• Smart Media Journal
• /
• v.11 no.10
• /
• pp.76-88
• /
• 2022

Personal information leakage is very harmful as it can lead to additional attacks using leaked information as well as privacy invasion, and it is primarily caused by hacking server databases of institutions that collect and store personal information. We propose a scheme that allows a service-requesting user to authorize a secure delegated transfer of his personal information to the service provider via a reliable authority and enables only the two parties of the service to retrieve the provided information stored on a blockchain ensuring data confidentiality. It thus eliminates the necessity of storing customer information in the service provider's own database. As a result, the service provider can serve customers without requiring membership registration or storing personal information in the database, so that information leakage through the server database can be completely blocked. In addition, the scheme is free from the risk of information leakage and subsequent attacks through smartphones because it does not require a user's smartphone to store any authentication credential or personal information of its owner.

• Smart Media Journal
• /
• v.12 no.2
• /
• pp.42-55
• /
• 2023

The combination of blockchain (BC), artificial Intelligence (AI), quantum computing (QC), and the Internet of Things (IoT) can potentially transform various industries and domains, including healthcare, logistics, and finance. In this paper, we look at the trends and developments in integrating these emerging technologies and the potential benefits and challenges that come with them. We present a conceptual framework for integrating BC, AI, QC, and IoT and discuss the framework's key characteristics and challenges. We also look at the most recent cutting-edge research and developments in integrating these technologies, as well as the key challenges and opportunities that come with them. Our analysis highlights the potential benefits of integrating the technologies and looks to increased security, privacy, and efficiency to provide insights into the future of these technologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.184-186
• /
• 2022

Recently, as interest in personal information protection has increased, various apps for personal information protection have emerged. These apps protect data in various formats, such as photos, videos, and documents containing personal information, using encryption and hide functions. These apps can have a positive effect on personal information protection, but in digital forensics, they act as anti-forensic because they can be difficult to analyze data during the investigation process. In this paper, finds out PIN, an access control function, through reverse engineering on Calculator - photo vault, one of the personal information protection apps, and files such as photos and documents to which encryption and hide were applied. In addition, the vulnerability to this app was analyzed by research decryption for database files where logs for encrypted and hide files are stored.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.627-628
• /
• 2022

There is no internationally accepted codified definition of digital trade because of the wide variety and scope of related industries and transactions(product + service + data) in general. Recently, innovative changes are taking place in digital trade due to the development of technologies such as IT due to the 4th industrial revolution, and advanced countries such as the US, EU, and Japan are including digital trade issues such as data movement liberalization in the negotiation agenda of the digital trade agreement. The issue with the liberalization of cross-border data movement is that freedom of data movement is necessary to vitalize digital trade, but it also increases the risk of information security and privacy violations. Looking at the directions of advanced countries, the US favors minimization of regulations, Europe favors regional single marketization, but passively opens up to the outside world, and China promotes independent markets through regulations. Therefore, measures to strengthen restrictions on cross-border data movement are an issue that has recently been implemented by each country or an international aggrement is scheduled to be reached soon, and Korea also needs a close response.

• International Journal of High-Rise Buildings
• /
• v.12 no.2
• /
• pp.179-193
• /
• 2023

It is undeniable that urban greenspace is the soul of a city. Conventional urban greenspace such as parks, community gardens, playgrounds etc. located within a city reduce the negative effects of pollution, play a major role in the survival of the urban ecosystem, and promote healthy lifestyles. Today, 55% of the world's population lives in urban areas, which is expected to increase to 68% by 2050. Projections show that urbanization and the gradual migration to urban areas combined with the fast growth of the world's population, could add another 2.5 billion people to urban areas by 2050 and almost 90% of this increase will take place in Asia(UN, 2018). As a result, many plots in the cities are and will continue to be occupied with buildings to provide residential support to the increased population. This will dangerously decrease urban greenspaces. Moreover, worldwide, food crisis, energy crisis, and social crisis is posing a great threat to the existence of mankind. Additionally, the COVID - 19 has introduced a new lifestyle where from work culture to community configuration has drastically transformed. In this scenario, residential buildings will have to serve more than just providing privacy and shelter. As urban greenspaces are being occupied by concrete residential buildings, these buildings will have to compensate for the percentage of urban green they are destroying and the issues they are imposing in the process. The goal of this thesis is to design, architecturally define and, categorize comprehensive 'sustainable Greenspace'(S.G.S) for the multi-family housing scenario. These will be different than the conventional green (veranda, rooftop green) we commonly see in residential buildings. An old, dilapidated apartment building will be the target of remodeling to fulfill the purpose of this thesis.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.5
• /
• pp.1310-1338
• /
• 2023

