Visible to the public Policy Design Based on Risk at Big Data Era: Case Study of Privacy Invasion in South Korea

TitlePolicy Design Based on Risk at Big Data Era: Case Study of Privacy Invasion in South Korea
Publication TypeConference Paper
Year of Publication2014
AuthorsHyejung Moon, Hyun Suk Cho, Seo Hwa Jeong, Jangho Park
Conference NameBig Data (BigData Congress), 2014 IEEE International Congress on
Date PublishedJune
KeywordsAccidents, Big Data, Big Data characteristics, Big Data laws, Big Data market, Big Data norms, Big Data technology, cultural types, culture type, data privacy, data spill accident case analysis, data variety, data velocity, data volume, egalitarianism group, fatalism group, hierarchy group, ICT policy, ICT risk based policy design, ICT risk management, ICT security, impact level, individual ICT risk, individualism group, intensive ICT risk, Moon, personal data, privacy, privacy invasion, probability level, risk acceptance, risk avoidance, risk management, risk mitigation, risk transfer, security, severe ICT risk, social science perspective, South Korea, strong ICT risk, technological risk
Abstract

This paper has conducted analyzing the accident case of data spill to study policy issues for ICT security from a social science perspective focusing on risk. The results from case analysis are as follows. First, ICT risk can be categorized 'severe, strong, intensive and individual' from the level of both probability and impact. Second, strategy of risk management can be designated 'avoid, transfer, mitigate, accept' by understanding their own culture type of relative group such as 'hierarchy, egalitarianism, fatalism and individualism'. Third, personal data has contained characteristics of big data such like 'volume, velocity, variety' for each risk situation. Therefore, government needs to establish a standing organization responsible for ICT risk policy and management in a new big data era. And the policy for ICT risk management needs to balance in considering 'technology, norms, laws, and market' in big data era.

DOI10.1109/BigData.Congress.2014.110
Citation Key6906854