device to realize the deformation simulation of the virtual liver. Experimental results show that the proposed model has a good shape restoration ability and incompressibility, which can enhance the deformation accuracy and interactive realism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3488-3500
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• 2020

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years, the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.486-503
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• 2023

Logs play an important role in mastering the health of the system, experienced operation and maintenance engineer can judge which part of the system has a problem by checking the logs. In recent years, many system architectures have changed from single application to distributed application, which leads to a very huge number of logs in the system and manually check the logs to find system errors impractically. To solve the above problems, we propose a method based on Message Middleware and ATT-GRU (Attention Gate Recurrent Unit) to detect the logs anomaly of distributed systems. The works of this paper mainly include two aspects: (1) We design a high-performance distributed logs collection architecture to complete the logs collection of the distributed system. (2)We improve the existing GRU by introducing the attention mechanism to weight the key parts of the logs sequence, which can improve the training efficiency and recognition accuracy of the model to a certain extent. The results of experiments show that our method has better superiority and reliability.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.497-501
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• 2010

A software montage means information that can be extracted quickly from software and includes inherent characteristics. If a montage is made from well-known programs, we can filter candidates of similar programs among the group of programs based on the montage. In this paper, we suggest software montages based on two characteristics: API calls and strings. To evaluate the proposed montages, we performed experiments to filter candidates of some similar programs to instant messenger programs. From the experiments, we confirmed that the proposed montages can be used as a forensic tool that filters a group of similar programs even when their functions are not known in advance.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.123-128
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• 2020

As the use of digital devices is becoming more commonplace, digital forensics techniques recover data to collect physical evidence during the investigation. Among them, the file forensics technique recovers deleted files, therefore, it can recover the database by recovering all files which compose the database itself. However, if the record is deleted from the database, the modified record contents will not be restored even if the file is recovered. For this reason, the database forensics technique is required to recover deleted records. Database forensics obtains metadata from database configuration files and recovers deleted records from data files. However, record recovery is difficult if database metadata such as block size cannot be obtained from the database. In this paper, we propose three methods for obtaining block size, which is database metadata. The first method uses the maximum size of free space in the block, and the second method uses the location where the block appears. The third method improves the second method to find the block size faster. The experimental results show that three methods can correctly find the block size of three DBMSes.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.47-55
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• 2021

Purpose: Organizational crime is an offense committed by an individual or an official in a corporate entity for organizational gain. This study aims to explore the literature on challenges facing digital forensics and further discuss possible solutions to such challenges as far as the protection of corporate crime is concerned. Research design, data and methodology: Qualitative textual methodology matches the interpretative approach since it is a quality method meant to consider the inductivity of strategies. Also, a qualitative approach is vital because it is distinct from the techniques used in optimistic paradigms linked to science laws. Results: For achieving justice through the investigation of digital forensic, there is a need to eradicate corporate crimes. This study suggests several solutions to reduce corporate crime such as 'Solving a problem to Anti-forensic Techniques', 'Cloud computing technique', and 'Legal Framework' etc. Conclusion: As corporate crime increases in rate, the data collected by digital forensics increases. The challenge of analyzing chunks of data requires digital forensic experts, who need tools to analyze them. Research findings shows that a change of the operating system and digital evidence interpretation is becoming a challenge as the new computer application software is not compatible with older software's structure.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.525-533
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• 2015

MS Office suit software is the most widely used electronic documents by a large number of users in the world, which has absolute predominance in office software market. MS Office 2007-2013 documents, which use new office open extensible markup language (OOXML) format, could be illegally used as cover mediums to transmit secret information by offenders, because they do not easily arouse others suspicion. This paper proposes nine forensic methods and an integrated forensic tool for OOXML format documents on the basis of researching the potential information hiding methods. The proposed forensic methods and tool cover three categories; document structure, document content, and document format. The aim is to prevent covert communication and provide security detection technology for electronic documents downloaded by users. The proposed methods can prevent the damage of secret information embedded by offenders. Extensive experiments based on real data set demonstrate the effectiveness of the proposed methods.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.8-16
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• 2022

In this paper, we propose a method of reconstructing the file system to obtain digital forensics information from the APFS file system when meta information that can know the structure of the file system is deleted due to partial damage to the disk. This method is to reconstruct the tree structure of the file system by only retrieving the B-tree node where file/directory information is stored. This method is not a method of constructing nodes based on structural information such as Container Superblock (NXSB) and Volume Checkpoint Superblock (APSB), and B-tree root and leaf node information. The entire disk cluster is traversed to find scattered B-tree leaf nodes and to gather all the information in the file system to build information. It is a method of reconstructing a tree structure of a file/directory based on refined essential data by removing duplicate data. We demonstrate that the proposed method is valid through the results of applying the proposed method by generating numbers of user files and directories.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.10-18
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• 2022

Since High Sierra, APFS has been used as the main file system. It is a well-established file system that has been used stably thus far. From the perspective of digital forensics, there are still many areas to be investigated. Apple File System Reference is provided to the apple developer site, but it is not satisfactory to fully analyze APFS. Researchers know more about the structure of APFS than before, but they have not yet fully analyzed its structure to a perfect level about it. In this paper, we develop APFS object identification tool for digital forensics. The most basic and essential object identification and analysis of the APFS filesystem will be conducted with the tool. The analysis in this study serves as the background for an analysis of the checkpoint operation principle and structure, including the more complex B-tree structure of APFS. There are several options for the developed tool, but the results of two use cases will be shown here. Based on the implemented tool, it is hoped that more functions will be added to make APFS a useful tool for faster and more accurate analyses.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.178-192
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• 2021

File system forensics typically focus on the contents or timestamps of a file, and it is common to work around file/directory centers. But to recover a deleted file on the disk or use a carving technique to find and connect partial missing content, the evidence must be analyzed using cluster-centered analysis. Forensics tools such as EnCase, TSK, and X-ways, provide a basic ability to get information about disk clusters, but these are not the core functions of the tools. Alternatively, Sysinternals' DiskView tool provides a more intuitive visualization function, which makes it easier to obtain information around disk clusters. In addition, most current tools are for Windows. There are very few forensic analysis tools for MacOS, and furthermore, cluster analysis tools are very rare. In this paper, we developed a tool named FACT (Forensic Analyzer based Cluster Information Tool) for analyzing the state of clusters in a HFS+ file system, for digital forensics. The FACT consists of three features, a Cluster based analysis, B-tree based analysis, and Directory based analysis. The Cluster based analysis is the main feature, and was basically developed for cluster analysis. The FACT tool's cluster visualization feature plays a central role. The FACT tool was programmed in two programming languages, C/C++ and Python. The core part for analyzing the HFS+ filesystem was programmed in C/C++ and the visualization part is implemented using the Python Tkinter library. The features in this study will evolve into key forensics tools for use in MacOS, and by providing additional GUI capabilities can be very important for cluster-centric forensics analysis.