Fault Tree Analysis: Identifying Maximum Probability Minimal Cut Sets with MaxSAT

Autor: Martín Barrère, Chris Hankin
Přispěvatelé: Horizon2020
Jazyk: angličtina
Rok vydání: 2020
Předmět:
MaxSAT
FOS: Computer and information sciences
Computer Science - Logic in Computer Science
J.2
Computer Science - Cryptography and Security
Discrete Mathematics (cs.DM)
B.6.3
Computer science
Computer Science - Artificial Intelligence
C.4
B.8
0102 computer and information sciences
02 engineering and technology
Systems and Control (eess.SY)
G.2.2
Computer Science::Computational Complexity
01 natural sciences
Electrical Engineering and Systems Science - Systems and Control
J.6
J.7
F.4.1
D.4.5
D.4.6
Computer Science - Networking and Internet Architecture
0202 electrical engineering
electronic engineering
information engineering
FOS: Electrical engineering
electronic engineering
information engineering
Risk assessment
Fault tree analysis
Networking and Internet Architecture (cs.NI)
Cyber-physical systems
Cyber-physical system
Logic in Computer Science (cs.LO)
Dependability evaluation
Open source
Artificial Intelligence (cs.AI)
010201 computation theory & mathematics
68M15
05C05
94C15
68R10
90B25
93B20
90C27
90C35
68U07
03B05
Maximum satisfiability problem
020201 artificial intelligence & image processing
Minimal cut sets
Algorithm
Cryptography and Security (cs.CR)
Computer Science - Discrete Mathematics
Zdroj: 2020 50th Annual IEEE-IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S)
DSN (Supplements)
50th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2020)
Popis: In this paper, we present a novel MaxSAT-based technique to compute Maximum Probability Minimal Cut Sets (MPMCSs) in fault trees. We model the MPMCS problem as a Weighted Partial MaxSAT problem and solve it using a parallel SAT-solving architecture. The results obtained with our open source tool indicate that the approach is effective and efficient.
Accepted for publication at the 50th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2020), Fast Abstracts Track, 2020
Databáze: OpenAIRE
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