@inproceedings{257dd8c8c5c542169cda7596d8a9e56d,
title = "Toward parametric security analysis of machine learning based cyber forensic biometric systems",
abstract = "Machine learning algorithms are widely used in cyber forensic biometric systems to analyze a subject's truthfulness in an interrogation. An analytical method (rather than experimental) to evaluate the security strength of these systems under potential cyber attacks is essential. In this paper, we formalize a theoretical method for analyzing the immunity of a machine learning based cyber forensic system against evidence tampering attack. We apply our theory on brain signal based forensic systems that use neural networks to classify responses from a subject. Attack simulation is run to validate our theoretical analysis results.",
keywords = "Cyber forensic, Electroencephalogram, Machine learning, Security strength",
author = "Koosha Sadeghi and Ayan Banerjee and Javad Sohankar and Sandeep Gupta",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016 ; Conference date: 18-12-2016 Through 20-12-2016",
year = "2017",
month = jan,
day = "31",
doi = "10.1109/ICMLA.2016.168",
language = "English (US)",
series = "Proceedings - 2016 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "626--631",
booktitle = "Proceedings - 2016 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016",
}