DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

Understand

Deep learning (DL) defines a new data-driven programming paradigm that constructs the internal system logic of a crafted neuron network through a set of training data.

• We have seen wide adoption of DL in many safety-critical scenarios.
• However, a plethora of studies have shown that the state-of-the-art DL systems suffer from various vulnerabilities which can lead to severe consequences when applied to real-world applications.
• Currently, the testing adequacy of a DL system is usually measured by the accuracy of test data.