Hybrid Deep Learning Techniques for Securing Bioluminescent Interfaces in Internet of Bio Nano Things

The data-set presents normal and anomalous values of twelve traffic parameters, generated by Bioluminescent bio-cyber Interfacing (BBI) in the Internet of Bio Nano Things (IoBNT) based systems. The traffic parameters included in the data-set represent bio-electric and electro-bio transduction unit operation of BBI incorporating normal, as well as abnormal data to train and test machine/deep learning classifiers in discriminating attack scenarios. The parameters considered include the following: Cumulative concentration of released molecules, Elimination rate, Michaelis-Menten constant, Kinetic constant, Forward rate constant, Catalytic reaction constant, Ligand-receptor binding constant, Concentration of ATP, Concentration of information molecules, Release rate Reverse kinetic constant, and Reverse forward rate constant. The data set is divided into training and testing data for simplified analysis, and application.