The University of Maine’s recent acquisition of $400,000 as part of a $1.2 million collaboration funded by the National Science Foundation (NSF) marks a pivotal moment for cybersecurity and semiconductor design. This project, known as “KIPPER: A Scalable Learning-Guided Hardware IP Protection Platform,” brings new hope to an industry beleaguered by confidentiality breaches and intellectual property (IP) theft. Led by assistant professor Prabuddha Chakraborty, the initiative is slated to run until August 31, 2028, and aims to establish a robust framework for hardware security. The continuous rise in the complexity and global distribution of semiconductor designs has only exacerbated the risks, posing significant threats to both industry and national security.
KIPPER’s cornerstone lies in its innovative use of artificial intelligence techniques, like reinforcement learning and explainable algorithms, to bolster hardware security. By automating the detection of security vulnerabilities, KIPPER aims to mimic the analytical approaches employed by security researchers. This automation allows for the simulation of how experts identify attack vectors and root causes, thereby streamlining the entire process. One of the primary goals is to implement design transformations that defend against security attacks without imposing significant additional hardware overhead. By closely emulating human strategies for identifying and mitigating these vulnerabilities, KIPPER endeavors to create a scalable and adaptable defense mechanism capable of evolving with emerging threats.
Advancing Cybersecurity Education and Collaboration
The University of Maine’s recent receipt of $400,000, part of a larger $1.2 million grant from the National Science Foundation (NSF), marks a significant advancement in cybersecurity and semiconductor design. This effort, named “KIPPER: A Scalable Learning-Guided Hardware IP Protection Platform,” offers new solutions to an industry plagued by confidentiality breaches and IP theft. Spearheaded by assistant professor Prabuddha Chakraborty, the project will run until August 31, 2028, and aims to build a solid foundation for hardware security. The increasing intricacy and worldwide distribution of semiconductor designs have heightened risks, creating serious threats to both industry and national security.
The innovation of KIPPER lies in its use of artificial intelligence strategies, including reinforcement learning and explainable algorithms, designed to strengthen hardware security. Automating the detection of security vulnerabilities, KIPPER simulates the methods of security experts, making the process more efficient. A key objective is to introduce design changes that counter security attacks without adding substantial hardware overhead. By closely mimicking expert strategies for identifying and addressing vulnerabilities, KIPPER aims to create a scalable and adaptable defense mechanism that can evolve with new threats.
