• Journal of Information Technology Services
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• v.22 no.4
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• pp.21-35
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• 2023

Software as Medical Devices (SaMD) is a growing category of medical devices that are composed of software to perform one or more medical purposes. SaMD is less likely to cause physical harm compared to conventional medical devices, particularly medical electrical equipments, and may be more vulnerable to privacy issues. This difference was acknowledged and resulted in introducing new regulation guidance specifically for cybersecurity of SaMD. It guides stakeholders of SaMD what to consider in what context in terms of cybersecurity. This study examines the current guidance of how cybersecurity is considered for SaMD by analyzing current medical device standards, then suggest which concept or details beyond current medical device standards may be applicable through analysis of international standards documents published for software in general.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.56-61
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• 2023

The present study explored a comprehensive investigation of university professors' perspectives on the implementation of ChatGPT - an artificial intelligence-powered language model - in their teaching practices. A diverse group of 30 university professors responded to a questionnaire about the level of their interest in implementing the tool, willingness to apply it, and concerns they have regarding the intervention of ChatGPT in higher education setting. The results showed that the participants are highly interested in employing the tool into their teaching practice, and find that the students are likely to benefit from using ChatGPT in classroom settings. On the other hand, they displayed concerns regarding high depandency on data, privacy-related issues, lack of supports required, and technical contraints. In today's fast-paced society, educators are urged to mindfully apply this inevitable generative AI means with thoughtfulness and ethical considerations to and for their learners. Relevant topics are discussed to successfully intervene AI tools in teaching practices in higher education.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.31-50
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• 2009

As the collected information which is static or dynamic is infinite in ubiquitous computing environments, information overload and invasion of privacy have been pressing issues in the recommendation service. In this study, we propose a recommendation service procedure through P2P, The P2P helps customer to obtain effective and secure product information because of communication among customers who have the similar preference about the products without connection to server. To evaluate the performance of the proposed recommendation service, we utilized real transaction and product data of the Korean mobile company which service character images. We developed a prototype recommender system and demonstrated that the proposed recommendation service makes an effect on recommending product in the ubiquitous environments. We expect that the information overload and invasion of privacy will be solved by the proposed recommendation procedure in ubiquitous environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.296-301
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• 2010

Radio frequency identification(RFID) system can identify an object using wireless transmission. RFID applications are numerous and far reaching. The most interesting and widely used applications are supply chain management for companies. Currently, RFID tags must be detached or killed for security and privacy reasons when tagged objects are purchased. In this paper, we present a new architecture that transfers information about products from the electronic product code information services (EPCIS) server of a company to an individual's personal purchases management (PPM) server when products with RFID codes are sold. It solves the security and privacy issues without detaching the tag. Moreover, the PPM server described in this paper allows customers to handle the expiration dates, updates, location management, and group management of products.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.155-174
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• 2012

As Online Behavioral Advertising is dramatically growing with usefulness of information and user convenience in recent years, there are privacy issues caused by collecting user's behavioral information without their consent. To tackle the problem, the need of Do Not Track regulations is getting much higher. In Korea, however, it has never existed. So, this study is examining the case of the major countries have been enforcing the law and regulations of DNT. After that, it is classified with four domain (law/regulation, corporation, individual, society) to include all stakeholders of OBA. Furthermore, this study may have academic significance by suggesting DNT framework through analysis of them. Providing DNT mechanism consisted of three type (behavioral information, control, DNT system), it can be useful guidelines for companies to support decision making as introduced DNT. As analyzed between DNT and stakeholders based on the study of OBA market, it will be useful basic material of OBA study later.

• Convergence Security Journal
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• v.20 no.2
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• pp.15-28
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• 2020

Smart City is highly anticipated to solve the problems of existing cities and create new added value, but there is also increasing concern about security risks. The negative view of smart city according to security risk awareness is a problem that needs to be improved in order to activate the fourth industrial revolution technology and develop smart city. This study examined risk factors in smart cities based on perceived risk and user resistance theory, and empirically analyzed the relationship with resistance attitudes. According to the empirical analysis with 288 research samples, security, social, and physical risk factors directly affect smart city resistance, while financial, performance, and privacy risk have no significant effect. In addition, it was verified that the security risk can is an antecedent factor for other risk factors, and it was confirmed that it is required to separately discuss the security and privacy risk in the smart city environment. This study shows that it is necessary to prepare policy supports for social interactions as well as security and physical safety issues in order to activate smart city by discussing the risk factors that negatively affect smart city perception from the public's point of view.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.665-672
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• 2015

In this paper, we analyze the international financial biometric adoption cases in smart phones and ATMs and propose a scheme for Korean financial telebiometrics. Regional privacy issues, financial services environment, according to the differences in the direction of government policy introducing biometric aspects were appearing differently. In Korea, due to changes in fin-tech vitalization and outstanding convenience mobile oriented service to the regulatory environment, the introduction of biometric technology is the point that is being actively discussed. In this paper, we propose a scheme for the Korean banking financial sector through the introduction of biometric technology adoption case analysis of each country. Thus, this paper is intended to help that the financial sector makes a precise decision when it is establishes a policy of biometric technology application for electronic financial services.

• The Journal of Bigdata
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• v.5 no.1
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• pp.89-96
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• 2020

Deep learning using an artificial neural network has been recently researched and developed in various fields such as image recognition, big data and data analysis. However, federated learning has emerged to solve issues of data privacy invasion and problems that increase the cost and time required to learn. Federated learning presented learning techniques that would bring the benefits of distributed processing system while solving the problems of existing deep learning, but there were still problems with server-client system and motivations for providing learning data. So, we replaced the role of the server with a blockchain system in federated learning, and conducted research to solve the privacy and security problems that are associated with federated learning. In addition, we have implemented a blockchain-based system that motivates users by paying compensation for data provided by users, and requires less maintenance costs while maintaining the same accuracy as existing learning. In this paper, we present the experimental results to show the validity of the blockchain-based system, and compare the results of the existing federated learning with the blockchain-based federated learning. In addition, as a future study, we ended the thesis by presenting solutions to security problems and applicable business fields.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.733-738
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• 2015

User demographic information is necessary in order to improve the quality of personalized services such as recommendation systems. Mobile data, especially text data, is known to be effective for prediction of user demographic information. However, mobile text data has privacy issues so that its utilization is limited. In this regard, we introduce an on-device gender prediction framework utilizing mobile text data while minimizing the privacy issue. Discriminative word and emoticon sets of each gender are constructed from web documents written by authors of each gender. After gender prediction is performed by comparing discriminative word and emoticon sets with a user's mobile text data, an ensemble method that combines two prediction results draws a final result. From experiments conducted on real-world mobile text data, the proposed on-device framework shows promising results for gender prediction.

• The Journal of Bigdata
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• v.3 no.2
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• pp.1-10
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• 2018

In the field of smart water management, there is an increasing demand for strengthening competitiveness through big data analysis. As a result, systematic management (Governance) of big data is becoming an important issue. Big data governance is a systematic approach to evaluating, directing and monitoring data management, such as data quality assurance, privacy protection, data lifetime management, data ownership and clarification of management rights. Failure to establish big data governance can lead to serious problems by using low quality data for critical decisions. In addition, personal privacy data can make Big Brother worry come true, and IT costs can skyrocket due to the neglect of data age management. Even if these technical problems are fixed, the big data effects will not be sustained unless there are organizations and personnel who are dedicated and responsible for data-related issues. In this paper, we propose a method of building data governance for smart water data management based on big data.