Genetic program based data mining to reverse engineer digital logic

James F. Smith III; Thanh Vu H. Nguyen

doi:10.1117/12.664952

18 April 2006 Genetic program based data mining to reverse engineer digital logic

James F. Smith III, Thanh Vu H. Nguyen

Proceedings Volume 6241, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006; 624103 (2006) https://doi.org/10.1117/12.664952
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

A data mining based procedure for automated reverse engineering and defect discovery has been developed. The data mining algorithm for reverse engineering uses a genetic program (GP) as a data mining function. A genetic program is an algorithm based on the theory of evolution that automatically evolves populations of computer programs or mathematical expressions, eventually selecting one that is optimal in the sense it maximizes a measure of effectiveness, referred to as a fitness function. The system to be reverse engineered is typically a sensor. Design documents for the sensor are not available and conditions prevent the sensor from being taken apart. The sensor is used to create a database of input signals and output measurements. Rules about the likely design properties of the sensor are collected from experts. The rules are used to create a fitness function for the genetic program. Genetic program based data mining is then conducted. This procedure incorporates not only the experts' rules into the fitness function, but also the information in the database. The information extracted through this process is the internal design specifications of the sensor. Uncertainty related to the input-output database and the expert based rule set can significantly alter the reverse engineering results. Significant experimental and theoretical results related to GP based data mining for reverse engineering will be provided. Methods of quantifying uncertainty and its effects will be presented. Finally methods for reducing the uncertainty will be examined.

Citation Download Citation

James F. Smith III and Thanh Vu H. Nguyen "Genetic program based data mining to reverse engineer digital logic", Proc. SPIE 6241, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006, 624103 (18 April 2006); https://doi.org/10.1117/12.664952

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