During the past decade, cryptographers have identified several directions to meet future security demands like secure outsourced environments, robustness against non-traditional attacks, and post-quantum crypto systems. Despite many exciting advances, many of these instantiations are still far from practical, which reduces their potential impact. This project will provide critical thrusts towards reducing these restrictions in order to make these techniques more applicable in practice. This project introduces new research-intensive courses on homomorphic computation, defines appropriate research activities for training students, and has numerous outreach activities to underrepresented groups including middle school students.

This project focuses on improving two significant classes of lattice-based cryptography: (1) homomorphic computation, and (2) security against non-traditional attacks. These two classes provide powerful tools to secure data in both outsourced and portable environments, and additionally achieve post-quantum security. Particularly, this project starts with several recently developed techniques that connect homomorphic computation with (1) improved efficiency of identity-based encryption, (2) tighter/stronger security, and (3) non-traditional attacks. The objective is to refine these recent approaches and design practically efficient solutions. The outcomes would yield multiple efficient post-quantum crypto systems, contributing to further post-quantum standardizations, and providing secure methods for more advanced applications. Techniques developed in this project are expected to bring critical insights for making a leap towards the general goal, aiming at building truly practical solutions for all homomorphic computation and security against non-traditional attacks.

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.

National Science Foundation (NSF)
Division of Computer and Network Systems (CNS)
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Nina Amla
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Florida Atlantic University
Boca Raton
United States
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