scholarly journals A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks

2017 ◽  
Author(s):  
Baoping Cai ◽  
Min Xie ◽  
Yonghong Liu ◽  
Yiliu Liu ◽  
Renjie Ji ◽  
...  
Keyword(s):  
Bayesian Networks ◽  
Critical Infrastructure ◽  
Dynamic Bayesian Networks ◽  
Assessment Approach ◽  
Infrastructure Resilience ◽  
Resilience Assessment

scholarly journals A Dynamic-Bayesian-Networks-Based Resilience Assessment Approach of Structure Systems: Subsea Oil and Gas Pipelines as A Case Study

2020 ◽  
Vol 34 (5) ◽  
pp. 597-607
Author(s):  
Bao-ping Cai ◽  
Yan-ping Zhang ◽  
Xiao-bing Yuan ◽  
Chun-tan Gao ◽  
Yong-hong Liu ◽  
...  
Keyword(s):  
Bayesian Networks ◽  
Oil And Gas ◽  
Dynamic Bayesian Networks ◽  
Gas Pipelines ◽  
Oil And Gas Pipelines ◽  
Assessment Approach ◽  
Resilience Assessment

Advancing Cyber Resilience Analysis with Performance-Based Metrics from Infrastructure Assessments

2014 ◽  
pp. 2033-2055 ◽  
Author(s):  
Eric D. Vugrin ◽  
Jennifer Turgeon
Keyword(s):  
Assessment Methods ◽  
Infrastructure Systems ◽  
Quantitative Metrics ◽  
Performance Based Assessment ◽  
Assessment Approach ◽  
Hypothetical System ◽  
Qualitative Component ◽  
Infrastructure Resilience ◽  
Resilience Assessment

Cyber resilience is becoming increasingly recognized as a critical component of comprehensive cybersecurity practices. Current cyber resilience assessment approaches are primarily qualitative methods, making validation of their resilience analyses and enhancement recommendations difficult, if not impossible. The evolution of infrastructure resilience assessment methods has paralleled that of their cyber counterparts. However, the development of performance-based assessment methods has shown promise for overcoming the validation challenge for infrastructure systems. This article describes a hybrid infrastructure resilience assessment approach that combines both qualitative analysis techniques with performance-based metrics. The qualitative component enables identification of system features that limit resilience, and the quantitative metrics can be used to evaluate and confirm the effectiveness of proposed mitigation options. The authors propose adaptation of this methodology for cyber resilience analysis. A case study is presented to demonstrate how the approach could be applied to a hypothetical system.

Advancing Cyber Resilience Analysis with Performance-Based Metrics from Infrastructure Assessments

2013 ◽  
Vol 4 (1) ◽  
pp. 75-96 ◽  
Author(s):  
Eric D. Vugrin ◽  
Jennifer Turgeon
Keyword(s):  
Assessment Methods ◽  
Analysis Techniques ◽  
Quantitative Metrics ◽  
Performance Based Assessment ◽  
Assessment Approach ◽  
Hypothetical System ◽  
Qualitative Component ◽  
Infrastructure Resilience ◽  
Resilience Assessment

Cyber resilience is becoming increasingly recognized as a critical component of comprehensive cybersecurity practices. Current cyber resilience assessment approaches are primarily qualitative methods, making validation of their resilience analyses and enhancement recommendations difficult, if not impossible. The evolution of infrastructure resilience assessment methods has paralleled that of their cyber counterparts. However, the development of performance-based assessment methods has shown promise for overcoming the validation challenge for infrastructure systems. This paper describes a hybrid infrastructure resilience assessment approach that combines both qualitative analysis techniques with performance-based metrics. The qualitative component enables identification of system features that limit resilience, and the quantitative metrics can be used to evaluate and confirm the effectiveness of proposed mitigation options. The authors propose adaptation of this methodology for cyber resilience analysis. A case study is presented to demonstrate how the approach could be applied to a hypothetical system.

Multiple small objects tracking based on dynamic Bayesian networks with spatial prior

Optik ◽  
2014 ◽  
Vol 125 (10) ◽  
pp. 2243-2247 ◽  
Author(s):  
Rui Yao ◽  
Yanning Zhang ◽  
Yong Zhou ◽  
Shixiong Xia
Keyword(s):  
Bayesian Networks ◽  
Dynamic Bayesian Networks ◽  
Objects Tracking

Multimodal Sensor Fusion for Indoor Occupancy Determination

2015 ◽  
Vol 764-765 ◽  
pp. 1319-1323
Author(s):  
Rong Shue Hsiao ◽  
Ding Bing Lin ◽  
Hsin Piao Lin ◽  
Jin Wang Zhou
Keyword(s):  
Bayesian Networks ◽  
Sensor Fusion ◽  
Dynamic Bayesian Networks ◽  
Sensor Nodes ◽  
Detection Accuracy ◽  
Multisensor Fusion ◽  
Fusion Algorithm ◽  
Improve Energy Efficiency ◽  
Occupancy Detection ◽  
Automation Systems

Pyroelectric infrared (PIR) sensors can detect the presence of human without the need to carry any device, which are widely used for human presence detection in home/office automation systems in order to improve energy efficiency. However, PIR detection is based on the movement of occupants. For occupancy detection, PIR sensors have inherent limitation when occupants remain relatively still. Multisensor fusion technology takes advantage of redundant, complementary, or more timely information from different modal sensors, which is considered an effective approach for solving the uncertainty and unreliability problems of sensing. In this paper, we proposed a simple multimodal sensor fusion algorithm, which is very suitable to be manipulated by the sensor nodes of wireless sensor networks. The inference algorithm was evaluated for the sensor detection accuracy and compared to the multisensor fusion using dynamic Bayesian networks. The experimental results showed that a detection accuracy of 97% in room occupancy can be achieved. The accuracy of occupancy detection is very close to that of the dynamic Bayesian networks.

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