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A Hybrid Approach to Detecting Security Defects in Programs
By: Lian Yu; Qianxiang Wang; Jianchu Fan; Yue Yi; Jun Zhou;
2009 / IEEE / 978-1-4244-5913-1
This item was taken from the IEEE Conference ' A Hybrid Approach to Detecting Security Defects in Programs ' Static analysis works well at checking defects that clearly map to source code constructs. Model checking can find defects of deadlocks and routing loops that are not easily detected by static analysis, but faces the problem of state explosion. This paper proposes a hybrid approach to detecting security defects in programs. Fuzzy Inference System is used to infer selection among the two detection approaches. A cluster algorithm is developed to divide a large system into several clusters in order to apply model checking. Ontology based static analysis employs logic reasoning to intelligently detect the defects. We also put forwards strategies to improve performance of the static analysis. At last, we perform experiments to evaluate the accuracy and performance of the hybrid approach.
Ontology Based Static Analysis
Fuzzy Inference System
Ontologies (artificial Intelligence)
Security Of Data