• Electronics and Telecommunications Trends
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• v.30 no.2
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• pp.68-78
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• 2015

최근 들어 클라우드, 소셜네트워크, 빅데이터 등 보안시장에 영향을 미칠 수 있는 새로운 성장동력원이 등장하면서 정보보호산업이 급격히 진화하고 있다. 본고에서는 정보보호산업의 국내외 시장 전망과 주요국의 정보보호정책을 개관한 후, 최근 주요 선진국을 중심으로 이슈화되고 있는 IoT 정보보호 관련 법 규제 동향을 살펴보았다. 본 분석을 통하여 국내 정보보호산업을 육성하기 위해서는 제품시장도 중요하지만, 상대적으로 부가가치가 높은 서비스시장에 보다 중점을 둔 시장육성 전략이 요구된다는 점과 기존의 정보보호법을 사물인터넷에 적용하기 위한 대책을 서둘러야 한다는 시사점을 얻을 수 있었다.

• Smart Media Journal
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• v.10 no.2
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• pp.92-99
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• 2021

Smart space is a technology that supports humans by interacting with the surrounding environment. Smart space has a built-in dynamic intelligent environment. This paper proposes a framework that provides user-customized dynamic intelligent environments in smart spaces. In the existing research that provides user-customized intelligent services, users' interests are only explicitly analyzed, and smart spaces are not considered. Implicit interest analysis can suggest a service that may be of interest to users rather than explicit interest analysis, but it requires higher performance than explicit interest analysis. Smart spaces can obtain useful information by interacting with information in the space. The framework proposed in the study uses a proximity-based social network of things to fit into a smart space. In addition, the implicit interest analysis provides intelligent information for smart spaces using the social media information and spatial information objects. In addition, we propose a method to prevent performance degradation while maintaining accuracy in consideration of the characteristics of the smart space.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.76-81
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• 2018

The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.113-121
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• 2019

The fourth industrial revolution technology focused on the fusion of infrastructure and various advanced technologies related city. Therefore, technical cooperation in various fields of research is essential. In order to activating the fourth industrial revolution technologies, it is necessary to research the state of technology in various fields. Consequently, this paper aims to analysis of domestic and foreign research trends on technology to the fourth industrial revolution using SNA and text mining for web site. We collected text, date data of research paper and report in web site for five years, that is, from January 1st in 2014 to December 31st in 2018. Next, we have deduced the major keywords in public data through analyzing the morphemes. Then we have analyzed the core and related keyword lists through an SNA. In Korea, the focus is on R&D and legal/institutional solution in relation to the fourth industrial revolution technology. On the other hand, in the case of foreign, there was focus on practical technologies for urban services in detail aspects.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.791-794
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• 2017

IoT, 소셜미디어, 스마트 폰, 웨어러블 기기의 등장함에 따라 발생하는 데이터가 폭발적으로 증가해 바야흐로 "빅 데이터" 시대가 다가왔다. 이에 정부와 기업에서는 빅 데이터를 효율적으로 사용하기 위한 정책을 추진하고 전문 인력 양성에 힘쓰고 있다. 그 중 빅 데이터를 이용한 시각화는 빠른 의사결정을 도와주고, 자료로부터 데이터를 얻는 시간을 단축하고 즉각적인 상황판단이 가능해지는 등 다양한 장점을 가지고 있다. 그러나 무수히 많은 데이터 중 공공데이터를 활용한 시각화에 관한 연구는 현재까지 잘 이루어지지 않고 있다. 따라서 본 논문에서는 공공데이터를 기반으로 데이터 가시화의 활용방법에 대해 제안한다.

• Electronics and Telecommunications Trends
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• v.31 no.4
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• pp.44-54
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• 2016

클라우드 스토리지에 대한 수요가 증가하면서 전 세계적으로 수십 페타바이트까지 지원 가능한 구축 사례들이 점점 늘어나고 있다. 그러나 소셜, 모바일, IoT와 같이 클라우드 스토리지를 이용하는 데이터가 기하급수적으로 증가하면서 2020년경에는 엑사바이트 시대에 진입할 것으로 예상되고 있다. 이처럼 급증하는 클라우드 환경에서의 데이터를 수용하기 위해서는 보다 고용량의 클라우드 스토리지 구축에 대한 필요성이 대두되고 있는 상황이다. 본고에서는 클라우드 환경에서 효율적인 스케일-아웃 방식의 클라우드 스토리지와 관련한 기술동향을 살펴보고 스토리지의 고용량화를 위해 해결해야 할 기술적 이슈들이 무엇인지 분석한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.111-114
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• 2019

최근 봇넷(Botnet)은 PC 뿐만 아니라 IoT 기기를 대상으로 확대되어 구축되고 있으며, 최신 기술들이 적용되면서 탐지와 방어가 어렵도록 구축되고 있다. 특히, 해커와 테러범 사이에서 많이 활용되는 정보 은닉 기술인 스테가노그래피(Steganography)가 적용된 Botnet(Stego-botnet)이 출현하였는데, 기존의 Botnet 형태와는 달리 SNS 환경을 Botnet 개체 사이의 통신 기반으로 활용하며 Steganography 기술로 통신 내용을 숨겨 탐지가 어렵기 때문에 그 위험성과 피해가 심각할 수 있다. 본 논문에서는 SNS 환경에서의 Steganography 기반 Botnet 구축 가능성을 조사하고, 실제로 카카오톡을 활용한 Steganography 기반 Botnet 통신 가능성을 실험한 후 결과를 제시하며, Steganography 기반 Botnet에 대한 탐지 및 역추적 방안을 간략히 제안한다.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.103-112
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• 2014

In recent years, the rapid diffusion of smart devices and growth of internet usage and social media has led to a constant production of huge amount of valuable data set that includes personal information, buying patterns, location information and other things. IT and Production Infrastructure has also started to produce its own data with the vitalization of M2M (Machine-to-Machine) and IoT (Internet of Things). This analysis study researches the applicable effects of Structured and Unstructured Big Data in various business circumstances, and purposes to find out the value creation method for a corporation through the Structured and Unstructured Big Data case studies. The result demonstrates that corporations looking for the optimized big data utilization plan could maximize their creative values by utilizing Unstructured and Structured Big Data generated interior and exterior of corporations.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.465-475
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• 2018

Recently, as the use of social media and IoT has increased, large graph streams has been generating and studies on real-time processing for them have been actively carrying out. In this paper we propose a incremental graph stream processing scheme that reuses previous result data when the graph changes continuously. We also propose a cost model to selectively perform incremental processing and static processing. The proposed cost model computes the predicted value of the detection cost and the processing cost of the recalculation area based on the actually processed history and performs the incremental processing when the incremental processing is more profit than the static processing. The proposed incremental processing increases the efficiency by processing only the part that changes when the graph update occurs. Also, by collecting only the previous result data of the changed part and performing the incremental processing, the disk I/O costs are reduced. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.