Neuro-Cybersecurity: Exploiting Neural Signal Patterns for Biometric Hacking and Defense

As brain-computer interfaces (BCIs) and systems that use brain signals for identification become more popular, security concerns are also increasing. This paper discusses some new ways attackers might try to trick these systems, such as using AI to create fake brain signals, or using light and sound to control someone’s brain activity. I also look at how computer models can create fake EEG data that looks real. To stop these attacks, I suggest using special encryption for EEG signals, checking brain signal patterns for anything unusual, and asking users to do mental tasks during login to make sure it’s really them. By combining ideas from neuroscience, cybersecurity, and artificial intelligence, this paper presents a new way to protect systems that rely on brain signals.