Abstract

The significant rise in the cost of manufacturing nanoscale integrated circuits (ICs) has led the majority of IC design companies to outsource the fabrication of their products to other companies, often located in different countries. The multinational nature of the hardware supply chain has led to a host of security threats, including IP piracy, IC overproduction, and Trojan insertion. To combat these, researchers have proposed logic locking techniques to protect the intellectual properties of the design and increase the difficulty of malicious modification of its functionality. However, the adoption of logic locking approaches has been rather slow due to the lack of integration with the IC production process and the lack of efficacy of existing algorithms. This work automates the logic locking process by developing software using Python that performs the locking on a gate-level netlist, which can be integrated with the existing digital synthesis tools. Analysis of the latest logic locking algorithms has demonstrated that the SFLL-HD algorithm is one of the most secure and versatile when trading-off levels of protection against different types of attacks and was thus selected for implementation. The presented tool can also be expanded to incorporate the latest locking mechanisms to keep up with the fast-paced development in this field. The paper also presents a case study to demonstrate the functionality of the tool and how it could be used to explore the design space and compare different locking solutions.

Highlights

  • The production of nanoscale integrated circuits (ICs) has become a multinational distributed process; a trend driven by the increase in the level of outsourcing to reduce costs

  • Logic locking algorithms have been developed in response to emerging threats against the hardware supply chain, in particular, these techniques can be used to mitigate the risks of IP piracy through reverse engineering, IC overproduction, and Trojan insertion

  • Since the stripped functionality logic locking—Hamming distance (SFLL-HD) algorithm performs the logic locking on an input cone, the tool first selects the input cone that will be locked by its size

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Summary

Introduction

Several experiments have been conducted on the tool when it was used to lock various benchmark circuits. The conducted experiments demonstrated the correctness of the tool against the algorithm specification, evaluation of the level of protection it provides for varying parameters k and h, evaluation of performance and computational complexity for varying parameters k and h, and the number of nodes in the input netlist n, as well as comparison of area, power, and timing overheads, each being assessed for varying parameters k and h

A Review of Logic Locking Algorithms and Related Attacks
Principles of Random Logic Locking
Sensitization Attacks on Random Logic Locking
Principles of Fault Analysis-Based Logic Locking
Principles of Strong Logic Locking
SAT Attacks on Random Logic Locking
Principles of Cyclic Logic Locking
Principles of Anti-SAT
Principles of SARLock
Removal Attacks on SAT Resilient Techniques
2.10. Inter-Module SAT Techniques
2.11. Principles of Tenacious and Traceless Logic Locking
2.12. Principles of Stripped Functionality Logic Locking—Hamming Distance
2.13. Analysis of Algorithms
2.14. Analysis of Strategies
Internal Structure of the Tool
Graphical User Interface
Graph Representation
Technology
Netlist Parsing
Selection of an Input Cone to Lock
Key Generation
Functionality Strip
Functionality Restore
3.10. Gate Size Reduction
3.11. Technology Mapping of the Gates
3.12. Writing out the Locked Netlist
3.13. Integration of the Tool with the IC Design Process
Computational Complexity and Performance Evaluation
Functional Verification
Security Evaluation
Comparison of Overheads
Findings
Conclusions
Full Text
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