• The Korean Journal of Physiology and Pharmacology
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• v.23 no.2
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• pp.95-102
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• 2019

Endoplasmic reticulum (ER) stress is mediated by disturbance of $Ca^{2+}$ homeostasis. The store-operated calcium (SOC) channel is the primary $Ca^{2+}$ channel in non-excitable cells, but its participation in agent-induced ER stress is not clear. In this study, the effects of tunicamycin on $Ca^{2+}$ influx in human umbilical vein endothelial cells (HUVECs) were observed with the fluorescent probe Fluo-4 AM. The effect of tunicamycin on the expression of the unfolded protein response (UPR)-related proteins BiP and CHOP was assayed by western blotting with or without inhibition of Orai1. Tunicamycin induced endothelial dysfunction by activating ER stress. Orai1 expression and the influx of extracellular $Ca^{2+}$ in HUVECs were both upregulated during ER stress. The SOC channel inhibitor SKF96365 reversed tunicamycin-induced endothelial cell dysfunction by inhibiting ER stress. Regulation of tunicamycin-induced ER stress by Orai1 indicates that modification of Orai1 activity may have therapeutic value for conditions with ER stress-induced endothelial dysfunction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1280-1300
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• 2020

In the modern financial sector, interest in providing financial services that employ blockchain technology has increased. Blockchain technology is efficient and can operate without a trusted party to store all transaction information; additionally, it provides transparency and prevents the tampering of transaction information. However, new security threats can occur because blockchain technology shares all the transaction information. Furthermore, studies have reported that the private keys of users who use the same signature value two or more times can be recovered. Because private keys of blockchain identify users, private key leaks can result in attackers stealing the ownership rights to users' property. Therefore, as more financial services use blockchain technology, actions to counteract the threat of private key recovery must be continually investigated. Private key recovery studies are presented here. Based on these studies, duplicated signatures generated by blockchain users are defined. Additionally, scenarios that generate and use duplicated signatures are applied in an actual bitcoin environment to demonstrate that actual bitcoin users' private keys can be recovered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.566-576
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• 2017

Key-value stores proved its superiority by being applied to various NoSQL databases such as Redis, Memcached. Lookup performance is important because key-value store applications performs more lookup than insert operations in most environments. However, in traditional applications, lookup may be slow because hash tables are constructed out of linked-list. Therefore, cuckoo hashing has been getting attention from the academia for constant lookup time, and bucketized cuckoo hashing (BCH) has been proposed since it can achieve high load factor. In this paper, we introduce Sorting Cuckoo which inserts data using insertion sort in BCH structure. Sorting Cuckoo determines the existence of a key with a relatively small memory access because data are sorted in each buckets. In particular, the higher memory load factor, the better lookup performance than BCH's. Experimental results show that Sorting Cuckoo has smaller memory access than BCH's as many as about 19 million (25%) in 10 million negative lookup operations (key is not in the table), about 4 million times (10%) in 10 million positive lookup operations (where it is) with load factor 95%.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.187-193
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• 2019

Key-value storage engines are an essential component of growing demand in many computing environments, including social networks, online e-commerce, and cloud services. Recent key-value storage engines offer many features such as transaction, versioning, and replication. In a key-value storage engine, transaction processing provides atomicity through Write-Ahead-Logging (WAL), and a synchronous commit method for transaction processing flushes log data before the transaction completes. According to our observation, flushing log data to persistent storage is a performance bottleneck for key-value storage engines due to the significant overhead of fsync() calls despite the various optimizations of existing systems. In this article, we propose a group synchronization method to improve the performance of the key-value storage engine. We also design and implement a transaction scheduling method to perform other transactions while the system processes fsync() calls. The proposed method is an efficient way to reduce the number of frequent fsync() calls in the synchronous commit while supporting the same level of transaction provided by the existing system. We implement our scheme on the WiredTiger storage engine and our experimental results show that the proposed system improves the performance of key-value workloads over existing systems.

• Review of KIISC
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• v.33 no.5
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• pp.5-10
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• 2023

디지털 시대에 클라우드 서비스가 급성장함에 따라 데이터 보호 및 보안에 대한 지속적인 관심이 요구되고 있다. 수많은 클라우드 서비스들의 필수 구성 요소인 인메모리 키-밸류 스토어 (Key-Value Store)는 데이터 컨텐츠 캐싱부터 공유 상태유지에 이르기까지 다양한 작업을 처리한다. 인메모리 KVS가 클라우드 서비스에서 차지하는 비중을 고려할 때 이러한 인메모리 KVS는 특히 신뢰할 수 없는 클라우드 서비스 제공자 혹은 외부 공격자로부터의 위협 시나리오에서 데이터 침해의 주요 대상이 된다. 본 논문에서는 인메모리 KVS와 관련된 설계, 구현 및 보안 위협 대응의 발전 동향과 최근 기술들을 소개한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.12C
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• pp.1276-1281
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• 2002

