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Recent work has made great progress in verifying the forwarding correctness of networks . However, these approaches cannot be used to verify networks containing middleboxes, such as caches and firewalls, whose forwarding behavior depends on previously observed traffic. We explore how to verify reachability properties for networks that include such mutable datapath elements. We want our verification results to hold not just for the given network, but also in the presence of failures. The main challenge lies in scaling the approach to handle large and complicated networks, We address by developing and leveraging the concept of slices, which allow network-wide verification to only require analyzing small portions of the network. We show that with slices the time required to verify an invariant on many production networks is independent of the size of the network itself.
Great progress has been made recently in verifying the correctness of router forwarding tables. However, these approaches do not work for networks containing middleboxes such as caches and firewalls whose forwarding behavior depends on previously obs
Verifying correctness of deep neural networks (DNNs) is challenging. We study a generic reachability problem for feed-forward DNNs which, for a given set of inputs to the network and a Lipschitz-continuous function over its outputs, computes the lowe
Deep neural networks are widely used for nonlinear function approximation with applications ranging from computer vision to control. Although these networks involve the composition of simple arithmetic operations, it can be very challenging to verify
Inspired by recent successes with parallel optimization techniques for solving Boolean satisfiability, we investigate a set of strategies and heuristics that aim to leverage parallel computing to improve the scalability of neural network verification
Deep convolutional neural networks have been widely employed as an effective technique to handle complex and practical problems. However, one of the fundamental problems is the lack of formal methods to analyze their behavior. To address this challen