• Title/Summary/Keyword: 네트워크 확장

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Characterization of pH Dependent Properties of mCherry Mutant, I202T (형광 단백질 mCherry-I202T의 pH 감응성 분석)

  • Lee, Sangmin;Chung, Minsub
    • Applied Chemistry for Engineering
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    • v.32 no.1
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    • pp.10-14
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    • 2021
  • mCherry is one of the well-understood red fluorescent proteins which has a similar tertiary structure as GFPs, but pH resistant due to the lack of hydrogen bond network. Whereas mCherry-I202T showed far-red fluorescence and also pH sensitive property because of the additional hydrogen bond formed by substituting Ile of 202 amino acid sequence on mCherry with Thr. In order to verify the pH sensitive characteristic of mCherry-I202T owing to the extension of hydrogen bond, UV-vis spectrum was measured over the range of acidic to basic pH. We also demonstrate further possibilities of applying mCherry-I202T as a pH sensor.

Effect of Media Literacy on the Formation of Smart Divide (미디어 리터러시가 스마트 디바이드 형성에 미치는 영향)

  • Lee, Seungmin
    • Journal of the Korean Society for information Management
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    • v.38 no.2
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    • pp.19-38
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    • 2021
  • This study empirically analyzed the effect of media literacy on the formation of the smart divide, which is a multi-faceted digital divide that occurs in the context of the use of smart devices. As a result, most of the factors of media literacy affect the establishment of social relations and social network through the use of smart devices, which, in turn, leads to the expansion of the range of informational and social activities. In addition, media literacy has a significant effect on the competence to evaluate the value of information acquired through the use of smart devices. Based on these results, there can be social disparity between those who have secured media literacy and those who do not from the perspective of informational and social benefits through the use of smart devices, which can function as a mechanism to generate the smart divide.

A Defense Mechanism Against Attacks on Files by Hiding Files (파일 은닉을 통한 파일 대상 공격 방어 기법)

  • Choi, Jione;Lee, Junghee;Lee, Gyuho;Yu, Jaegwan;Park, Aran
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.2
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    • pp.1-10
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    • 2022
  • Deception technology is an extended concept of honeypot, which detects, prevents or delays attacks by deceiving adversaries. It has been applied to various system components such as network ports, services, processes, system calls and database management systems. We can apply the same concept to attacks on files. A representative example of a file attack is ransomware. Ransomware is a type of malware that encrypts user files and ask for ransom to recover those files. Another example is the wiper attack, which erases all or target files of a system. In this paper we propose a defense mechanism against these kinds of attacks by hiding files. Compared to backup or virtualization techniques, the proposed method incurs less space and performance overheads.

A slide reinforcement learning for the consensus of a multi-agents system (다중 에이전트 시스템의 컨센서스를 위한 슬라이딩 기법 강화학습)

  • Yang, Janghoon
    • Journal of Advanced Navigation Technology
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    • v.26 no.4
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    • pp.226-234
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    • 2022
  • With advances in autonomous vehicles and networked control, there is a growing interest in the consensus control of a multi-agents system to control multi-agents with distributed control beyond the control of a single agent. Since consensus control is a distributed control, it is bound to have delay in a practical system. In addition, it is often difficult to have a very accurate mathematical model for a system. Even though a reinforcement learning (RL) method was developed to deal with these issues, it often experiences slow convergence in the presence of large uncertainties. Thus, we propose a slide RL which combines the sliding mode control with RL to be robust to the uncertainties. The structure of a sliding mode control is introduced to the action in RL while an auxiliary sliding variable is included in the state information. Numerical simulation results show that the slide RL provides comparable performance to the model-based consensus control in the presence of unknown time-varying delay and disturbance while outperforming existing state-of-the-art RL-based consensus algorithms.

Analysis of Cyber Incident Artifact Data Enrichment Mechanism for SIEM (SIEM 기반 사이버 침해사고 대응을 위한 데이터 보완 메커니즘 비교 분석)

  • Lee, Hyung-Woo
    • Journal of Internet of Things and Convergence
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    • v.8 no.5
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    • pp.1-9
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    • 2022
  • As various services are linked to IoT(Internet of Things) and portable communication terminals, cyber attacks that exploit security vulnerabilities of the devices are rapidly increasing. In particular, cyber attacks targeting heterogeneous devices in large-scale network environments through advanced persistent threat (APT) attacks are on the rise. Therefore, in order to improve the effectiveness of the response system in the event of a breach, it is necessary to apply a data enrichment mechanism for the collected artifact data to improve threat analysis and detection performance. Therefore, in this study, by analyzing the data supplementation common elements performed in the existing incident management framework for the artifacts collected for the analysis of intrusion accidents, characteristic elements applicable to the actual system were derived, and based on this, an improved accident analysis framework The prototype structure was presented and the suitability of the derived data supplementary extension elements was verified. Through this, it is expected to improve the detection performance when analyzing cyber incidents targeting artifacts collected from heterogeneous devices.

