DANA Universal Dataflow Analysis for Gate-Level Netlist Reverse Engineering

Reverse engineering of integrated circuits, i.e., understanding the internals of Integrated Circuits (ICs), is required for many benign and malicious applications. Examples of the former are detection of patent infringements, hardware Trojans or Intellectual Property (IP)-theft, as well as interface recovery and defect analysis, while malicious applications include IP-theft and finding insertion points for hardware Trojans. However, regardless of the application, the reverse engineer initially starts with a large unstructured netlist, forming an incomprehensible sea of gates.This work presents DANA, a generic, technology-agnostic, and fully automated dataflow analysis methodology for flattened gate-level netlists. By analyzing the flow of data between individual Flip Flops (FFs), DANA recovers high-level registers. The key idea behind DANA is to combine independent metrics based on structural and control information with a powerful automated architecture. Notably, DANA works without any thresholds, scenario-dependent parameters, or other “magic” values that the user must choose. We evaluate DANA on nine modern hardware designs, ranging from cryptographic co-processors, over CPUs, to the OpenTitan, a stateof- the-art System-on-Chip (SoC), which is maintained by the lowRISC initiative with supporting industry partners like Google and Western Digital. Our results demonstrate almost perfect recovery of registers for all case studies, regardless whether they were synthesized as FPGA or ASIC netlists. Furthermore, we explore two applications for dataflow analysis: we show that the raw output of DANA often already allows to identify crucial components and high-level architecture features and also demonstrate its applicability for detecting simple hardware Trojans.Hence, DANA can be applied universally as the first step when investigating unknown netlists and provides major guidance for human analysts by structuring and condensing the otherwise incomprehensible sea of gates. Our implementation of DANA and all synthesized netlists are available as open source on GitHub.

Dataflow analysis of vehicle safety computers regarding high-speed maglev transportation based on data priorities

To analyze the dataflow of vehicle safety computers regarding high-speed maglev transportation, it is considerable to add data priorities to the dataflow model of vehicle safety computers to improve the accuracy. With regard to vehicle safety computers, we choose VSC1 as our research object. First, we give a brief summary for the interface relationships of VSC1. Next, we analyze the data priorities of VSC1 in detail. After that, we present the dataflow model of VSC1 with priorities. Finally, we make a brief conclusion. The structure of the abstract of an article is strictly arranged and should encompass the following points: Background: Dataflow model of Vehicle Safety Computers regarding high-speed maglev transportation. Aim: To analyze the dataflow of vehicle safety computers with data priorities. Methods: interface analysis, data priority analysis and dataflow chart. Results: The dataflow model of VSC1 with data priorities is presented. Conclusion: Adding data priorities to the dataflow model of vehicle safety computers to improve the accuracy is fulfilled. The recommended number of words in the abstract is 500.