Cognitive Warfare Indicators and Warnings Identification Framework
| Autoři | |
|---|---|
| Rok publikování | 2025 |
| Druh | Článek ve sborníku |
| Konference | Meaningful Human Control in Information Warfare |
| Fakulta / Pracoviště MU | |
| Citace | |
| www | https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-HFM-377/MP-HFM-377-09.pdf |
| Doi | http://dx.doi.org/10.14339/STO-MP-HFM-377-09-PDF |
| Popis | Cognitive Warfare (CogWar) is an emerging concept, yet already hotly contested across NATO nations and partner states. CogWar is enabled primarily by advancements in technology, artificial intelligence (AI), as well as new knowledge developed in the social sciences. The speed with which such operations can reach target audiences requires fast identification of these attacks to allow for an adequate response. Without using cutting-edge AI algorithms, ensemble learning methods, and large-language models (LLMs), indicators and warnings (I&W) solutions cannot compete with CogWar operations. A potential issue with AI-enabled solutions for I&W is a lack of transparency and fine-tuning. The SAS-185 team, examining Indicators and Warnings for Cognitive Warfare in Cyberspace, is now developing a framework to identify quantifiable (and/or LLM-enabled) indicators of Cognitive Attacks and CogWar operations for use in future software solutions. Such a framework can keep a system transparent thanks to the known inputs. Furthermore, while LLMs are still unable to create new knowledge, human researchers and practitioners will hopefully be able to use this framework to anticipate future uses of CogWar and update relevant I&W software pre-emptively. SAS-185 uses an existing morphological analysis method to construct CogWar-relevant scenarios, which can in turn, be used to identify potential indicators. A considerable body of literature in intelligence studies deals with I&W and early warning systems that will be utilized to develop a coherent framework using scenarios as a basis for indicators for Cognitive Warfare. The proposed framework is a critical step in feeding and updating a potential AI-enabled solution to identify adversarial CogWar. |