Can you still see me? Identifying robot operations over end-to-end encrypted channels

Tools

Shah, Ryan and Ahmed, Chuadhry Mujeeb and Nagaraja, Shishir; (2022) Can you still see me? Identifying robot operations over end-to-end encrypted channels. In: WiSec 2022 - Proceedings of the 15th ACM Conference on Security and Privacy in Wireless and Mobile Networks. WiSec 2022 - Proceedings of the 15th ACM Conference on Security and Privacy in Wireless and Mobile Networks . ACM, New York, pp. 298-300. ISBN 9781450392167 (https://doi.org/10.1145/3507657.3529659)

[thumbnail of Shah-etal-ACM-WiSec-2022-Can-you-still-see-me-identifying-robot-operations]
Preview
 Text. Filename: Shah_etal_ACM_WiSec_2022_Can_you_still_see_me_identifying_robot_operations.pdf
Final Published Version
License: Creative Commons Attribution-NonCommercial 4.0 logo
Download (577kB)| Preview

Abstract

Connected robots play a key role in automating industrial workflows. Robots can expose sensitive operational information to remote adversaries. Despite the use of end-to-end encryption, a passive adversary could fingerprint and reconstruct the entire workflows being carried out and developing a detailed understanding of how facilities operate. In this paper, we investigate whether a remote passive attacker can accurately fingerprint robot movements and reconstruct operational workflows. Using a neural network-based traffic analysis approach, we found that attackers can predict TLS-encrypted robot movements with around ~60% accuracy, increasing to near perfect accuracy in realistic settings. Ultimately, simply adopting best cybersecurity practices is not enough to stop even weak (passive) adversaries.

ORCID iDs

Shah, Ryan ORCID logoORCID: https://orcid.org/0000-0003-1348-8423, Ahmed, Chuadhry Mujeeb ORCID logoORCID: https://orcid.org/0000-0003-3644-0465 and Nagaraja, Shishir;
CORE (COnnecting REpositories)