This article presents eight neural cyberattacks affecting spontaneous neural
activity, inspired by well-known cyberattacks from the computer science domain:
Neural Flooding, Neural Jamming, Neural Scanning, Neural Selective Forwarding,
Neural Spoofing, Neural Sybil, Neural Sinkhole and Neural Nonce. These
cyberattacks are based on the exploitation of vulnerabilities existing in the
new generation of Brain-Computer Interfaces. After presenting their formal
definitions, the cyberattacks have been implemented over a neuronal simulation.
To evaluate the impact of each cyberattack, they have been implemented in a
Convolutional Neural Network (CNN) simulating a portion of a mouse’s visual
cortex. This implementation is based on existing literature indicating the
similarities that CNNs have with neuronal structures from the visual cortex.
Some conclusions are also provided, indicating that Neural Nonce and Neural
Jamming are the most impactful cyberattacks for short-term effects, while
Neural Scanning and Neural Nonce are the most damaging for long-term effects.

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Author Of this post: <a href="">Sergio L&#xf3;pez Bernal</a>, <a href="">Alberto Huertas Celdr&#xe1;n</a>, <a href="">Gregorio Mart&#xed;nez P&#xe9;rez</a>

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