Bellare and Rivest proposed the translucent cryptography which was a kind of key recovery system. Translucent cryptography is a system in which the third party can recover encrypted message with the probability p(0$\leq$p$\leq$1). The key recovery agency doesn't need to store the user's private key in advance. The balance between key recovery agency and user can be controlled by the value of p. For example, if p is set to be 0.4 then the key recovery agency can recover 40 out of 100 encrypted messages. In this paper, we show that user can easily deceive the key recovery agency in the translucent cryptography. Then we propose the solution of this problem.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.915-932
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• 2022

According to the Personal Information Protection Act and Pseudonymization Guidelines, the mapping is processed to the hash value of the combination key generation items including Salt value when different combination applicants wish to combine. Example of combination key generation items may include personal information like name, phone number, date of birth, address, and so on. Also, due to the properties of the hash functions, when different applicants store their items in exactly the same form, the combination can proceed without any problems. However, this method is vulnerable to combination in scenarios such as address changing and renaming, which occur due to different database update times of combination applicants. Therefore, we propose a privacy preserving combination key generation scheme robust to updates of items used to generate combination key even in scenarios such as address changing and renaming, based on the thresholds through probabilistic record linkage, and it can contribute to the development of domestic Big Data and Artificial Intelligence business.

• Journal of the Korean Society of Costume
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• v.51 no.2
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• pp.105-120
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• 2001

The purpose of this study is to identify the relationship of self-efficacy, which is a kind of the self concept about one's own ability, to the decision-making process, which is the key part of consumer behavior. The subjects in this study were 985 male and female undergraduates of a university located in the city of Kyongsan, the north Kyongsang province. The collected data were statistically processed by MANOVA and ANOVA. For post test, Scaffle and $\chi$$^2$-test were employed. The followings are findings of this study : 1. Concerning incentive to buying, the group having the weaker general self-efficacy is stimulated more highly by the incentives of self-display, fashion pursuit and economic utility than the group having the stronger general self-efficacy does. 2. Regarding information sources. the factor of observation is frequently used by the group having the weaker general and social self-efficacies more than the group having the stronger general and social self-efficacies. 3. As to the evaluative criteria of clothes, the group having the stronger general and social self-efficacies put a higher value on functional and economical points than the group having the weaker general and social self-efficacies does. 4. As for the evaluative criteria of store the group having the stronger general self-efficacy lays stress on store atmosphere, store attributes and convenient shopping condition, while the group having the weaker general self-efficacy puts emphasis on brand and fashion. 5. In buying apparels, the group having the stronger general and social self-efficacies makes more planned purchase.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.293-298
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• 2017

Recently, much research has been devoted to implementing and provisioning high-performance computing environment using clusters with multiple computers and high-performance networking technologies. In-memory based Key-Value stores, such as Redis or Memcached, are widely used in high performance cluster environments to improve the data processing performance. We can distribute data at different storage nodes, and each computing node can access it at a high speed using these In-memory based Key-Value stores. InfiniBand is a de-facto technology that is widely used to interconnect each node of a cluster. In this paper, we propose a new data pre-fetching scheme for Key-Value store based on high performance clusters to improve the performance. The proposed scheme utilizes the data transfer characteristics of InfiniBand. The results of the simulation show that the proposed scheme can reduce the data transfer time by up to about 28%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1277-1282
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• 2016

The term "Big Data" has been defined to encapsulate a broad spectrum of data sources and data formats. It is often described to be unstructured data due to its properties of variety in data formats. Even though the traditional methods of structuring data in rows and columns have been reinvented into column families, key-value or completely replaced with JSON documents in document-based databases, the fact still remains that data have to be reshaped to conform to certain structure in order to persistently store the data on disc. ETL processes are key in restructuring data. However, ETL processes incur additional processing overhead and also require that data sources are maintained in predefined formats. Consequently, data in certain formats are completely ignored because designing ETL processes to cater for all possible data formats is almost impossible. Potentially, these unconsidered data sources can provide useful insights when incorporated into big data analytics. In this project, using big data solution, Apache Spark, we tapped into other sources of data stored in their raw formats such as various text files, compressed files etc and incorporated the data with persistently stored enterprise data in MongoDB for overall data analytics using MongoDB Aggregation Framework and MapReduce. This significantly differs from the traditional ETL systems in the sense that it is compactible regardless of the data formats at source.