• International journal of advanced smart convergence
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• v.12 no.2
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• pp.56-66
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• 2023

The goal of deep learning is to extract complex features from multidimensional data use the features to create models that connect input and output. Deep learning is a process of learning nonlinear features and functions from complex data, and the user data that is employed to train deep learning models has become the focus of privacy concerns. Companies that collect user's sensitive personal information, such as users' images and voices, own this data for indefinite period of times. Users cannot delete their personal information, and they cannot limit the purposes for which the data is used. The study has designed a deep learning method that employs privacy protection technology that uses distributed collaborative learning so that multiple participants can use neural network models collaboratively without sharing the input datasets. To prevent direct leaks of personal information, participants are not shown the training datasets during the model training process, unlike traditional deep learning so that the personal information in the data can be protected. The study used a method that can selectively share subsets via an optimization algorithm that is based on modified distributed stochastic gradient descent, and the result showed that it was possible to learn with improved learning accuracy while protecting personal information.

• Knowledge Management Research
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• v.18 no.3
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• pp.63-80
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• 2017

Big Data environment is established by accumulating vast amounts of data as users continuously share and provide personal information in online environment. Accordingly, the more data is accumulated in online environment, the more data is accessible easily by third parties without users' permissions compared to the past. By utilizing strategies based on data-driven, firms recently make it possible to predict customers' preferences and consuming propensity relatively exactly. This Big Data environment, on the other hand, establishes 'Dataveillance' which means anybody can watch or control users' behaviors by using data itself which is stored online. Main objective of this study is to identify the relationship between Dataveillance and users' online privacy protection behaviors. To achieve it, we first investigate perceived online service efficiency; loss of control on privacy; offline surveillance; necessity of regulation influences on users' perceived threats which is generated by Dataveillance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.121-134
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• 2009

Consumer-centric marketing business is surely one of the most successful emerging business but it poses a threat to personal privacy. Between the service provider and the user there are many contrary issues to each other. The enterprise asserts that to abuse the privacy data which is anonymous there is not a problem. The individual only will not be able to willingly submit the problem which is latent. Web traffic analysis technology itself doesn't create issues, but this technology when used on data of personal nature might cause concerns. The most criticized ethical issue involving web traffic analysis is the invasion of privacy. So we need to inspect how many and what kind of personal informations being used and if there is any illegal treatment of personal information. In this paper, we inspect the operation of consumer-centric marketing tools such as web log analysis solutions and data gathering services with web browser toolbar. Also we inspect Microsoft explorer-based toolbar application which records and analyzes personal web browsing pattern through reverse engineering technology. Finally, this identified and explored security and privacy requirement issues to develop more reliable solutions. This study is very important for the balanced development with personal privacy protection and web traffic analysis industry.

• Informatization Policy
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• v.21 no.1
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• pp.17-34
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• 2014

The study on the structure of personal information flows is very important because government can measure and respond the risks caused by companies which collect personal information from other personal data users to operate their business. Recently, as the value of personal information is increasing, number of companies which intend to process a large scale of personal information is increasing too. Accordingly, the issue on the structure of personal data flow has become important for the leading personal information processors which receive far more personal information from others to comply the personal information protection laws. However, research on this issue has rarely performed so far. Therefore, this study proposes a framework for personal information data flow structure based on network theory. Theoretically, the results of the study may contribute to extending the application areas of the network theory to personal information area. Practically, the study may contribute to assisting regulatory authorities to find and monitor personal information processors.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.767-777
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• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.

• The Journal of Society for e-Business Studies
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• v.17 no.3
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• pp.43-60
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• 2012

This study reviews the life cycle models considering legal and technical characteristics of personal data respectively. Based on the reviews, this research proposes 'consent and management based model of personal data' which is applicable to the domestic IT companies. The model suggested in this paper has characteristics that 'Consent' and 'Management' factors are ㅁpositively considered, which is overlooked in the other models. The validity of the model is examined by two methods, validation of the model of excellence by contrast of the other models, and 'consent' and 'management' factors cover all the life cycle processes. Using this model, IT companies will be contributed to the analysis of the personal data utilization and the development of IT system protection.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1161-1170
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• 2013

Currently in 2013, a law that was drawn as a result of social agreement for personal information protection was enacted, and through several amendments, definite policy of written law and guideline were presented for definitive information protection in various fields of social business including IT field. Based on a series of social issues about the importance of personal information, a new access paradigm to personal information appeared. And from macroscopic access method called information protection, the necessity of technical access method came to the fore. Of course, it seems somewhat irrational to restrict all data in the form of personal information to a certain category of information until now. But in the deluge of information based on IT field, it is true that the part of checking the flow of personal information and selecting as security target has been standardized. But still there are cases in which it is difficult to routinely apply the five standardized flows of personal information Life-Cycle-collect, process, provide, store, and destroy-to information that all companies and organizations have. Therefore, the researcher proposes the standardized methodology by proposing the access control methodology for dualised hierarchical personal information Life-Cycle. The results of this research aim to provide practical data which makes optimal access control to personal information Life-Cycle possible.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.19-25
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• 2024

This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1205-1219
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• 2019

As the ability to use data becomes competitive power in the data-driven economy, the effort to create economic value by using personal data is emphasized as much as to protect personal data. EU's PSD2(the second Payment Service directive) became the initiative of the Open Banking trends all over the world, as it is the Mydata policy which protects the data subject's right by empowering the subject to control over the personal data with the right to data portability and promotes personal data usages and transfer. Korean government is now fast adopting EU's PSD2 in financial sector, but there is growing concerns in personal data abuse and misuse, and data breach. This study analyzes domestic financial Mydata policy in comparison with EU's PSD2 and focus on Personal information life-cycle risks of financial Mydata policy. Some suggestions on how to promote personal information and privacy in domestic financial Mydata Policy will be given.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.57-69
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• 2013

Progresses in ICT make the processing and exchange of personal data across international borders often necessary and relatively easy. The challenge lies in protecting fundamental rights and freedoms of individuals, notably the right to privacy and the right to personal information, while encouraging the free and secure flow of information across borders for the continued expansion of online transactions. The key to establishing a functioning international solution for personal data protection is to strike a right balance between the two camps which currently dominate the debate - the advocates of individual privacy rights on one side exemplified by the EU, and the proponents of self-regulation and economic efficiency on the other, represented by the U.S. In the face of a growing tension between the two sides each equipped with their own ideals, a practical solution may lie in utilizing established institutions of standardization such as ISO and IEC as a ground upon which an agreement can take its root.