• Convergence Security Journal
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• v.15 no.5
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• pp.87-95
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• 2015

Recently, The cloud computing technology is emerging as an important issue in the world, and In technology and services, has attracted much attention. Cloud services have evolved from simple forms to complex forms(using multiple mobile devices and communication services(Kakao talk, Facebook, etc.). In particular, as the cloud is especially facilitated the collection of user information, it can now be analyzed with the user's taste and preference. And many of the benefits of the cloud became increasingly closely with our lives. However, the positive aspects of cloud computing unlike the includes several vulnerabilities. For this reason, the Hacking techniques according to the evolution of a variety of attacks and damages is expected. Therefore, this paper will be analyzed through case studies of attack and vulnerability to the privacy threats factors of the cloud computing services. and In the future, this is expected to be utilized as a basis for the Privacy security and Response.

• The Journal of Bigdata
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• v.5 no.2
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• pp.201-213
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• 2020

Despite empirical research that the response to human risk is significantly influenced affective factors, the role of affective factors has been unexplored in information privacy research. This study aims to explore the privacy behaviors of location-based service (LBS) users from an affective point of view. Specifically, the study explored the relationship between three types of privacy threats (collection, hacking, secondary use), two affects (worry, anger), and a coping behavior (continuous use intentions). The structured survey was conducted with 552 users. In order to analyze the effect of the combination of perception of particular privacy threats and particular affects on the intention of continuous use, association rules, one of the data mining techniques, was employed. As a result, there was a difference in the intention to use according to the combination of the perception of risk and affect responses, and the most significant influence on the intention is when the second use of personal information was combined with anger. This study has significant theoretical contribution in that it includes affective factors in the research of information privacy users, complementing the biases of existing cognition-oriented approaches and providing a comprehensive understanding of privacy response behavior.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.1-17
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• 2014

Social networking service (SNS) is a service that allows people to share information, manage relationships with others, and express themselves on the Internet. The number of SNS users have increased explosively with the growth of mobile devices such as smartphones. As the influence of SNS has grown extensively, potential threats to privacy have also become pervasive. The purpose of this study is to empirically examine the main factors that affect users' intentions to use security functions provided by their SNS. The main theories for this study include the rational choice theory and the theory of planned behavior. This study has identified the factors that affect intention to use security functions. In addition, security function awareness and information security awareness are found to be important antecedents for intention to use security functions. The results of this study implies that when SNS providers develop security policies, they should consider the ways to improve users information security awareness and security function awareness simultaneously.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.85-90
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• 2016

In this paper, the biometric data is transmitted in real time from the IoT environment is runoff, forgery, alteration, prevention of the factors that can be generated from a denial-of-service in advance, and the security strategy for the biometric data to protect the biometric data secure from security threats offer. The convenience of living in our surroundings to life with the development of ubiquitous computing and smart devices are available in real-time. And is also increasing interest in the IOT. IOT environment is giving the convenience of life. However, security threats to privacy also are exposed for 24 hours. This paper examines the security threats to biological data to be transmitted in real time from IOT environment. The technology for such security requirements and security technology according to the analysis of the threat. And with respect to the biometric data transmitted in real time on the IoT environment proposes a security strategy to ensure the stability against security threats and described with respect to its efficiency.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.272-279
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• 2009

A location information used in LBS provides convenience to the user, but service provider can be exploited depending on how much risk you have. Location information can be exploited to track the location of the personal privacy of individuals because of the misuse of location information may violate the user can import a lot of damage. In this paper, we classify the life cycle of location information as collection, use, delivery, storage and destroy and analyze the factors the privacy is violated. Furthermore, we analyze information security mechanism is classified as operation mechanism and policy/management mechanism and propose a security solutions of all phase in life cycle.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.41-62
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• 2016

