Successful attack on permutation-parity-machine-based neural cryptography

TL;DR

This paper introduces a probabilistic attack on permutation-parity-machine-based neural cryptography, demonstrating that the protocol is vulnerable as the attack can compromise synchronization.

Contribution

The paper presents a novel Monte Carlo-based attack strategy that effectively breaches the security of the permutation-parity-machine protocol.

Findings

The attack does not require faster synchronization than legitimate parties.

The method successfully extracts key information during the attack.

The protocol's security is compromised under the proposed attack.

Abstract

An algorithm is presented which implements a probabilistic attack on the key-exchange protocol based on permutation parity machines. Instead of imitating the synchronization of the communicating partners, the strategy consists of a Monte Carlo method to sample the space of possible weights during inner rounds and an analytic approach to convey the extracted information from one outer round to the next one. The results show that the protocol under attack fails to synchronize faster than an eavesdropper using this algorithm.