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 <strong>Bioluminescent bio-cyber Interfacing </strong>(BBI) in the I<strong>nternet of Bio Nano Things </strong>(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: <strong>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,</strong> and <strong>Reverse forward rate constant.</strong> The data set is divided into training and testing data for simplified analysis, and application.