Version 1
: Received: 28 December 2023 / Approved: 29 December 2023 / Online: 29 December 2023 (13:15:29 CET)
How to cite:
Nguyen, T. Accelerated CognitiveWarfare via the Dual Use of Large Language Models. Preprints2023, 2023122279. https://doi.org/10.20944/preprints202312.2279.v1
Nguyen, T. Accelerated CognitiveWarfare via the Dual Use of Large Language Models. Preprints 2023, 2023122279. https://doi.org/10.20944/preprints202312.2279.v1
Nguyen, T. Accelerated CognitiveWarfare via the Dual Use of Large Language Models. Preprints2023, 2023122279. https://doi.org/10.20944/preprints202312.2279.v1
APA Style
Nguyen, T. (2023). Accelerated CognitiveWarfare via the Dual Use of Large Language Models. Preprints. https://doi.org/10.20944/preprints202312.2279.v1
Chicago/Turabian Style
Nguyen, T. 2023 "Accelerated CognitiveWarfare via the Dual Use of Large Language Models" Preprints. https://doi.org/10.20944/preprints202312.2279.v1
Abstract
Cognitive Warfare (CogWar) is another form of warfare where the goal is to exploit cognition facets to disrupt, undermine, influence or modify human decisions. Famous examples include “Operation Gidlock” meddling with the US 2016 election, and CogWar campaigns assisting the annexation of Crimea. As Large Language Model(LLM)-based applications expand, reaching more users and their cognitive states, stealth Malicious Cognitive Behavioral Tactics (MCBT) can be embedded in trusted application sessions to systematically profile, then alter, each individual’s cognition over time. Successful MCBT can create more cases like Snowden, mass shootings, or January6. This short-form paper discusses a novel MCBT threat model, a novel kill chain, and an on-going prototype for demonstration.
Keywords
cognitive warfare; large language model; artificial intelligence; cognitive behavioral therapy; cybersecurity
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