As Internet of Things (IoT) applications and devices rapidly grow, cyber-attacks on IoT networks/systems also have an increasing trend, thus increasing the threat to security and privacy. Botnet is one of the threats that dominate the attacks as it can easily compromise devices attached to an IoT networks/systems. The compromised devices will behave like the normal ones, thus it is difficult to recognize them. Several intelligent approaches have been introduced to improve the detection accuracy of this type of cyber-attack, including deep learning and machine learning techniques. Moreover, dimensionality reduction methods are implemented during the preprocessing stage. This research work proposes deep Autoencoder dimensionality reduction method combined with Artificial Neural Network (ANN) classifier as botnet detection system for IoT networks/systems. Experiments were carried out using 3- layer, 4-layer and 5-layer pre-processing data from the MedBIoT dataset. Experimental results show that using a 5-layer Autoencoder has better results, with details of accuracy value of 99.72%, Precision of 99.82%, Sensitivity of 99.82%, Specificity of 99.31%, and F1-score value of 99.82%. On the other hand, the 5-layer Autoencoder model succeeded in reducing the dataset size from 152 MB to 12.6 MB (equivalent to a reduction of 91.2%). Besides that, experiments on the N_BaIoT dataset also have a very high level of accuracy, up to 99.99%.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.7
• /
• pp.179-187
• /
• 2023

Consumer trust plays a crucial role in the development of the sharing economy. This study primarily focuses on the factors influencing consumer trust and examines the case of ofo, a former leader in China's bike-sharing industry. This paper analyzes the decline in consumer trust in ofo, which can be attributed to internal management issues and the near-bankruptcy situation. The "difficulty in refunds" issue faced by ofo since December 2018 has been growing continuously, and this study explores the factors influencing trust and distrust in this context. By considering product factors (quality), platform factors (payment security, privacy protection, reputation), and social factors (social norms, government regulation) as independent variables, the study analyzes the factors affecting consumer trust. The analysis results revealed that as consumers' distrust towards shared bikes increases, their switching intention also increases. The company's reputation and social norms were found to influence both trust and distrust, while government regulation was found to influence trust. The research findings provide insights relevant to sharing economy platforms and offer guidance for future studies.

• Journal of Information Technology Services
• /
• v.22 no.5
• /
• pp.1-16
• /
• 2023

This study aimed to provide fundamental insights into the digital customer experience by identifying its components and analyzing their importance and satisfaction levels among youths. To achieve this objective, the components of digital customer experience were identified through a review of prior research and consultation with experts. Subsequently, a survey was conducted with 200 youths in Seoul and Gyeonggi-do. The main findings of the study are as follows: First, The components of the digital customer experience consisted of 12 items grouped into three categories. Second, an analysis of the disparity between the importance and satisfaction levels of digital customer experience revealed statistically significant differences across all items. Third, By utilizing IPA (Importance-Performance Analysis), the digital customer experience was categorized into four quadrant, each with its own characteristics and recommendations for management: The first quadrant, the "current level maintenance area," encompassed items related to "entertainment" and "recommended service." This area is currently functioning well but necessitates continuous attention and management. The second quadrant, the "area to be supported first," included items such as "personalization," "security," "inducing participation," "privacy," and "individuality expression." Intensive management and improvements are imperative in this quadrant. The third quadrant, the "long-term improvement area," consisted of items like 'consistency,' 'information quality,' and 'convenience.' These items require focus on long-term enhancement efforts. The fourth quadrant, the "areas where efforts have already been invested," encompassed items like 'accessibility' and 'deliberation.' It appears that excessive investment has been made in these areas relative to their importance, calling for selective investments while considering the specific issues associated with each factor. These research findings serve as essential data for managing the digital customer experiences of youths.

• Journal of Industrial Convergence
• /
• v.21 no.12
• /
• pp.45-54
• /
• 2023

This study aims to examine trends so far and proactively seek future policy directions because the degree of implementation of hyper-connected society and smart technology at home and abroad cannot be overlooked at present in Korea. The method of the study focused on differentiating it from this study through literature research and comparison of major previous studies. As a result of the study, data security and maintenance, enhanced privacy of users and users, and related policy directions for entering a super-aged society were identified in the era of the 4th industrial revolution in Korea according to hyper-connected society and smart technology. Research limitations were difficulties in obtaining data and technical limitations in statistical quantification through trend analysis, although research analysis should be approached through quantitative and quantitative methods. It needs to be supplemented in future studies.

• Journal of Internet Computing and Services
• /
• v.25 no.2
• /
• pp.1-9
• /
• 2024

Although federated learning is designed to be safer than centralized methods in terms of security and privacy, it still has many vulnerabilities. An attacker performing an adversarial attack intentionally manipulates the deep learning model by injecting carefully crafted input data, that is, adversarial examples, into the client's training data to induce misclassification. A common defense strategy against this is so-called adversarial training, which involves preemptively learning the characteristics of adversarial examples into the model. Existing research assumes a scenario where all clients are under adversarial attack, but considering the number of clients in federated learning is very large, this is far from reality. In this paper, we experimentally examine aspects of adversarial training in a scenario where some of the clients are under attack. Through experiments, we found that there is a trade-off relationship in which the classification accuracy for normal samples decreases as the classification accuracy for adversarial examples increases. In order to effectively utilize this trade-off relationship, we present a method to perform adversarial training by adaptively selecting a loss function depending on whether the client is attacked.