Hybrid learning of expert heuristic, machine and deep learning for ranking automotive level applications

Disclosed herein are methods and systems for training and using a neural network to assess vulnerabilities of software packages, the method and system comprising training the neural network using a plurality of training samples to calculate a probability that one or more of a plurality of vulnerabilities are present in each of a plurality of software packages and outputting the trained neural network, the plurality of training samples each associate one of the plurality of software packages with one of the plurality of vulnerabilities identified by one of the plurality of validators. The verifier may include expert knowledge, heuristic, rule-based models, and machine learning and deep learning models. The trained neural network may then be applied to a feed based on vulnerabilities identified in one or more previously unseen software packages by a plurality of validators to calculate a probability that one or more of the vulnerabilities are present in the one or more previously unseen software packages. 本文公开用