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Jahoon Koo received the B.S. degrees in computer science and engineering from the University of Sejong, Seoul, South Korea, in 2017. He is currently pursuing the Ph.D. degree with Department of Computer and Information Security, Sejong University, Seoul.
The use of big data in various fields has led to a rapid increase in a wide variety of data resources, and various data analysis technologies such as standardized data mining and statistical analysis techniques are accelerating the continuous expansion of the big data market. An important characteristic of big data is that data from various sources have life cycles from collection to destruction, and new information can be derived through analysis, combination, and utilization. However, each phase of the life cycle presents data security and reliability issues, making the protection of personally identifiable information a critical objective. In particular, user tendencies can be analyzed using various big data analytics, and this information leads to the invasion of personal privacy. Therefore, this paper identifies threats and security issues that occur in the life cycle of big data by confirming the current standards developed by international standardization organizations and analyzing related studies. In addition, we divide a big data life cycle into five phases (i.e., collection, storage, analytics, utilization, and destruction), and define the security taxonomy of the big data life cycle based on the identified threats and security issues.
Jahoon Koo; Giluk Kang; Young-Gab Kim. Security and Privacy in Big Data Life Cycle: A Survey and Open Challenges. Sustainability 2020, 12, 10571 .
AMA StyleJahoon Koo, Giluk Kang, Young-Gab Kim. Security and Privacy in Big Data Life Cycle: A Survey and Open Challenges. Sustainability. 2020; 12 (24):10571.
Chicago/Turabian StyleJahoon Koo; Giluk Kang; Young-Gab Kim. 2020. "Security and Privacy in Big Data Life Cycle: A Survey and Open Challenges." Sustainability 12, no. 24: 10571.
With the development of the fourth industrial technology, such as the Internet of Things (IoT) and cloud computing, developed countries including the U.S. are investigating the efficiency of national defense, the public sector and national innovation, and constructing the infrastructure for cloud computing environments through related policies. The Republic of Korea is enacting the related legislation and considering the fourth industrial technology in various fields. Particularly, it is considering the adaptation of the cloud to the command and control system in the national defense sector; hence, related research and pilot projects are being conducted. However, if the existing information system is converted to a cloud computing system by introducing IoT devices, existing security requirements cannot solve problems related to the security vulnerabilities of cloud computing. Therefore, to build a cloud-based secure command and control system, it is necessary to derive additional cloud computing-related security requirements that are lacking in the existing security requirements, and to build a secure national defense command and control system architecture based upon it. In this paper, we derive security requirements for a cloud-based command control system, propose a security architecture designed based thereupon, and implement a security architecture with an open-stack-based cloud platform, “OpenStack”.
Jahoon Koo; Se-Ra Oh; Sang Hoon Lee; Young-Gab Kim. Security Architecture for Cloud-Based Command and Control System in IoT Environment. Applied Sciences 2020, 10, 1035 .
AMA StyleJahoon Koo, Se-Ra Oh, Sang Hoon Lee, Young-Gab Kim. Security Architecture for Cloud-Based Command and Control System in IoT Environment. Applied Sciences. 2020; 10 (3):1035.
Chicago/Turabian StyleJahoon Koo; Se-Ra Oh; Sang Hoon Lee; Young-Gab Kim. 2020. "Security Architecture for Cloud-Based Command and Control System in IoT Environment." Applied Sciences 10, no. 3: 1035.
With the continuous improvement of Internet of Things (IoT) technologies, various IoT platforms are under development. However, each IoT platform is developed based on its own device identification system. That is, it is challenging to identify each sensor device between heterogeneous IoT platforms owing to the resource request format (e.g., device identifier) varying between platforms. Moreover, despite the considerable research focusing on resource interoperability between heterogeneous IoT platforms, little attention is given to sensor device identification systems in diverse IoT platforms. In order to overcome this problem, the current work proposes an IoT device name system (DNS) architecture based on the comparative analysis of heterogeneous IoT platforms (i.e., oneM2M, GS1 'Oliot', IBM 'Watson IoT', OCF 'IoTivity', FIWARE). The proposed IoT DNS analyzes and translates the identification system of the device and resource request format. In this process, resource requests between heterogeneous IoT platforms can be reconfigured appropriately for the resources and services requested by the user, and as a result, users can use heterogeneous IoT services. Furthermore, in order to illustrate the aim of the proposed architecture, the proposed IoT DNS is implemented and tested on a microcomputer. The experimental results show that a oneM2M-based device successfully performs a resource request to a Watson IoT and FIWARE sensor devices.
Jahoon Koo; Se-Ra Oh; Young-Gab Kim. Device Identification Interoperability in Heterogeneous IoT Platforms. Sensors 2019, 19, 1433 .
AMA StyleJahoon Koo, Se-Ra Oh, Young-Gab Kim. Device Identification Interoperability in Heterogeneous IoT Platforms. Sensors. 2019; 19 (6):1433.
Chicago/Turabian StyleJahoon Koo; Se-Ra Oh; Young-Gab Kim. 2019. "Device Identification Interoperability in Heterogeneous IoT Platforms." Sensors 19, no. 6: 1433.