Vulnerabilities threaten the security of information systems. It is crucial to detect and patch vulnerabilities before attacks happen. However, existing vulnerability detection methods suffer from long-term dependency, out vocabulary, bias towards global features or local features, coarse granularity. This paper proposes an automatic framework in source code based on a hybrid neural network. Fi...

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a netwo...

The contribution of this paper is to present the network modeling methodology to make it possible to test the survivability of computer network. As the structure and behavior of network becomes complicated and unpredictable, it becomes difficult to test the survivability of computer network. The modeling and simulation is a widely used approach to Predict the behavior of system or set of system...

Neural networks provide candidate substrates for the spread of proteinopathies causing neurodegeneration, and emerging data suggest that macroscopic signatures of network disintegration differentiate diseases. However, how do protein abnormalities produce network signatures? The answer may lie with 'molecular nexopathies': specific, coherent conjunctions of pathogenic protein and intrinsic netw...