Cognitive Cyber Crimes in the Era of Artificial Intelligence

1Intersection of AI, Neuroscience, and Cryptography in Cybercrime Investigations

Priya Matta¹*, Dhiren P. Bhagat², Priyanka Rastogi³, Anisha⁴ and Atika Gupta⁵

¹Department of Computer Applications, Tula’s Institute, Dehradun, Uttarakhand, India

²Sarvajanik College of Engineering and Technology, Surat, India

³Dept of Computer Science and Engineering, School of Engineering, Manav Rachna International Institute of Research & Studies, Faridabad, India

⁴Manav Rachna International Institute of Research and Studies, Faridabad, India

⁵Graphic Era Hill University, Dehradun, India

Abstract

This study proposes Neuro-CryptoNet-AI, a cross-domain threat detection model that leverages neuroscience-driven electroencephalogram signal processing, deep learning behavior modeling, and advanced cryptographic schemes to secure cybercrime investigations. Electroencephalogram data from the DEAP dataset are analyzed using alpha, beta, gamma, theta, and delta wave energy distributions. Behavioral anomalies are identified via the transformer–convolutional neural network model trained on the UNSW-NB15 dataset using 49 features, including flow duration, source/destination IP, payload bytes, and protocol type. AES-256 (Advanced Encryption Standard) encryption secures data streams and forensic logs. Our results demonstrate 98.76% accuracy, 97.85% precision, 98.34% F1 score, and 1.2% false-positive rate, outperforming conventional single-domain methods. This fusion of cognitive neuroscience, artificial intelligence, ...