Deepfakes and Large Language Models: Risks, Defenses, and the Future of Generative AI

Deepfakes and Large Language Models: Risks, Defenses, and the Future of Generative AI | 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 Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed.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. 4 February 2026 V1 Latest version Share on Deepfakes and Large Language Models: Risks, Defenses, and the Future of Generative AI Authors : Alakananda Mitra 0000-0002-8796-4819 [email protected] , Saraju P Mohanty , and Elias Kougianos Authors Info & Affiliations https://doi.org/10.22541/au.177023018.89520346/v1 297 views 116 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Generative Artificial Intelligence (GenAI) is rapidly changing how digital content is created and consumed. Two widely used GenAI technologies are deepfakes and large language models (LLMs). Deepfakes can generate realistic images, videos, audio, and text that imitate real people, while LLMs provide robust language understanding, reasoning, and multimodal coordination. When combined, these technologies significantly increase the realism, speed, and accessibility of synthetic media, raising concerns about misinformation, impersonation, and loss of digital trust. At the same time, the same reasoning capabilities that enable deepfake generation can also be leveraged for detection, verification, and mitigation. This article explores how LLMs strengthen deepfake generation by enabling realistic scripts, coordinated multimodal outputs, and scalable automation. Furthermore, it highlights how LLMs can also be used to fight deepfakes through semantic analysis, cross-modal verification, and provenance-based safeguards. By examining this dual role in an agentic AI setting, the article emphasizes why LLMs are central to both the deepfake problem and its defense. Supplementary Material File (techrxiv_deepfake_llm (1).pdf) Download 1.30 MB Information & Authors Information Version history V1 Version 1 04 February 2026 Copyright This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License Keywords ai security deepfakes digital trust generative artificial intelligence large language models misinformation multimodal ai synthetic media Authors Affiliations Alakananda Mitra 0000-0002-8796-4819 [email protected] Nebraska Water Center, University of Nebraska-Lincoln View all articles by this author Saraju P Mohanty Department of Computer Science and Engineering, University of North Texas View all articles by this author Elias Kougianos Department of Electrical Engineering, University of North Texas View all articles by this author Metrics & Citations Metrics Article Usage 297 views 116 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Alakananda Mitra, Saraju P Mohanty, Elias Kougianos. Deepfakes and Large Language Models: Risks, Defenses, and the Future of Generative AI. Authorea . 04 February 2026. DOI: https://doi.org/10.22541/au.177023018.89520346/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.177023018.89520346/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:'9fe446fb0bf509d6',t:'MTc3OTIwNjAzNQ=='};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())}}}})();