• Journal of information and communication convergence engineering
• /
• v.4 no.4
• /
• pp.166-169
• /
• 2006

Almost all network systems provide an authentication mechanism based on user ID and password. In such system, it is easy to obtain the user password using a sniffer program with illegal eavesdropping. The one-time password and challenge-response method are useful authentication schemes that protect the user passwords against eavesdropping. In client/server environments, the one-time password scheme using time is especially useful because it solves the synchronization problem. In this paper, we present a new identification scheme: OPI(One Pass Identification). The security of OPI is based on the square root problem, and OPI is secure: against the well known attacks including pre-play attack, off-line dictionary attack and server comprise. A number of pass of OPI is one, and OPI processes the password and does not need the key. We think that OPI is excellent for the consuming time to verify the prover.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.3
• /
• pp.627-632
• /
• 2005

Almost all network systems provide an authentication mechanism based on user ID and password. In such system, it is easy to obtain the user password using a sniffer program with illegal eavesdropping. The one-time password and challenge-response method are useful authentication schemes that protect the user passwords against eavesdropping. In client/ server environments, the one-time password scheme using time is especially useful because it solves the synchronization problem. It is the stability that is based on Square Root problem, and we would like to suggest OPI(One Pass Identification), enhancing the stability for all of the well-known attacks by now including Free-playing attack, off-line Literal attack, Server and so on. OPI does not need to create the special key to read the password. OPI is very excellent in identifying the approved person within a very short time.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.1
• /
• pp.81-86
• /
• 2009

Almost all network systems provide an authentication mechanism based on user ID and password. In such system, it is easy to obtain the user password using a sniffer program with illegal eavesdropping. The one-time password and challenge-response method are useful authentication schemes that protect the user passwords against eavesdropping. In client/server environments, the one-time password scheme using time is especially useful because it solves the synchronization problem. In this paper, we propose a new identification scheme One Pass Identification. The security of Password base System is based on the square root problem, and Password base System is secure against the well known attacks including pre-play attack, off-line dictionary attack and server comprise. A number of pass of Password base System is one, and Password base System processes the password and does not need the key. We think that Password base System is excellent for the consuming time to verify the prover.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.155-174
• /
• 2022

From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (