Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4970284 | Pattern Recognition Letters | 2017 | 8 Pages |
Abstract
Although it is agreed that the Volgenant-Jonker (VJ) algorithm provides a fast way to approximate graph edit distance (GED), until now nobody has reported how the VJ algorithm can be tuned for this task. To this end, we revisit VJ and propose a series of refinements that improve both the speed and memory footprint without sacrificing accuracy in the GED approximation. We quantify the effectiveness of these optimisations by measuring distortion between control-flow graphs: a problem that arises in malware matching. We also document an unexpected behavioural property of VJ in which the time required to find shortest paths to unassigned vertices decreases as graph size increases, and explain how this phenomenon relates to the birthday paradox.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
William Jones, Aziem Chawdhary, Andy King,