SaTC: CORE: Small: SLIQ: Securing Large-Scale Noisy-Intermediate Scale Quantum Computing

Application-specific parametric quantum circuits designed to solve societal and science problems using powerful quantum computers contain assets and embed Intellectual Property (IP). Next generation quantum computers will face two new security issues: (i) evolution of multi-tenant computing (MTC) where multiple programs will share the hardware. The unwanted coupling between qubits can leak information and allow fault/Trojan injection; (ii) dependence on untrusted third-party compilers which can steal IP and tamper the circuit. This project will identify the vulnerabilities and threat vectors and develop a suite of defenses at the circuit and system level to secure future large scale quantum computing.

The intellectual merits of this project are rooted at, (i) identification of various assets in quantum circuits, algorithms and hardware; (ii) identification of vulnerabilities in MTC environment such as, crosstalk, qubit allocation, scheduling and hardware splitting policies and untrusted compiler such as, embedding of IP, crosstalk, sensitivity of circuit quality to qubit allocation and gates; (iii) identification of security and privacy threats from MTC environment e.g., crosstalk-based fault/Trojan injection and data leakage and untrusted compiler such as, reverse engineering and tampering; (iv) development of circuit and system-level defenses such as, machine learning-based screening, obfuscation and split compilation.

By addressing security, this project will remove a major roadblock towards applicability of quantum computers in security/privacy sensitive sectors. It will lead to widespread adoption of quantum computers in healthcare, energy and defense sectors and therefore, make a positive economic impact. This project will establish collaboration with industry and experts from computer science and cryptography communities to exchange ideas and will contribute directly to the Quantum Initiative Act and AI initiative Act. It will train new generation of workforce to solve problems using quantum computing. The tools and methodologies from this project can be plugged into existing commercial optimization tools.

All publicly released data will be posted at PI's academic website http://personal.psu.edu/~szg212 and the code developed in this project will be released in github (https://github.com/szg212) throughout the project and preserved without restrictions after the award ends. The conference and journal papers produced in this project will be archived in publisher's website (e.g., ACM, IEEE). The presentations, tutorials and images will be hosted in PI's academic website throughout the project and preserved without restrictions after the award ends. The video files of demonstrations and presentations will be uploaded in YouTube and will be preserved without restrictions after the project.

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.