The broader impact and commercial potential of this PFI project is to pave the road for commercialization of a new generation of security solutions through leveraging recent advances in low power non-silicon based memories, advanced error recovery techniques and artificial intelligence. This new methodology offers a radical shift in the field of cybersecurity through departing from pure-software based cryptographic methods toward a hybrid solution of using fabrication variability of electronic devices and advanced error correction methods. This project is a collaboration between academia and industry to enhance current security solutions used in e-commerce, banking, smart cities, supply chains, smart health, machine to machine communications and the emerging Internet of Things. In addition to the scientific impact of opening up new research opportunities for scholars (faculty, graduate and undergraduate students), R&D, and production line workforce in semiconductor and security industry, this project has a great socioeconomic impact by restoring people's trust on using advanced technology and internet based service. Making the system robust to security attacks will save the country millions of dollars noting that more than $11 million dollars is spent directly to combat cybercrime in the US with an annual raise of 22%.
The proposed project offers a proof-of-concept security module that uses fabrication variability of embedded memories in electronic devices to secure web-based communication protocols against hacking attacks. In contrast to the current cryptographic methods, where the keys are store in conventional memories, no security keys will be stored in the proposed security module; therefore it will be highly protected against cloning attempts to provide full security in the case of physical hijacking. Further, recently developed ultra-low power memories will be used to make the developed module secure to side channel attacks, as an additional key feature of this device. Using a novel error correction mechanism by integrating ternary state logic, artificial intelligence and recent advances in modern coding theory, a long-lasting problem of key generation mismatch is resolved by making the key generation failure rate infinitesimal.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
