LGDCMLDec 31, 2021

Improved Algorithm for the Network Alignment Problem with Application to Binary Diffing

arXiv:2112.15336v12 citations
Originality Incremental advance
AI Analysis

This work addresses network alignment for applications like binary diffing, offering incremental improvements in speed and convergence.

The paper tackles the Network Alignment problem by introducing a novel algorithm that speeds up message updates and ensures convergence, outperforming state-of-the-art solvers. It applies this method to Binary Diffing, achieving better assignments than reference differs in most instances.

In this paper, we present a novel algorithm to address the Network Alignment problem. It is inspired from a previous message passing framework of Bayati et al. [2] and includes several modifications designed to significantly speed up the message updates as well as to enforce their convergence. Experiments show that our proposed model outperforms other state-of-the-art solvers. Finally, we propose an application of our method in order to address the Binary Diffing problem. We show that our solution provides better assignment than the reference differs in almost all submitted instances and outline the importance of leveraging the graphical structure of binary programs.

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