Hardware and Information Security Primitives Based on 2D Materials and Devices

Hardware security is a major concern for the entire semiconductor ecosystem that accounts for billions of dollars in annual losses. Similarly, information security is a critical need for the rapidly proliferating edge devices that continuously collect and communicate a massive volume of data. While silicon-based complementary metal-oxide-semiconductor technology offers security solutions, these are largely inadequate, inefficient, and often inconclusive, as well as resource intensive in time, energy, and cost, leading to tremendous room for innovation in this field. Furthermore, silicon-based security primitives have shown vulnerability to machine learning (ML) attacks. In recent years, 2D materials such as graphene and transition metal dichalcogenides have been intensely explored to mitigate these security challenges. In this review, 2D-materials-based hardware security solutions such as camouflaging, true random number generation, watermarking, anticounterfeiting, physically unclonable functions, and logic locking of integrated circuits (ICs) are summarized with accompanying discussion on their reliability and resilience to ML attacks. In addition, the role of native defects in 2D materials in developing high entropy hardware security primitives is also examined. Finally, the existing challenges for 2D materials, which must be overcome for large-scale deployment of 2D ICs to meet the security needs of the semiconductor industry, are discussed.

Automated summary

Hardware security is a major concern in the semiconductor industry, with billions of dollars in losses annually. Information security is also critically important for edge devices, which collect and transmit large amounts of data. Current silicon-based solutions are inadequate, inefficient, and vulnerable to machine learning attacks, leading to a need for innovation. 2D materials, such as graphene, have shown potential in addressing these security challenges through techniques like camouflaging and true random number generation.