Strategies for the Implementation of Cultural Heritage Night Travel Program Using Cognitive Inspection (인지시학을 적용한 문화재 야행(夜行) 프로그램 구현 전략)

  • Park, Seong-Ho
    • The Journal of the Korea Contents Association
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    • v.22 no.10
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    • pp.103-113
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    • 2022
  • As globalization progresses and localization takes place, interest in local culture is increasing. In line with this trend, the Cultural Heritage Administration has been promoting the Cultural Heritage Night Tour Project as a night-type cultural property tourism content since 2016. Cultural property nightlife, part of the regional regeneration project, creates new added value by converging and combining various historical and cultural-related contents centered on local cultural heritage. Although the "cultural nightlife" has been greatly activated, it is judged that changes are needed to continue. This is because fixed nightlife programs are positive in terms of establishing a nationwide network, but there is a limitation in that they cannot be standardized and expanded to various forms. Therefore, in this study, the meaning and limitations of nightlife programs were identified, and cognitive theory applicable to nightlife programs was considered. Through this process, it was confirmed that cognitive poetry's 'circular for dynamic semantic composition', 'surreal foreground', and 'adventures in time and space' can be applied to nightlife programs. As a result of combining cognitive poetry with nightlife programs, it was possible to present a strategy for implementing nightlife programs differentiated from existing nightlife programs.

RIDS: Random Forest-Based Intrusion Detection System for In-Vehicle Network (RIDS: 랜덤 포레스트 기반 차량 내 네트워크 칩입 탐지 시스템)

  • Daegi, Lee;Changseon, Han;Seongsoo, Lee
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.614-621
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    • 2022
  • This paper proposes RIDS (Random Forest-Based Intrusion Detection), which is an intrusion detection system to detect hacking attack based on random forest. RIDS detects three typical attacks i.e. DoS (Denial of service) attack, fuzzing attack, and spoofing attack. It detects hacking attack based on four parameters, i.e. time interval between data frames, its deviation, Hamming distance between payloads, and its diviation. RIDS was designed in memory-centric architecture and node information is stored in memories. It was designed in scalable architecture where DoS attack, fuzzing attack, and spoofing attack can be all detected by adjusting number and depth of trees. Simulation results show that RIDS has 0.9835 accuracy and 0.9545 F1 score and it can detect three attack types effectively.

Understanding the Categories and Characteristics of Depressive Moods in Chatbot Data (챗봇 데이터에 나타난 우울 담론의 범주와 특성의 이해)

  • Chin, HyoJin;Jung, Chani;Baek, Gumhee;Cha, Chiyoung;Choi, Jeonghoi;Cha, Meeyoung
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.9
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    • pp.381-390
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    • 2022
  • Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.

Applying a Novel Neuroscience Mining (NSM) Method to fNIRS Dataset for Predicting the Business Problem Solving Creativity: Emphasis on Combining CNN, BiLSTM, and Attention Network

  • Kim, Kyu Sung;Kim, Min Gyeong;Lee, Kun Chang
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.8
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    • pp.1-7
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    • 2022
  • With the development of artificial intelligence, efforts to incorporate neuroscience mining with AI have increased. Neuroscience mining, also known as NSM, expands on this concept by combining computational neuroscience and business analytics. Using fNIRS (functional near-infrared spectroscopy)-based experiment dataset, we have investigated the potential of NSM in the context of the BPSC (business problem-solving creativity) prediction. Although BPSC is regarded as an essential business differentiator and a difficult cognitive resource to imitate, measuring it is a challenging task. In the context of NSM, appropriate methods for assessing and predicting BPSC are still in their infancy. In this sense, we propose a novel NSM method that systematically combines CNN, BiLSTM, and attention network for the sake of enhancing the BPSC prediction performance significantly. We utilized a dataset containing over 150 thousand fNIRS-measured data points to evaluate the validity of our proposed NSM method. Empirical evidence demonstrates that the proposed NSM method reveals the most robust performance when compared to benchmarking methods.

A Study on the Development Direction of Traditional Cultural Contents in the Age of Convergence Media (융합미디어 시대에서 전통문화 콘텐츠의 발전방향 연구)

  • Shan, Xinyi;Chung, Jeanhun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.99-104
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    • 2022
  • In the age of convergent media, traditional media and network media are highly integrated, and benefits are shared, which promotes the increase of traditional culture communication channels, the change of communication methods, and the change of the mode of interaction with audiences. This article analyzes the difficulties of traditional culture dissemination by enumerating some excellent cultural programs in China. At the same time, combined with the current situation of convergence media, it discusses how to transform invisible traditional culture into visual digital content, and make it widely disseminated by means of convergence media. It provides reference for the development of traditional culture, and has enlightening significance for creating high-quality cultural programs and spreading mainstream culture.