• Journal of Platform Technology
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• v.11 no.2
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• pp.15-25
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• 2023

This study analyzes the limitations of the insider threat datasets used for insider threat detection research and compares and analyzes the solution-based insider threat data with public insider threat data using a security solution to overcome this. Through this, we design a data format suitable for insider threat detection and implement a system that can safely share insider threat information between different institutions and companies using blockchain technology. Currently, there is no dataset collected based on actual events in the insider threat dataset that is revealed to researchers. Public datasets are virtual synthetic data randomly created for research, and when used as a learning model, there are many limitations in the real environment. In this study, to improve these limitations, a private blockchain was designed to secure information sharing between institutions of different affiliations, and a method was derived to increase reliability and maintain information integrity and consistency through agreement and verification among participants. The proposed method is expected to collect data through an outflow threat collector and collect quality data sets that posed a threat, not synthetic data, through a blockchain-based sharing system, to solve the current outflow threat dataset problem and contribute to the insider threat detection model in the future.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.267-272
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• 2022

Online exams are not limited by time and space. It has the advantage that it does not require a separate exam site for examinees, and there is no time and cost required to move to the exam site. However, the online exam has the disadvantage that various cheating is possible because the exam is conducted in an individual environment. In addition, there is a difficulty in detecting cheating due to the lack of exam supervision methods. In addition, since the exam process and result data exist only as digital data, it is inconvenient to check directly on the server where the exam result is stored in order to check whether the exam result is forged or not. If the data related to the exam is maliciously changed, the authenticity cannot be verified. In this study, we tried to increase the reliability of the online exam by developing a blockchain-based online exam cheating detection system that stores exam progress-related data in the blockchain to detect cheating. Through the experiment, it was confirmed that forgery and falsification are detected as a result of the exam.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.10 s.340
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• pp.25-30
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• 2005

This paper generalizes the concept of the signal space detection to construct a fixed delay tree search (FDTS) detector which estimates a block of n channel symbols at a time. This technique is applicable to high speed implementation. Two approaches are discussed both of which are based on efficient signal space partitioning. In the first approach, symbol detection is performed based on a multi-class partitioning of the signal space. This approach is a generalization of binary symbol detection based on a two-class pattern classification. In the second approach, binary signal detection is combined with a look-ahead technique, resulting in a highly parallel detector architecture.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2498-2511
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• 1998

본 논문에서는 질의화상을 위한 칼라의 위치묘사 키워드와 칼라 키워드를 칼라특징으로 매핑하여 검색할 수 있는 내용기반 화상 검색 방법을 제안하고 이를 구현하였다. 칼라 키워드는 화상의 칼라 특징을 사용하여 칼라 세그먼트 프리미티브로부터 정의되고, 위치 묘사 키워드는 칼라 영역 정보를 사용하여 위치 세그먼트 프리미티브로부터 정의된다. 정의된 각 칼라 키워드 프리미티브는 화상의 칼라특징으로 매핑되어 저장된 참조화상의 6x6 블록의 칼라 특징과 비교하게 되고 유사도 순치 묘사 키워드와 칼라 키워드 검색의 정확도를 측정하였고, 화상검색 실험결과, 평균 recall/precision이 0.72/0.80를 보임으로써 내용기반 화상 데이터 검색에 제안된 방법이 유용함을 보였다.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2675-2677
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• 2003

본 논문에서는 공간 해상도 감축이 이루어지는 디지털 동영상 변환 부호화기에서의 적응 움직임 벡터 재추정 기법을 제안한다. 영상의 복잡도를 기반으로 한 에러 추정을 통해 움직임 벡터를 1차 추정하고, 이를 기반으로 정제범위를 효율적으로 조절하여 연산량을 감소시킨다. TMN5를 이용한 실험 결과 제안된 방법에 의한 추정 벡터는 기존 방법들에 의해 추정된 벡터보다 더 좋은 화질을 보였으며 적응적 정제 범위 선택에 의해 연산량도 더 적었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.77-84
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• 2015

Most of the existing methods make the index key with every 6 words in every sentence in a document in order to identify copyright infringement between two documents. However, these methods has the disadvantage to take a long time to inspect the copyright infringement because of the long indexing time for the large-scale document. In this paper, we propose a method to select the longest word (called a feature bock) as an index key in the predetermined-sized window which scans a document character by character. This method can be characterized by removing duplicate blocks in the process of scanning a document, dramatically reducing the number of the index keys. The system with this method can find the copyright infringement positions of two documents very accurately and quickly since relatively small number of blocks are compared.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.703-706
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• 2010

Recently, a need to encode a depth image has been raising with the deployment of 3D video services. The 3DV/FTV group in the MPEG has standardized the compression method of depth map image. Because conventional depth map coding methods are independently encoded without referencing the color image, coding performance of conventional algorithms is poor. In this letter, we proposed a novel method which rearranged modes of depth blocks according to modes of corresponding color blocks by using a correlation between color and depth images. In experimental results, the proposed method achieves bits reduction of 2.2% compared with coding method based on JSVM.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.299-308
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• 2019

As the utilization value of personal information becomes higher, discussions about providing personal information are being conducted actively. One of the most common methods of providing personal information is that a group obtains a personal information with a consent of individual. However, the above method has 2 problems. First, more information is exposed than the information required by organization for utilization of personal information. Second, trusted party should provide organization with an authentication of personal information whenever they require personal information. To solve these problems, we propose a personal information management system with blockchain using zk-SNARK(zero-knowledge Succinct Non-interactive ARgument of Knowledge) for privacy. Our proposal enables individuals to guarantee reliability of their information and protect their privacy concurrently using zk-SNARK when they provid organization with their personal information. In addition, it is possible to manage the personal information data while ensuring the integrity of the data using blockchain and it is possible to share the personal information more conveniently than existing systems.

• Journal of Digital Convergence
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• v.18 no.3
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• pp.1-12
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• 2020

The purpose of this study is to explore the trend of blockchain technology through analysis of patents and news articles using text mining, and to suggest the blockchain policy agenda by grasping social interests. For this purpose, 327 blockchain-related patent abstracts in Korea and 5,941 full-text online news articles were collected and preprocessed. 12 patent topics and 19 news topics were extracted with latent dirichlet allocation topic modeling. Analysis of patents showed that topics related to authentication and transaction accounted were largely predominant. Analysis of news articles showed that social interests are mainly concerned with cryptocurrency. Policy agendas were then derived for blockchain development. This study demonstrates the efficient and objective use of an automated technique for the analysis of large text documents. Additionally, specific policy agendas are proposed in this study which can inform future policy-making processes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.571-572
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• 2017

The blockchain technology that implements electronic money uses decentralized computing and all transactions in a blockchain are open to everyone. This technique seems to guarantee anonymity by performing the transaction on the address instead of the user, but by using direction acyclic graph based on the transaction graph, the privacy problem is caused by tracking the addresses. In this paper, we analyze various techniques for centralized processing which makes it difficult to find the relevance on the graph in order to protect the privacy in the block chain technology. We also analyze the techniques of anonymizing in a distributed way to enhance privacy. Using the zero knowledge proof scheme guarantees full distributed anonymity but requires more computation and storage space, and various techniques to make this efficient are proposed. In this paper, we propose a privacy protection scheme of blockchain technology to integrate existing privacy protection techniques into a blockchain technology and perform it more efficiently with a centralized or decentralized technique.