WaveVerif: Acoustic Side-Channel based Verification of Robotic Workflows

WaveVerif: Acoustic Side-Channel based Verification of Robotic Workflows | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 3 December 2025 V1 Latest version Share on WaveVerif: Acoustic Side-Channel based Verification of Robotic Workflows Authors : Zeynep Yasemin Erdogan 0009-0003-8710-2762 [email protected] , Shishir Nagaraja , Chuadhry Mujeeb , and Ryan Shah Authors Info & Affiliations https://doi.org/10.22541/au.176479031.13872376/v1 158 views 102 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract In this paper, we present a framework that uses acoustic sidechannel analysis (ASCA) to monitor and verify whether a robot correctly executes its intended commands. We develop and evaluate a machine-learning-based workflow verification system that uses acoustic emissions generated by robotic movements. The system can determine whether real-time behavior is consistent with expected commands. The evaluation takes into account movement speed, direction, and microphone distance. The results show that individual robot movements can be validated with over 80% accuracy under baseline conditions using four different classifiers: Support Vector Machine (SVM), Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN). Additionally, workflows such as pick-and-place and packing could be identified with similarly high confidence. Our findings demonstrate that acoustic signals can support real-time, low-cost, passive verification in sensitive robotic environments without requiring hardware modifications. Supplementary Material File (manuscript7.pdf) Download 1.01 MB Information & Authors Information Version history V1 Version 1 03 December 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords acoustic side channel agriculture defence the proliferation of robotic systems across diverse domains-including industrial automation education healthcare logistics privacy robot security verification Authors Affiliations Zeynep Yasemin Erdogan 0009-0003-8710-2762 [email protected] View all articles by this author Shishir Nagaraja View all articles by this author Chuadhry Mujeeb View all articles by this author Ryan Shah View all articles by this author Metrics & Citations Metrics Article Usage 158 views 102 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Zeynep Yasemin Erdogan, Shishir Nagaraja, Chuadhry Mujeeb, et al. WaveVerif: Acoustic Side-Channel based Verification of Robotic Workflows. Authorea . 03 December 2025. DOI: https://doi.org/10.22541/au.176479031.13872376/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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