4,307 research outputs found
Secure and Private Cloud Storage Systems with Random Linear Fountain Codes
An information theoretic approach to security and privacy called Secure And
Private Information Retrieval (SAPIR) is introduced. SAPIR is applied to
distributed data storage systems. In this approach, random combinations of all
contents are stored across the network. Our coding approach is based on Random
Linear Fountain (RLF) codes. To retrieve a content, a group of servers
collaborate with each other to form a Reconstruction Group (RG). SAPIR achieves
asymptotic perfect secrecy if at least one of the servers within an RG is not
compromised. Further, a Private Information Retrieval (PIR) scheme based on
random queries is proposed. The PIR approach ensures the users privately
download their desired contents without the servers knowing about the requested
contents indices. The proposed scheme is adaptive and can provide privacy
against a significant number of colluding servers.Comment: 8 pages, 2 figure
Blind Interference Alignment for Private Information Retrieval
Blind interference alignment (BIA) refers to interference alignment schemes
that are designed only based on channel coherence pattern knowledge at the
transmitters (the "blind" transmitters do not know the exact channel values).
Private information retrieval (PIR) refers to the problem where a user
retrieves one out of K messages from N non-communicating databases (each holds
all K messages) without revealing anything about the identity of the desired
message index to any individual database. In this paper, we identify an
intriguing connection between PIR and BIA. Inspired by this connection, we
characterize the information theoretic optimal download cost of PIR, when we
have K = 2 messages and the number of databases, N, is arbitrary
Robust Private Information Retrieval on Coded Data
We consider the problem of designing PIR scheme on coded data when certain
nodes are unresponsive. We provide the construction of -robust PIR schemes
that can tolerate up to unresponsive nodes. These schemes are adaptive
and universally optimal in the sense of achieving (asymptotically) optimal
download cost for any number of unresponsive nodes up to
Private Information Retrieval Schemes for Coded Data with Arbitrary Collusion Patterns
In Private Information Retrieval (PIR), one wants to download a file from a
database without revealing to the database which file is being downloaded. Much
attention has been paid to the case of the database being encoded across
several servers, subsets of which can collude to attempt to deduce the
requested file. With the goal of studying the achievable PIR rates in realistic
scenarios, we generalize results for coded data from the case of all subsets of
servers of size colluding, to arbitrary subsets of the servers. We
investigate the effectiveness of previous strategies in this new scenario, and
present new results in the case where the servers are partitioned into disjoint
colluding groups.Comment: Updated with a corrected statement of Theorem
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