Worcester Polytechnic Institute

Homomorphic Encryption


You can access our publications from here.


You can access our software and GPU libraries, and applications from github using the link.




Supported by NSF-CNS

  • Towards Practical Fully Homomorphic Encryption
    Supported by NSF-CNS Award #1319130.
    PIs: Berk Sunar, William J. MartinFully homomorphic encryption (FHE) allows an untrusted party to efficiently compute any compact function directly on ciphertexts. When made available over an untrusted cloud server, data is submitted and returned in encrypted form, and the execution remains secure against malicious users. Early FHE proposals had rather disappointing efficiencies. Recently new FHE schemes based on the difficulty of the learning with errors (LWE) problem emerged with orders of magnitude improvement over earlier constructions. This project addresses a variety of problems in engineering, computer science and mathematics all centered around the goal of bringing LWE-based homomorphic encryption techniques closer to practice.The project team explores three research components. The first research component investigates algorithmic optimizations to speed up LWE-based schemes, and to develop optimized software implementations on CPUs and graphics processing units. Specifically, the investigators apply optimization techniques including changing the representation of the operands, batching, and precomputation. The team also aims to build a LWE-FHE based homomorphic instruction set. In another research component the project team develops application specific custom hardware to overcome inefficiencies of software platforms. Finally, we investigate the customization of parameters to match the needs of select lightweight cryptographic primitives.


  • Homomorphic Encryption for Cloud Privacy
    Supported by NSF-CNS Award #1117590.
    PIs: Berk Sunar, William J. Martin
    Students: Yin Hu, Yarkin Doroz, Wei DaiHomomorphic encryption is a new cryptographic technology that allows the evaluation of a restricted set of operations directly on the ciphertext. If made efficient, homomorphic encryption may turn untrusted servers, such as in cloud computing, into computing platforms that ensure the privacy of the users.The goal of this project is to bring homomorphic encryption schemes closer to deployment. Currently we are seeking solutions in two ways:

    • We explore special hardware features such as the Intel SIMD (XMM) extensions, and the advanced vector processing capabilities of graphic processing units (GPUs) for more efficient fully homomorphic encryption,
    • We investigate new partially homomorphic schemes to achieve specialized operations faster and with reduced message expansion.