• Title/Summary/Keyword: Big data Era

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A Study on the Model for Preemptive Intrusion Response in the era of the Fourth Industrial Revolution (4차 산업혁명 시대의 선제적 위협 대응 모델 연구)

  • Hyang-Chang Choi
    • Convergence Security Journal
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    • v.22 no.2
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    • pp.27-42
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    • 2022
  • In the era of the Fourth Industrial Revolution, digital transformation to increase the effectiveness of industry is becoming more important to achieving the goal of industrial innovation. The digital new deal and smart defense are required for digital transformation and utilize artificial intelligence, big data analysis technology, and the Internet of Things. These changes can innovate the industrial fields of national defense, society, and health with new intelligent services by continuously expanding cyberspace. As a result, work productivity, efficiency, convenience, and industrial safety will be strengthened. However, the threat of cyber-attack will also continue to increase due to expansion of the new domain of digital transformation. This paper presents the risk scenarios of cyber-attack threats in the Fourth Industrial Revolution. Further, we propose a preemptive intrusion response model to bolster the complex security environment of the future, which is one of the fundamental alternatives to solving problems relating to cyber-attack. The proposed model can be used as prior research on cyber security strategy and technology development for preemptive response to cyber threats in the future society.

Design of educational platform for strategic job plannning (직업준비를 위한 전략적 학습지원 교육플랫폼의 설계)

  • Jung, Myungee;Jung, Myungsun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.272-275
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    • 2022
  • Large-scale online platforms such as MOOCs-Massive Open Online Courses, which provide a variety of educational contents, have provided a learning environment that allows students to freely access and learn anytime and anywhere. Currently, the proportion of online lectures and home-based learning is increasing, and portfolio or experience-based learning such as bootcamp, field activities, and team project-based group learning are also being actively carried out for educational outcomes. At present, interest in nano or microdegree focused on core technology in units of hours or credits is increasing significantly because such strategic intensive education enables effective learning in terms of continuity and efficiency of education. In an era of large changes in job market due to the reorganization of the industrial structure by new technologies, intensive education in specialized new technology fields such as smart mobility, big data, and artificial intelligence is much more conducive to finding a job. With this reason it is attracting attention as an alternative to lifelong learning are receiving In this paper we propose an educational platform that can efficiently and effectively support the purpose learning for the personalized microdegree education in the online learning era.

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Refresh Cycle Optimization for Web Crawlers (웹크롤러의 수집주기 최적화)

  • Cho, Wan-Sup;Lee, Jeong-Eun;Choi, Chi-Hwan
    • The Journal of the Korea Contents Association
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    • v.13 no.6
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    • pp.30-39
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    • 2013
  • Web crawler should maintain fresh data with minimum server overhead for large amount of data in the web sites. The overhead in the server increases rapidly as the amount of data is exploding as in the big data era. The amount of web information is increasing rapidly with advanced wireless networks and emergence of diverse smart devices. Furthermore, the information is continuously being produced and updated in anywhere and anytime by means of easy web platforms, and smart devices. Now, it is becoming a hot issue how frequently updated web data has to be refreshed in data collection and integration. In this paper, we propose dynamic web-data crawling methods, which include sensitive checking of web site changes, and dynamic retrieving of web pages from target web sites based on historical update patterns. Furthermore, we implemented a Java-based web crawling application and compared efficiency between conventional static approaches and our dynamic one. Our experiment results showed 46.2% overhead benefits with more fresh data compared to the static crawling methods.

Optimization of Data Placement using Principal Component Analysis based Pareto-optimal method for Multi-Cloud Storage Environment

  • Latha, V.L. Padma;Reddy, N. Sudhakar;Babu, A. Suresh
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.248-256
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    • 2021
  • Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.

Digital color practice using Adobe AI intelligence research on application method - Focusing on color practice through Adobe Sensei - (어도비 AI 지능을 활용한 디지털 색채 실습에 관한 적용방식 연구 -쎈쎄이(Adobe Sensei)을 통한 색채 실습을 중심으로-)

  • Cho, Hyun Kyung
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.801-806
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    • 2022
  • In the modern era, the necessity of color capability in the digital era is the demand of the era, and research on improving color practice on the subdivided digital four areas that are not in the existing practice is needed. For digital majors who are difficult to solve in existing paint color practice, classes in digital color practice in four more specialized areas are needed, and the use of efficient artificial intelligence was studied for classes in digitized color and color sense. In this paper, we tried to show the expansion of the color practice area by suggesting digital color practice and color matching method based on Photoshop artificial intelligence and big data technology that existing color and color matching were practice that only CMYK could do. In addition, based on the color quantification data of individual users provided by the latest Adobe Sceney program artificial intelligence, the purpose of the practice was to improve learners' predictions of actual color combinations and random colors using filter effects. In conclusion, it is a study on the use of programs that eliminate ambiguity in the mixing process of existing paint practice, secure digital color details, and propose a practical method that can provide effective learning methods for beginners and intermediates to develop their senses through artificial intelligence support. The Adobe program practice method necessary for coloration and main color through theoretical consideration and improvement of teaching skills that are better than existing paint practice were presented.

