Paper 2022/1462

RTL-FSMx: Fast and Accurate Finite State Machine Extraction at the RTL for Security Applications

Rasheed Kibria, University of Florida
M. Sazadur Rahman, University of Florida
Farimah Farahmandi, University of Florida
Mark Tehranipoor, University of Florida

At the early stage of the design process, many security vulnerability assessment solutions require fast and precise extraction of the finite state machines (FSMs) present in the register-transfer level (RTL) description of the design. FSMs should be accurately extracted for watermark insertion, fault injection assessment of control paths in a system-on-chip (SoC), information leakage assessment, control-flow reverse engineering in RTL abstraction, logic obfuscation, etc. However, it is quite unfortunate that, as of today, existing state-of-the-art synthesis tools cannot provide accurate and reliable extraction of all FSMs from the provided high-level RTL code. Precise identification of all FSM state registers and the pure combinational state transition logic described in the RTL code with numerous registers and other combinational logic makes it quite challenging to develop such a solution. In this paper, we propose a framework named RTL-FSMx to extract FSMs from high-level RTL codes written in Verilog HDL. RTL-FSMx utilizes node-based analysis on the abstract syntax tree (AST) representation of the RTL code to isolate FSM state registers from other registers. RTL-FSMx automatically extracts state transition graphs (STGs) for each of the detected FSM state registers and additional information of the extracted FSMs. Experimental results on a large number of benchmark circuits demonstrate that RTL-FSMx accurately recovers all control FSMs from RTL codes with various complexity and size within just a few seconds.

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Publication info
Register Transfer Level FSM Extraction HDL Code Analysis Security Assessment FSM Automata Theory
Contact author(s)
rasheed kibria @ ufl edu
mohammad rahman @ ufl edu
farimah @ ece ufl edu
tehranipoor @ ece ufl edu
2022-12-29: withdrawn
2022-10-25: received
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