Risk Data Analysis Based Anomaly Detection of Ship Information System

Bowen Xing, Yafeng Jiang, Yuqing Liu and Shouqi Cao
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Bowen Xing: College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
Yafeng Jiang: College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
Yuqing Liu: College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China
Shouqi Cao: College of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, China

Energies, 2018, vol. 11, issue 12, 1-16

Abstract: Due to the vulnerability and high risk of the ship environment, the Ship Information System (SIS) should provide 24 hours of uninterrupted protection against network attacks. Therefore, the corresponding intrusion detection mechanism is proposed for this situation. Based on the collaborative control structure of SIS, this paper proposes an anomaly detection pattern based on risk data analysis. An intrusion detection method based on the critical state is proposed, and the corresponding analysis algorithm is given. In the Industrial State Modeling Language (ISML), risk data are determined by all relevant data, even in different subsystems. In order to verify the attack recognition effect of the intrusion detection mechanism, this paper takes the course/roll collaborative control task as an example to carry out simulation verification of the effectiveness of the intrusion detection mechanism.

Keywords: cybersecurity; intrusion detection; risk data analysis; signal attack; ship information system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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