In Internet of Things (IoT) era, more diverse types of information are collected and the environment of information usage, distribution, and processing is changing. Recently, there have been a growing number of cases involving breach and infringement of personal information in IoT services, for examples, including data breach incidents of Web cam service or drone and hacking cases of smart connected car or individual monitoring service. With the evolution of IoT, concerns on personal information protection has become a crucial issue and thus the risk analysis and management method of personal information should be systematically prepared. This study shows risk factors in IoT regarding possible breach of personal information and infringement of privacy. We propose "a risk analysis framework of protecting personal information in IoT environments" consisting of asset (personal information-type and sensitivity) subject to risk, threats of infringement (device, network, and server points), and social impact caused from the privacy incident. To verify this proposed framework, we conducted risk analysis of IoT services (smart communication device, connected car, smart healthcare, smart home, and smart infra) using this framework. Based on the analysis results, we identified the level of risk to personal information in IoT services and suggested measures to protect personal information and appropriately use it.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.76-90
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• 2024

Although artificial intelligence (AI) can be utilized in various domains such as smart city, healthcare, it is limited due to concerns about the exposure of personal and sensitive information. In response, the concept of distributed machine learning has emerged, wherein learning occurs locally before training a global model, mitigating the concentration of data on a central server. However, overall learning phase in a collaborative way among multiple participants poses threats to data privacy. In this paper, we systematically analyzes recent trends in privacy protection within the realm of distributed machine learning, considering factors such as the presence of a central server, distribution environment of the training datasets, and performance variations among participants. In particular, we focus on key distributed machine learning techniques, including horizontal federated learning, vertical federated learning, and swarm learning. We examine privacy protection mechanisms within these techniques and explores potential directions for future research.

• Journal of Information Technology Applications and Management
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• v.27 no.2
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• pp.1-21
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• 2020

The purpose of this study is to investigate the behavioral factors affecting the security attitude and intention to use biometrics password based on the protection motivation theory. This study also investigates security awareness training to understand trust, privacy, and security vulnerability regarding biometric authentication password. This empirical analysis reveals security awareness training boosts the protection motivational factors that affect on the behavior and intention of using biometric authentication passwords. This study also indicates that biometric authentication passwords can be used when the overall belief in a biometric system is present. After all, security awareness training enhances the belief of biometric passwords and increase the motivation to protect security threats. The study will provide insights into protecting security vulnerability with security awareness training.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.229-239
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• 2018

This paper analyzes the problems of existing CCTV and discusses cyber security problems of IP-CCTV in cloud computing environment. In order to reduce the risk of simply removing the risk associated with the provision of cloud services, the risk analysis and counter-measures need to be carried out effectively. Therefore, the STRIDE model as the Threat Risk Modeling is used to analyze the risk factors, and Analytic Hierarchy Process(AHP) is used to measure risk priorities based on the analyzed threats.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.41-54
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• 2020

In this paper, it will study various problems such as personal information infringement from when using various useful Apps in the Smartphone environment. It also researched the vulnerabilities Mobile Apps and the risks of personal information leakage when using Smartphone information to decrease threat and find solution. In the second chapter, it will check the existing Mobile App related Apps. In the third chapter, it will check the threats and major factors that caused by the leakage of personal information which related to the app. Then it will suggest solution and end with conclusion. This paper also looked at various problems that caused by illegal adverse effect from illegal personal information collection. Then it researched and made suggestion to make consideration on safety of personal information and privacy infringement that threat to personal information For safety of mobile banking, it proposed a safety method to separate and manage the code which has the core logic which required to run the App. For safety of direction App, when running the direction App, even if the information is collected, location information for unauthorized accessed will encrypt and store in DB, so that access to personal information is difficult. For delivery App environment, by using the national deliver order call center's representative phone to receive a telephone order then, the customer information is delivered to the branch office when it receive order and it will automatically delete information from the server when the delivery is completed by improving DB server of order. For the smart work app environment, the security solution operates automatically by separating and make independent private and work areas. Then it will suggest initialization for company's confidential business information and personal information to safe from danger even if loss.