• The Transactions of the Korea Information Processing Society
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• v.13 no.7
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• pp.299-310
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• 2024

Software is expensive, labor-intensive, and time-consuming to develop. To solve this problem, many organizations turn to publicly available open source, but they often do so without knowing exactly what they're getting into. Older versions of open source have various security vulnerabilities, and even when newer versions are released, many users are still using them, exposing themselves to security threats. Additionally, compliance with licenses is essential when using open source, but many users overlook this, leading to copyright issues. To solve this problem, you need a tool that analyzes open source versions, vulnerabilities, and license information. Traditional Blackduck provide a wealth of open source information when you request the source code, but it's a heavy lift to build the environment. In addition, Fossology extracts the licenses of open source, but does not provide detailed information such as versions because it does not have its own database. To solve these problems, this paper proposes a version and license detection tool that identifies the open source of a user's source code by measuring the source code similarity, and then detects the version and license. The proposed method improves the accuracy of similarity over existing source code similarity measurement programs such as MOSS, and provides users with information about licenses, versions, and vulnerabilities by analyzing each file in the corresponding open source in a web-based lightweight platform environment. This solves capacity issues such as BlackDuck and the lack of open source details such as Fossology.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.59-66
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• 2022

This study was conducted to find out whether excellent and non-excellent players could be distinguished by the achievement goal orientation(task-orientation, ego-orientation) test and the self-management(physical, interpersonal, training, mental management) test targeting youth soccer players. The subject of this study were 299 players(144 middle school students, 155 high school students) including 131 representative players by age and 168 general players who registered with the Korea Football Association. The questionnaires for data collection include the Task & Ego Orientation in Sport Questionnaire(TEOSQ) developed by Duda and Nicholls(1989) and the athlete self-management questionnaire(ASMQ) developed by Heo Jeong-hoon(2003) was used. For data analysis, frequency analysis, factor analysis, reliability analysis, and discriminant analysis were performed using SPSS 23 version. As a result of analyzing the data, task orientation and ego orientation, which are sub-factors of achievement goal orientation, were both confirmed as tests that did not discriminate between excellent and non-excellent players. On the other hand, the self-management test was confirmed as a test that can discriminate between excellent and non-excellent players in body management, training management, and mental management excluding interpersonal management among the sub-factors of self-managemnet. In particular, among self-management, mental management was identified as the most important factor in discriminating between excellent and non-excellent athletes.

• The Journal of Korean Institute of Information Technology
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• v.17 no.4
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• pp.131-136
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• 2019

People with compromised visual ability suffer from many inconveniences in daily life, such as distinguishing colors, identifying currency notes and realizing the atmospheric temperature. Therefore, to assist the visually impaired people, we propose a system by utilizing optical and infrared cameras. In the proposed system, an optical camera is used to collect features related to colors and currency notes while an infrared camera is utilized to get temperature information. The user is enabled to select the desired service by pushing the button and the appreciate voice information are provided through the speaker. The device can distinguish 16 kinds of colors, four different currency notes, and temperature information in four steps and the current accuracy is around 90%. It can be improved further through block-wise input image, machine learning, and a higher version of the infrared camera. In addition, it will be attached to the stick for easy carrying and to use it more conveniently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.195-199
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• 2009

This paper defines a new variation of CDH problem where an adversary interacts with a challenger and proves its security is equivalent to the CDH problem. This new problem is useful in designing a cryptographic protocol. To show the versatility of this problem, we present a new identification scheme. Finally, we show a decisional version of this protocol.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.41-46
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• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.153-159
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• 2012

Now a days, U-healthcare comes into the spotlight as a new business model which combines RFID technology with medical service in the well-being era and IT popularization. U-healthcare service needs a method that can deals with hand-writing, overlap data, forgery and falsification of data, difference between information version that happen in medical process because of graft between RFID technology and u-healthcare. This paper proposes RFID based user certification protocol to protect user's privacy who gets medical service through U-healthcare. In the protocol, secret information of patient does the XOR with the secret key that is created in the hospital to reconsider the stability of security system of U-healthcare and user's data forgery and falsification and privacy and then saves it in the secret key field of patient in DB table. Also, it informs the case of illegal access to certification server and make it approved the access of u-healthcare service by differentiating whether u-healthcare is illegal or not.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1011-1019
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• 2015

CAPTCHA(Completely Automated Public Turing test to tell Computers and Humans Apart) is a test used in computing to distinguish whether or not the user is computer or human. Many web sites mostly use the character-based CAPTCHA consisting of digits and characters. Recently, with the development of OCR technology, simple character-based CAPTCHA are broken quite easily. As an alternative, many web sites add noise to make it harder for recognition. In this paper, we analyzed the most recent CAPTCHA, which incorporates the addition of the natural images to obfuscate the characters. We proposed an efficient method using support vector machine to separate the characters from the background image and use convolutional neural network to recognize each characters. As a result, 368 out of 1000 CAPTCHAs were correctly identified, it was demonstrated that the current CAPTCHA is not safe.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.345-376
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• 2014

This study examined (1) what effect emotional labor has on an university library, focusing on (2) the relationship among a supervisor's emotional intelligence, the extent of social support and the level of library service on job performance. The survey period took place from 14 Oct. to 4 Nov. 2013. 533 librarians at 13 public and 28 private university libraries were included in the survey. Of the 533 surveys distributed, 529 were returned and used in the final analysis. SPSS Win 21.0 was used for statistical analysis, factor analysis, regression analysis and differential analysis. The survey also shows that a librarian's emotional labor affects emotional intelligence of supervisor, social support and library service level positively. This finding is not the case for the employees in the general service industry. Because the librarian is professional and manages stress better than general employees. This research suggest the following practical measures. Educational programs for librarian's emotional intelligence should be planned in order to improve library service.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.305-318
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• 2023

The complexity of software products led many manufacturers to stitch open-source software for composing a product. Using open-source help reduce the development cost, but the difference in the different development life cycles makes it difficult to keep the product up-to-date. For this reason, even the patches for known vulnerabilities are not adopted quickly enough, leaving the entire product under threat. Existing studies propose to use binary differentiation techniques to determine if a product is left vulnerable against a particular vulnerability. Despite their effectiveness in finding real-world vulnerabilities, they often fail to locate the evidence of a vulnerability if it is a small function that usually is inlined at compile time. This work presents our tool FunRank which is designed to identify the short functions. Our experiments using synthesized and real-world software products show that FunRank can identify the short, inlined functions that suggest that the program is left vulnerable to a particular vulnerability.