Part 2: Homomorphic Encryption for Beginners
We discuss a practical application of homomorphic encryption to privacy-preserving signal processing, particularly focusing on the Fourier transform.
Patricia Thaine
Part 1: Homomorphic Encryption for Beginners
We cover the basics of homomorphic encryption, followed by a brief overview of open source HE libraries and a tutorial on how to use one of those libraries (namely, PALISADE).
Why is Privacy-Preserving NLP Important?
A number of people ask us why we should bother creating NLP tools that preserve privacy. Apparently not everyone spends hours thinking about data breaches and privacy infringements.
A Brief Overview of Privacy-Preserving Technology Methods
A very brief overview of privacy-preserving technologies follows for anyone who’s interested in starting out in this area. I cover symmetric encryption, asymmetric encryption, homomorphic encryption, differential privacy, and secure multi-party computation.