• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1115-1130
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• 2020

Modern vehicles are equipped with a number of ECUs(Electronic Control Units), and ECUs can control vehicles efficiently by communicating each other through CAN(Controller Area Network). However, CAN bus is known to be vulnerable to cyber attacks because of the lack of message authentication and message encryption, and access control. To find these security issues related to vehicle hacking, CAN Fuzzing methods, that analyze the vulnerabilities of ECUs, have been studied. In the existing CAN Fuzzing methods, fuzzing inputs are randomly generated without considering the structure of CAN messages transmitted by ECUs, which results in the non-negligible fuzzing time. In addition, the existing fuzzing solutions have limitations in how to monitor fuzzing results. To deal with the limitations of CAN Fuzzing, in this paper, we propose a Non-Random CAN Fuzzing, which consider the structure of CAN messages and systematically generates fuzzing input values that can cause malfunctions to ECUs. The proposed Non-Random CAN Fuzzing takes less time than the existing CAN Fuzzing solutions, so it can quickly find CAN messages related to malfunctions of ECUs that could be originated from SW implementation errors or CAN DBC(Database CAN) design errors. We evaluated the performance of Non-Random CAN Fuzzing by conducting an experiment in a real vehicle, and proved that the proposed method can find CAN messages related to malfunctions faster than the existing fuzzing solutions.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• Survey Research
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• v.13 no.1
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• pp.135-158
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• 2012

Korean telephone surveys have been based on landline telephone directory or RDD(Random Digit Dialing) method. These days, however, there has been an increase of the households with no landline, or households with the line but not willing to register in the directory. Moreover, it is hard to contact young people or office workers who are usually staying out of home in the daytime. Due to these issues above, the predictability of election polls gets weaker. Especially, low accessibility to those who stay out of home when the poll's done, results in predictions with positive inclination toward conservatism. A solution to resolve this problem is to contact respondents by using both mobile and landline phones-via landline phone to those who are at home and via mobile phone to those who are out of home in the daytime(Mixed Mode Survey, hereafter MMS). To conduct MMS, 1) we need to obtain the sampling frames for the landline and mobile surveys, and 2) we need to decide the proportion of sample size of both. In this paper, we propose a heuristic method for conducting MMS. The method uses RDD for the landline phone survey, and the access panel list for the mobile phone survey. The proportion of sample sizes between landline and mobile phones are determined based on the 'Lifestyle and Time Use Study' conducted by Statistics Korea. As a case study, 4 election polls were conducted in the periods of the special election for the mayor of Seoul on Oct 26th, 2011. From the initial 3 polls, reactions and responses regarding the issues raised during the survey period were appropriately covered, and the final poll showed a very close prediction to the real election result.

• Journal of Korea Entertainment Industry Association
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• v.15 no.6
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• pp.35-54
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• 2021

This study examines the characteristics of CBS's Kim Hyun-Jung's News Show(hearafter News Show) and the change to transmedia. The distinguishing characteristics of News Show compared to radio-based current affairs programs are as follows. First, despite its time limit, it adopts the form of investigative reports or investigative documentaries to uncover the truth of the events through 'Detective Son Su-Ho', etc. Second, News show's interviews have avoided biased stance in the reporting of minority issues by interviewing the affected parties anonymously including people involved in incidents and accidents, bereaved families, and other victims. News Show has been producing a transmedia content called 'That Honey Show' (a show that reads comments as fun as honey) since November 2018. 'That Honey Show' is broadcast in real time on YouTube right after the News Show radio broadcast ends. As a form of spin-off content, 'That Honey Show' breaks down the boundaries among staff, MCs, and guests, as well as shifting roles by using 'vice characters'. The female host, Kim conducts interviews with the main characters related to various issues and extends the fixed identity of current affairs shows to the everyday politics and cultural realms. Thus she draws active participation and responses audience. This paper analyzes two representative broadcast cases of 'That Honey Show'-first, the case of resistance and activity of the BTS fandom ARMY in the US presidential election, and, second, the case of reporting on the Nth room incident. This analysis considers the critical participation of digital citizens and the effect of fostering a sense of community in the current affairs show in the transmedia era.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Korean Journal of Culture and Social Issue
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• v.19 no.2
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• pp.285-318
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• 2013

The purpose of this research is to examine the self-concept in the cyberspace, self-efficacy, relationship with friends, subjective well-being and academic grade among adolescents who are addicted to Internet and those who are not addicted to Internet. A total of 1,057 adolescents (male=545, female=512), 326 from middle school, 361 from high school, and 370 from special education school, participated in the study. The results are as follows. First, qualitative analysis of the conception of self in the cyberspace indicates that those adolescents addicted to Internet reported that in the cyberspace they have fun, followed by they are the same as in real life, they spend time in cyberspace and they can become an imaginary person. Those adolescents not addicted to Internet reported that in the cyberspace they are the same as in real life, followed by they spend time in cyberspace and they can become an imaginary person. When they play Internet games, majority of adolescents in both groups reported that it is fun, followed by they become engrossed and they become aggressive. Second, those adolescents who are not addicted to Internet had higher scores on self-efficacy than those adolescents who are addicted to Internet, including self-regulatory efficacy for learning, relational efficacy, and resiliency of efficacy. Third, the number of friends and close friends that adolescents who are not addicted to Internet were not significantly different from those adolescents who are addicted to Internet. However, those adolescents who are not addicted to Internet were more likely receive social support from friends and were less likely to be social excluded than those adolescents who are addicted to Internet. Fourth, those adolescents who are not addicted to Internet had significantly higher scores on subjective well-being than those adolescents who are addicted to Internet. Fifth, those adolescents who are not addicted to Internet had significantly higher scores on both subjective and objective academic grade than those adolescents who are addicted to Internet.

