@inproceedings{acarturk-etal-2026-neuro,
title = "A Neuro-Cyber Exploitation and Reconnaissance Taxonomy ({N}euro{CERT}) for Human-Centric Cybersecurity",
author = "Acarturk, Cengiz and
{\c{C}}a{\u{g}}layan, Melike and
Caglayan, Ece and
Wilkosz, Anna",
editor = "Mitkov, Ruslan and
Mu{\~n}oz, Rafael and
Lloret, Elena and
Ranasinghe, Tharindu and
Estevanell-Valladares, Ernesto L. and
Lamsiyah, Salima and
Montoyo, Andr{\'e}s and
Ezzini, Saad",
booktitle = "Proceedings of the Second International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security",
month = jun,
year = "2026",
address = "Alicante, Spain",
publisher = "Department of Languages and Information Systems, University of Alicante",
url = "https://aclanthology.org/2026.nlpaics-1.15/",
pages = "143--155",
abstract = "Neuroscientists and cyber threat actors operate on a ``black box'' paradigm, relying on both the passive measurement of physical exhaust to infer hidden internal states, and the active injection of targeted stimuli to disrupt or manipulate those systems. This paper introduces the Neuro-Cyber Exploitation and Reconnaissance Taxonomy (NeuroCERT), a theoretical framework that maps cybersecurity side-channel attacks and active vectors to psychophysiological measurement and neurostimulation techniques. It proposes that AI can serve as a translational layer to parse noisy biological data into actionable metrics or automate closed-loop attacks, suggesting the potential of novel threat vectors in human-centric cybersecurity."
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%0 Conference Proceedings
%T A Neuro-Cyber Exploitation and Reconnaissance Taxonomy (NeuroCERT) for Human-Centric Cybersecurity
%A Acarturk, Cengiz
%A Çağlayan, Melike
%A Caglayan, Ece
%A Wilkosz, Anna
%Y Mitkov, Ruslan
%Y Muñoz, Rafael
%Y Lloret, Elena
%Y Ranasinghe, Tharindu
%Y Estevanell-Valladares, Ernesto L.
%Y Lamsiyah, Salima
%Y Montoyo, Andrés
%Y Ezzini, Saad
%S Proceedings of the Second International Conference on Natural Language Processing and Artificial Intelligence for Cyber Security
%D 2026
%8 June
%I Department of Languages and Information Systems, University of Alicante
%C Alicante, Spain
%F acarturk-etal-2026-neuro
%X Neuroscientists and cyber threat actors operate on a “black box” paradigm, relying on both the passive measurement of physical exhaust to infer hidden internal states, and the active injection of targeted stimuli to disrupt or manipulate those systems. This paper introduces the Neuro-Cyber Exploitation and Reconnaissance Taxonomy (NeuroCERT), a theoretical framework that maps cybersecurity side-channel attacks and active vectors to psychophysiological measurement and neurostimulation techniques. It proposes that AI can serve as a translational layer to parse noisy biological data into actionable metrics or automate closed-loop attacks, suggesting the potential of novel threat vectors in human-centric cybersecurity.
%U https://aclanthology.org/2026.nlpaics-1.15/
%P 143-155
Markdown (Informal)
[A Neuro-Cyber Exploitation and Reconnaissance Taxonomy (NeuroCERT) for Human-Centric Cybersecurity](https://aclanthology.org/2026.nlpaics-1.15/) (Acarturk et al., NLPAICS 2026)
ACL