VeriORouting: Verification on intelligent routing outsourced to the cloud

Abstract

Current research on machine learning-based intelligent routing focuses on algorithm design and performance optimization. How to deploy it in practice remains a pressing issue. Existing deep learning-based intelligent routing algorithms suffer from a high computational cost, which is hard to be afforded by routers. Considering that the cloud can assist the routers with limited resources to handle complex computation, outsourcing deep learning-based intelligent routing computations to the cloud becomes a feasible solution to support intelligent routing. However, due to the untrustworthiness of the cloud, it is necessary for the routers to verify the truth of outsourced routing results. However, the literature has not yet explored this issue. In this paper, we proposed VeriORouting, a scheme to verify the correctness of outsourced deep learning-based intelligent routing results provided by the cloud. Facing a lazy cloud, VeriORouting allows routers to check the reliability of intelligent routing models by testing model accuracy, and to verify the routing results returned by the cloud without knowing the model by using verification functions generated with multilayer perceptron (MLP) and locality-sensitive hashing (LSH) in advance. We show the robustness of VeriORouting under two attacks raised by the cloud. We evaluate the performance of VeriORouting and compare it with a local intelligent routing scheme. The results show that VeriORouting outperforms the local scheme in terms of computational overhead and storage overhead, especially when the number of routers in the network increases. In terms of communication, VeriORouting reduces communication overhead between routers compared to the local scheme. In addition, we measure the verification performance of VeriORouting under a random attack. VeriORouting achieves a detection success rate of 73% with a false positive rate of 3%, and a detection success rate of 90% with a false positive rate of 25%.