• Journal of Distribution Science
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• v.12 no.4
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• pp.31-39
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• 2014

Purpose - This study investigates the following two issues. First, we attempt to find the important determinants of housing investment and to identify their significance rank using survey panel data. Recently, the expansion of global uncertainty in the real estate market has directly and indirectly influenced the Korean housing market; households demonstrate a sensitive reaction to changes in that market. Therefore, this study aims to draw conclusions from understanding how the impact of financial strength of the household is related to house investment. Second, we attempt to verify the effectiveness of diverse indices of financial strength such as DTI, LTV, and PIR as measures to monitor the housing market. In the continuous housing market recession after the global crisis, the government places top priority on residence stability. However, the government still imposes forceful restraints on indices of financial strength. We believe this study verifies the utility of these regulations when used in the housing market. Research design, data, and methodology - The data source for this study is the "National Survey of Tax and Benefit" from 2007 (1st) to 2011 (5th) by the Korea Institute of Public Finance. Based on this survey data, we use panel data of 3,838 households that have been surveyed continuously for 5 years. We sort the base variables according to relevance of house investment criteria using the decision tree model (DTM), which is the standard decision-making model for data-mining techniques. The DTM method is known as a powerful methodology to identify contributory variables for predictive power. In addition, we analyze how important explanatory variables and the financial strength index of households affect housing investment with the binary logistic multi-regressive model. Based on the analyses, we conclude that the financial strength index has a significant role in house investment demand. Results - The results of this research are as follows: 1) The determinants of housing investment are age, consumption expenditures, income, total assets, rent deposit, housing price, habits satisfaction, housing scale, number of household members, and debt related to housing. 2) The impact power of these determinants has changed more or less annually due to economic situations and housing market conditions. The level of consumption expenditure and income are the main determinants before 2009; however, the determinants of housing investment changed to indices of the financial strength of households, i.e., DTI, LTV, and PIR, after 2009. 3) Most of all, since 2009, housing loans has been a more important variable than the level of consumption in making housing market decisions. Conclusions - The results of this research show that sound financing of households has a stronger effect on housing investment than reduced consumption expenditures. At the same time, the key indices that must be monitored by the government under economic emergency conditions differ from those requiring monitoring under normal market conditions; therefore, political indices to encourage and promote the housing market must be divided based on market conditions.

• Clean Technology
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• v.26 no.3
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• pp.228-236
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• 2020

Korea has an economy based on manufacturing industrial fields, which produce high amounts of hazardous wastes, in spite of few landfill candidates, and a significant concern for fine airborne particulates; therefore, traditional waste management is difficult to apply in this country. Moreover, waste collection and accumulation have recently been intensified by the waste import prohibitions or regulations in developing nations, the universalization of delivery services in Korea, and the global COVID-19 crisis. This study thus presents a domestic waste management strategy that aims to address the recent issues on waste. The contents of the strategy as the main results of the study include the (1) improvement of the compatibility of the classification codes between the domestic hazardous waste and the international ones such as those of the Basel Convention; (2) consideration of the mixed hazard indices to represent toxicity from low-content components such as rare earth metals often contained in electrical and electronic equipment waste; (3) management application based on risks throughout the life cycles of waste; (4) establishment of detailed material flow information of waste by integrating the Albaro system, Pollutant Release and Transfer Register (PRTR) system, and online trade databases; (5) real-time monitoring and prediction of the waste movement or discharge using positional sensors and geographic information systems, among others; and (6) selection and implementation of optimal treatment or recycling practices through Life Cycle Assessment (LCA) and clean technologies.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1189-1193
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• 2010

Mobility management is one of the most important research issues in 6LoWPAN, Since the IP-WSN application domain is expanded to real-time applications such as healthcare and surveillance systems, a fast and seamless handover becomes an important criterion in 6LoWPAN. However, a draft of IETF 6LoWPAN WG for mobility support does not decrease handover delay. Although LoWMob supports a fast intra-PAN handover. it can be supported when the infrastructure node has the location information of the other nodes in the mobile node's moving direction. In this paper, we propose a fast and seamless mobility protocol to support intra-PAN handover, named intra-MARIO. In intra-MARIO, a parent node of the mobile node preconfigures its handover to the PAN when the parent node detects its movement, thereby reducing the handover delay. Since intra-MARIO also supports route optimization, the mobile node can communicate with its corresponding nodes through the optimal route. In this paper, we analysis the signaling cost and evaluates that the handover can be completed in 20ms by simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.8
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• pp.1620-1625
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• 2004

To advance fisheries, we set developmental directions of fishery information by grasping present situations and analyzing maritime & fisheries issues. We promote various policies through effective systematical information data bases, based on both control and utilization of oceanic resources. For these puposes, it is imperative that we set up fisheries communication networks. There are satellite assisted informational networks to assist fishing vessels with their marine based movements. However, there's no hope for poorly equipped fishermen to adopt this network because of extravagant network call charges. So we think that using existing SSB communication system is the best plan. We organize fishery communication network by HF SSB communication which doesn't have operational costs. We build wireless transmitting and receiving stations that are basic systems of informnation, and equip wireless data communication systems by the use of wireless communication network protocols in coastal stations. It is necessary that a fish boat has a terminal device for wireless data communication. In this research we can conclude that if we transmit the location of a fishing boat in-real time through GPS channels then we propose that some methods be formulated to able terminal devices on fishing boats to collect various types of information, such as meteorological and oceanic conditions.