An effective security measures for nuclear power plant using big data analysis approach

Abstract

Among the many hacking attempts carried out against information systems for the past few years, cyber-attacks that could lead to a national-level threat included attacks against nuclear facilities particularly nuclear power stations. Two of the typical examples are the Stuxnet attack against an Iranian nuclear facility and the cyber threat against Korea Hydro and Nuclear Power in December 2015. The former has proven that a direct cyber-attack can actually stop the nuclear power station, and the latter has shown that people can be terrorized with only a (cyber) threat. After these incidents, security measures for cyber-attacks against industrial control systems have been strengthened. The nuclear power stations also changed their passive concept of executing security measures by operating the plant with an isolated network to prepare for the cyber-attacks carried out by malicious codes. The difference between the two concepts is that the latter has been formulated based on the possibility that most of the control systems can be targets of cyber-attacks. Threats against control systems are gradually increasing nowadays, so the relevant industries are implementing some measures to identify/develop safe and reliable digital equipment and identify risks to establish effective cyber security plans. Thus, this paper proposes a security measure based on the classification of past attack incidents against control systems and the big data analysis technique that processes the data generated from individual security equipment. The security of control systems is expected to be strengthened through such effective measure.