A Bayesian-network approach for assessing the probability of success of physical security attacks to offshore Oil&Gas facilities

被引:13
作者
Iaiani, Matteo [1 ]
Tugnoli, Alessandro [1 ]
Cozzani, Valerio [1 ]
Reniers, Genserik [2 ]
Yang, Ming [2 ]
机构
[1] Alma Mater Studiorum Univ Bologna, Dept Civil Chem Environm & Mat Engn, LISES, Via Terracini n 28, I-40131 Bologna, Italy
[2] Delft Univ Technol, Fac Technol Policy & Management, Safety & Secur Sci Sect, Delft, Netherlands
关键词
Security; Security attack; OffshoreOil&Gas industry; Bayesian network; Security risk; Quantitative assessment; RISK-ASSESSMENT; SAFETY; VULNERABILITY;
D O I
10.1016/j.oceaneng.2023.114010
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Offshore Oil&Gas facilities are attractive targets of intentional malicious attacks (security attacks) that may trigger cascading events (e.g., the release and dispersion of hazardous material and/or energy, fires, explosions) with consequences on people, environment, and assets. The severity of these consequences is potentially similar to those arising from major accident scenarios originated by conventional safety-related causes. Current practice in managing the risk of security attacks mostly relies on qualitative or semi-quantitative procedures developed over the years in the offshore Oil&Gas industry. In the present study, a systematic quantitative procedure is developed, based on a Bayesian Network (BN) approach, for calculating the probability of success of physical security attacks, taking into account both preventive and mitigative security intervention strategies. The pro-cedure addresses the specific framework of the offshore Oil&Gas industry. A case study concerning an offshore fixed Oil&Gas platform allowed us to demonstrate the quality of the results that can be achieved and their potential towards the improvement of the security of the installations considered.
引用
收藏
页数:13
相关论文
共 60 条
[1]  
American Petroleum Institute (API), 2013, 780 API RP
[2]   How the definition of security risk can be made compatible with safety definitions [J].
Amundrud, Oystein ;
Aven, Terje ;
Flage, Roger .
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY, 2017, 231 (03) :286-294
[3]   Integrating Real-Time Monitoring Data in Risk Assessment for Crane Related Offshore Operations [J].
Ancione, Giuseppa ;
Paltrinieri, Nicola ;
Milazzo, Maria Francesca .
JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2020, 8 (07) :1-28
[4]  
[Anonymous], 1988, Probabilistic Reasoning in Intelligent Systems:Networks of Plausible Inference
[5]  
[Anonymous], 2004, Security for Worldwide Offshore Oil and Natural Gas Operations: API Recommended Practice 70I, VFirst
[6]  
[Anonymous], HOME CMEMS
[7]  
[Anonymous], 2010, Security for Offshore Oil and Natural Gas Operations: API Recommended Practice 70, VFirst
[8]   Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network [J].
Argenti, Francesca ;
Landucci, Gabriele ;
Reniers, Genserik ;
Cozzani, Valerio .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2018, 169 :515-530
[9]   A study on the performance assessment of anti-terrorism physical protection systems in chemical plants [J].
Argenti, Francesca ;
Landucci, Gabriele ;
Cozzani, Valerio ;
Reniers, Genserik .
SAFETY SCIENCE, 2017, 94 :181-196
[10]   The assessment of the attractiveness of process facilities to terrorist attacks [J].
Argenti, Francesca ;
Landucci, Gabriele ;
Spadoni, Gigliola ;
Cozzani, Valerio .
SAFETY SCIENCE, 2015, 77 :169-181