  The problem of spoofing attacks is increasingly relevant as digital systems
are becoming more ubiquitous. Thus the detection of such attacks and the
localisation of attackers have been objects of recent study. After an attack
has been detected, various algorithms have been proposed in order to localise
the attacker. In this work we propose a new adaptive pruning algorithm inspired
by the tropical and geometrical analysis of the traditional Viterbi pruning
algorithm to solve the localisation problem. In particular, the proposed
algorithm tries to localise the attacker by adapting the leniency parameter
based on estimates about the state of the solution space. These estimates stem
from the enclosed volume and the entropy of the solution space, as they were
introduced in our previous works.
