The Detection of Malicious Modifications in the FPGA

Field Programmable Gate Arrays (FPGAs) are being widely used in a variety of embedded applications. Due to their programmable feature, FPGAs are the perfect choice for various hardware-based systems. In many of the competing types of FPGAs, the dominant types are Static Random-Access Memory (SRAM) based which can be reprogrammed at any stage of execution of a job. SRAM-based FPGAs are volatile and need an external memory to store configuration bitstream that is vulnerable to attacks. In the development as well as deployment stages, the threat of malicious modifications or inserting Hardware Trojans (HTs) into the bitstream is always present. FPGA’s bitstream can be infiltrated or corrupted in a non-invasive manner that may cause fatal consequences. Therefore, a framework is proposed that uses Xilinx Design Language (XDL) or Native Circuit Description (NCD) files that can be extracted from the infected bitstream of FPGA. Xilinx Command Line tools are used to get complete information on hardware primitives, resource utilization, timing constraints, and power summaries from XDL/NCD files in textual form. Further, Natural Language Processing (NLP) has been employed to extract the syntactic features from the descriptive artifact to find the malicious modifications/HTs. The proposed framework also identifies the types of the detected HTs and provides a good understanding to study the behavior of trojans. For logic implementation and testing, Xilinx ISE 14.7 along with PlanAhead^TM and FPGA Editor design tools are used. The experimental results show that the proposed framework can be successfully used for the detection of malicious modifications/HTs with optimal accuracy.