Improvement of Personal Information Protection Laws in the era of the 4th industrial revolution (4차 산업혁명 시대의 개인정보보호법제 개선방안)

  • Choi, Kyoung-jin
    • Journal of Legislation Research
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    • no.53
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    • pp.177-211
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    • 2017
  • In the course of the emergence and development of new ICT technologies and services such as Big Data, Internet of Things and Artificial Intelligence, the future will change by these new innovations in the Fourth Industrial Revolution. The future of this fourth industrial revolution will change and our future will be data-based society or economy. Since there is personal information at the center of it, the development of the economy through the utilization of personal information will depend on how to make the personal information protection laws. In Korea, which is trying to lead the 4th industrial revolution, it is a legal interest that can not give up the use of personal information, and also it is an important legal benefit that can not give up the personal interests of individuals who want to protect from personal information. Therefore, it is necessary to change the law on personal information protection in a rational way to harmonize the two. In this regard, this article discusses the problems of duplication and incompatibility of the personal information protection law, the scope of application of the personal information protection law and the uncertainty of the judgment standard, the lack of flexibility responding to the demand for the use of reasonable personal information, And there is a problem of reverse discrimination against domestic area compared to the regulated blind spot in foreign countries. In order to solve these problems and to improve the legislation of personal information protection in the era of the fourth industrial revolution, we proposed to consider both personal information protection and safe use by improving the purpose and regulation direction of the personal information protection law. The balance and harmony between the systematical maintenance of the personal information protection legislation and laws and regulations were also set as important directions. It is pointed out that the establishment of rational judgment criteria and the legislative review to clarify it are necessary for the constantly controversial personal information definition regulation and the method of allowing anonymization information as the intermediate domain. In addition to the legislative review for the legitimate and non-invasive use of personal information, there is a need to improve the collective consent system for collecting personal information to differentiate the subject and to improve the legislation to ensure the effectiveness of the regulation on the movement of personal information between countries. In addition to the issues discussed in this article, there may be a number of challenges, but overall, the protection and use of personal information should be harmonized while maintaining the direction indicated above.

Economic Analysis of The Operational Policy for Data Backup with Information Security Threats (정보보호위협하에서 경제적인 데이터백업 운영 정책 분석)

  • Yang, Won Seok;Kim, Tae-Sung;Lee, Doo Ho
    • The Journal of the Korea Contents Association
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    • v.14 no.10
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    • pp.270-278
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    • 2014
  • The stability and security management of IT data becomes more important because information security threats increases rapidly in Big Data era. The operational policy of the data backup considering information security threats is required because the backup policy is the fundamental method that prevents the damage of security threats. We present an economic approach for a data backup system with information security threats which damage the system. The backup operation consists of the differential backup and the batch backup. We present a stochastic model considering the occurrence of information security threats and their damage. We analyze the stochastic model to derive the performance measures for the cost analysis. Finally we analyze the average cost of the system and give numerical examples.

Unusual data local access using inverse order tree (역순트리를 이용한 특이데이터 국소적 접근)

  • Rim, Kwang-Cheol;Seol, Jung-Ja
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.3
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    • pp.595-601
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    • 2014
  • With the advent of the Smart information-communication era, the number of data has increased exponentially. Accordingly, figuring out and analyzing in which area and circumstance the data has been created becomes one of the factors for prompt actions. In this paper identifies how to analyze the data by implementing a route from the lowest module to highest one in an inverse order for the part judgement for the particular data. The script first identifies cluster analisys, paralizes the analysis using the sum of each factors of the cluster with the tree structure, and finally transpose the answer into number. Also, it is designed to place priority on particular answer, thereafter, draws the wanted answer real-time.

Design and Utilization of Connected Data Architecture-based AI Service of Mass Distributed Abyss Storage (대용량 분산 Abyss 스토리지의 CDA (Connected Data Architecture) 기반 AI 서비스의 설계 및 활용)

  • Cha, ByungRae;Park, Sun;Seo, JaeHyun;Kim, JongWon;Shin, Byeong-Chun
    • Smart Media Journal
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    • v.10 no.1
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    • pp.99-107
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    • 2021
  • In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

Development of a driver's emotion detection model using auto-encoder on driving behavior and psychological data

  • Eun-Seo, Jung;Seo-Hee, Kim;Yun-Jung, Hong;In-Beom, Yang;Jiyoung, Woo
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.3
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    • pp.35-43
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    • 2023
  • Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.