In this paper, we present the concept of k-distance signature which is a general case of many existing signatures. By exploiting k-distance signature, we propose an algorithm for input differentiation (AID) which is very powerful to distinguish inputs of Boolean functions. Moreover, based on AID, we propose a heuristic method to detect G-symmetry of Boolean functions and a Boolean matching algorithm. The experimental results show that our methods are not only effective but also very efficient for Boolean matching and G-symmetry detection.
['Kuo-Hua Wang']
Exploiting K-Distance Signature for Boolean Matching and G-Symmetry Detection