• Title/Summary/Keyword: 사이버 ISR

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An Investigation of Users' Privacy Protection Behaviors: Factors Affecting Privacy Protection Technology Adoption (개인정보보호 기술 수용행동에 영향을 미치는 요인에 대한 연구)

  • Choi, Bomi;Park, Minjung;Chai, Sangmi
    • Information Systems Review
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    • v.17 no.3
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    • pp.77-94
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    • 2015
  • As Internet has become a popular media for sharing information, users create and share tremendous volume of information including large amount of personal information in cyberspace. Sharing private information online can enhance strength of social relationship but it could also bring negative consequences like information privacy invasion. Although many companies and governments address the importance of information privacy online, there are countless cases of crimes and hackings relating personal information online world wide. Since there are some researches investigating the role of governments and organizations on online privacy domain but there is little research regarding users' privacy protection behaviors. This study investigates relationship between Internet users' information privacy protection behavior and environmental factors. Especially, this study focuses on users' behaviors regarding information privacy protection technology adoption. According to our research results, users' online privacy protective behaviors positively affected by governmental regulations expressed as an information privacy protection law. In addition, if user is allowed to use anonymity when he or she uses online services, they have more tendencies to adopt privacy protection technologies. The detailed research findings and contribution are discussed as well.

Investigating Key Security Factors in Smart Factory: Focusing on Priority Analysis Using AHP Method (스마트팩토리의 주요 보안요인 연구: AHP를 활용한 우선순위 분석을 중심으로)

  • Jin Hoh;Ae Ri Lee
    • Information Systems Review
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    • v.22 no.4
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    • pp.185-203
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    • 2020
  • With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

Fraud Detection System Model Using Generative Adversarial Networks and Deep Learning (생성적 적대 신경망과 딥러닝을 활용한 이상거래탐지 시스템 모형)

  • Ye Won Kim;Ye Lim Yu;Hong Yong Choi
    • Information Systems Review
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    • v.22 no.1
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    • pp.59-72
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    • 2020
  • Artificial Intelligence is establishing itself as a familiar tool from an intractable concept. In this trend, financial sector is also looking to improve the problem of existing system which includes Fraud Detection System (FDS). It is being difficult to detect sophisticated cyber financial fraud using original rule-based FDS. This is because diversification of payment environment and increasing number of electronic financial transactions has been emerged. In order to overcome present FDS, this paper suggests 3 types of artificial intelligence models, Generative Adversarial Network (GAN), Deep Neural Network (DNN), and Convolutional Neural Network (CNN). GAN proves how data imbalance problem can be developed while DNN and CNN show how abnormal financial trading patterns can be precisely detected. In conclusion, among the experiments on this paper, WGAN has the highest improvement effects on data imbalance problem. DNN model reflects more effects on fraud classification comparatively.

Information Security Job Skills Requirements: Text-mining to Compare Job Posting and NCS (정보보호 직무 수행을 위해 필요한 지식 및 기술: 텍스트 마이닝을 이용한 구인광고와 NCS의 비교)

  • Hyo-Jung Jun;Byeong-Jo Park;Tae-Sung Kim
    • Information Systems Review
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    • v.25 no.3
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    • pp.179-197
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    • 2023
  • As a sufficient workforce supports the industry's growth, workforce training has also been carried out as part of the industry promotion policy. However, the market still has a shortage of skilled mid-level workers. The information security disclosure requires organizations to secure personnel responsible for information security work. Still, the division between information technology work and job areas is unclear, and the pay is not high for responsibility. This paper compares job keywords in advertisements for the information security workforce for 2014, 2019, and 2022. There is no difference in the keywords describing the job duties of information security personnel in the three years, such as implementation, operation, technical support, network, and security solution. To identify the actual needs of companies, we also analyzed and compared the contents of job advertisements posted on online recruitment sites with information security sector knowledge and skills defined by the National Competence Standards used for comprehensive vocational training. It was found that technical skills such as technology development, network, and operating system are preferred in the actual workplace. In contrast, managerial skills such as the legal system and certification systems are prioritized in vocational training.