A review on machine learning based counterfeit integrated circuit detection

Abstract

Counterfeit electronics parts have changed today’s electronic market all over the world. A large number of Integrated Circuit (IC) designers, manufacturers and suppliers present in the market have led to an increase in the counterfeiting. Still, there are no proper standards are formulated to regulate the spread of counterfeit electronics. Large number of research solutions is provided to identify them. Still, several forms of counterfeit ICs are not yet detected up to an extent. One of the promising solutions developed in recent research is the use of machine learning algorithms in the detection of counterfeit ICs. A state-of-the-art survey on the electrical and physical inspection methods to detect the counterfeit ICs using various machine learning approaches with other algorithms are presented and compared. Future directions for the identification of counterfeit ICs are also provided to increase the lifetime of the circuit.