Simpler protocols for privacy-preserving disease susceptibility testing
George Danezis, Emiliano De Cristofaro
Abstract
George Danezis, Emiliano De Cristofaro
Abstract
This short paper presents a preliminary description of two new protocols \nfor privacy-preserving disease susceptibility testing, following \nthe model proposed by Ayday et al. in [5]. We show that an \nalternative encoding of the patient’s SNPs can simplify private computations, \nand make patient-side computation on a trusted smartcard \ndevice extremely efficient. To support larger tests, we propose a second \nprotocol variant based on secret sharing that is also simpler than \nthe original proposal, and relies on more efficient primitives.
OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This short paper presents a preliminary description of two new protocols \nfor privacy-preserving disease susceptibility testing, following \nthe model proposed by Ayday et al. in [5]. We show that an \nalternative encoding of the patient’s SNPs can simplify private computations, \nand make patient-side computation on a trusted smartcard \ndevice extremely efficient. To support larger tests, we propose a second \nprotocol variant based on secret sharing that is also simpler than \nthe original proposal, and relies on more efficient primitives.
Key concepts: Computer science, Secure multi-party computation, Protocol (science), Computation, Encoding (memory), Secret sharing, Secure two-party computation, Theoretical computer science