Threats and Mitigation Strategies for Electroencephalography-Based Person Authentication.

Area of Science:

• Biometrics and Cybersecurity
• Neuroscience and Signal Processing

Background:

• Electroencephalography (EEG) offers unique biometric authentication due to its resistance to imitation and postmortem acquisition.
• Traditional biometrics like fingerprints and irises are susceptible to degradation and illicit use.
• Recent advancements highlight potential vulnerabilities in EEG-based authentication.

Purpose of the Study:

• To investigate emerging risks in EEG-based person authentication.
• To review current knowledge and identify challenges in EEG signal authentication.
• To propose solutions for mitigating identified security threats.

Main Methods:

• Comprehensive literature review of EEG signal research over the past decade.
• Analysis of recent advancements and challenges in EEG biometrics.
• Development of updated liveness detection approaches.

Main Results:

• EEG signals from deceased individuals were successfully captured, posing a significant threat to current authentication systems.
• Existing EEG authentication literature lacks robust "liveness detection" implementation.
• Novel challenges include falsified EEG signals and the use of postmortem EEG data.

Conclusions:

• EEG-based authentication requires enhanced liveness detection to address new threats.
• The study introduces updated approaches to counter falsified and postmortem EEG signals.
• Findings aim to stimulate further research in secure EEG biometric systems.