Capacity of Private Linear Computation for Coded Databases
Document Type
Conference Proceeding
Publication Date
7-2-2018
Abstract
We consider the problem of private linear computation (PLC) in a distributed storage system. In PLC, a user wishes to compute a linear combination of f messages stored in noncolluding databases while revealing no information about the coefficients of the desired linear combination to the databases. In extension of our previous work we employ linear codes to encode the information on the databases. We show that the PLC capacity, which is the ratio of the desired linear function size and the total amount of downloaded information, matches the maximum distance separable (MDS) coded capacity of private information retrieval for a large class of linear codes that includes MDS codes. In particular, the proposed converse is valid for any number of messages and linear combinations, and the capacity expression depends on the rank of the coefficient matrix obtained from all linear combinations.
Identifier
85062882766 (Scopus)
ISBN
[9781538665961]
Publication Title
2018 56th Annual Allerton Conference on Communication Control and Computing Allerton 2018
External Full Text Location
https://doi.org/10.1109/ALLERTON.2018.8636039
First Page
813
Last Page
820
Grant
CNS-1526547
Fund Ref
National Science Foundation
Recommended Citation
Obead, Sarah A.; Lin, Hsuan Yin; Rosnes, Eirik; and Kliewer, Jorg, "Capacity of Private Linear Computation for Coded Databases" (2018). Faculty Publications. 8537.
https://digitalcommons.njit.edu/fac_pubs/8537
