Author:
Johannes Schneider
Affiliation:
ABB Corporate Research, Switzerland
Keyword(s):
Client-server Computation, Secure Cloud Computing, Secure Multi-party Computation, Privacy Preserving Data Mining.
Related
Ontology
Subjects/Areas/Topics:
Data and Application Security and Privacy
;
Information and Systems Security
;
Privacy
;
Privacy Enhancing Technologies
;
Security and Privacy for Big Data
;
Security and Privacy in IT Outsourcing
;
Security and Privacy in the Cloud
;
Security Protocols
Abstract:
A client wishes to outsource computation on confidential data to a network of servers. He does not trust a
single server, but believes that multiple servers do not collude. To solve this problem we introduce a new
scheme called JOS for perfect security in the semi-honest model that naturally requires at least three parties.
It differs from classical secure multi-party computation (MPC) through three points: (i) a client-server setting,
where all inputs and outputs are only known to the client; (ii) the use of three parties, where one party serves
merely as “helper” for computation, but does not store any shares of a secret; (iii) distinct use of the distributive
and associative nature of well-known linear encryption schemes to derive our protocols. We improve on the
total amount of communication needed to compute both an AND and a multiplication compared to all prior
schemes (even two party protocols), while matching round complexity or requiring only one more round.
For big-data ana
lysis, network bandwidth is often the most severe limitation, thus minimizing the amount of
communication is essential. Therefore, we make an important step towards making MPC more practical. We
also reduce the total amount of storage needed (eg. in a database setting) compared to all prior schemes using
three parties. Our local computation requirements lag behind non-encrypted computation by less than an order
of magnitude per party, while improving on other schemes, ie. GRR, by several orders of magnitude.
(More)