State Reconstruction Under Malicious Sensor Attacks

State Reconstruction Under Malicious Sensor Attacks | 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 Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed.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. 10 April 2026 V1 Latest version Share on State Reconstruction Under Malicious Sensor Attacks Author : Wei Liu 0000-0001-7116-510X [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.177584985.51524936/v1 120 views 57 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper considers the state reconstruction problem for discrete-time cyber-physical systems when some of the sensors can be arbitrarily corrupted by malicious attacks where the attacked sensors belong to an unknown set. We first prove that the state is s-error correctable if the system under consideration is s-sparse observable where s denotes the maximum number of attacked sensors. Then, two state reconstruction methods are presented where the first method is based on searching elements with the same value in a set and the second method is developed in terms of searching element satisfying a given condition. In addition, after establishing and analyzing the conditions that the proposed state reconstruction methods are not effective, we address that it is very hard to prevent the state reconstruction when either state reconstruction method proposed in this paper is used. The correctness and effectiveness of the proposed methods are examined via an example of four-dimensional dynamic systems and a real-world example of three-inertia systems. Supplementary Material File (manuscript.pdf) Download 185.83 KB Information & Authors Information Version history V1 Version 1 10 April 2026 Copyright This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License Keywords cyber-physical systems discrete-time error correction sensor attacks state reconstruction Authors Affiliations Wei Liu 0000-0001-7116-510X [email protected] View all articles by this author Metrics & Citations Metrics Article Usage 120 views 57 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Wei Liu. State Reconstruction Under Malicious Sensor Attacks. Authorea . 10 April 2026. DOI: https://doi.org/10.22541/au.177584985.51524936/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.177584985.51524936/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe4d34d1f7c58d3',t:'MTc3OTIxMTc4Mw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();