12,884 research outputs found
Single-Server Multi-Message Private Information Retrieval with Side Information
We study the problem of single-server multi-message private information
retrieval with side information. One user wants to recover out of
independent messages which are stored at a single server. The user initially
possesses a subset of messages as side information. The goal of the user is
to download the demand messages while not leaking any information about the
indices of these messages to the server. In this paper, we characterize the
minimum number of required transmissions. We also present the optimal linear
coding scheme which enables the user to download the demand messages and
preserves the privacy of their indices. Moreover, we show that the trivial MDS
coding scheme with transmissions is optimal if or .
This means if one wishes to privately download more than the square-root of the
number of files in the database, then one must effectively download the full
database (minus the side information), irrespective of the amount of side
information one has available.Comment: 12 pages, submitted to the 56th Allerton conferenc
A Formal Study of the Privacy Concerns in Biometric-Based Remote Authentication Schemes
With their increasing popularity in cryptosystems, biometrics have attracted more and more attention from the information security community. However, how to handle the relevant privacy concerns remains to be troublesome. In this paper, we propose a novel security model to formalize the privacy concerns in biometric-based remote authentication schemes. Our security model covers a number of practical privacy concerns such as identity privacy and transaction anonymity, which have not been formally considered in the literature. In addition, we propose a general biometric-based remote authentication scheme and prove its security in our security model
When the Hammer Meets the Nail: Multi-Server PIR for Database-Driven CRN with Location Privacy Assurance
We show that it is possible to achieve information theoretic location privacy
for secondary users (SUs) in database-driven cognitive radio networks (CRNs)
with an end-to-end delay less than a second, which is significantly better than
that of the existing alternatives offering only a computational privacy. This
is achieved based on a keen observation that, by the requirement of Federal
Communications Commission (FCC), all certified spectrum databases synchronize
their records. Hence, the same copy of spectrum database is available through
multiple (distinct) providers. We harness the synergy between multi-server
private information retrieval (PIR) and database- driven CRN architecture to
offer an optimal level of privacy with high efficiency by exploiting this
observation. We demonstrated, analytically and experimentally with deployments
on actual cloud systems that, our adaptations of multi-server PIR outperform
that of the (currently) fastest single-server PIR by a magnitude of times with
information theoretic security, collusion resiliency, and fault-tolerance
features. Our analysis indicates that multi-server PIR is an ideal
cryptographic tool to provide location privacy in database-driven CRNs, in
which the requirement of replicated databases is a natural part of the system
architecture, and therefore SUs can enjoy all advantages of multi-server PIR
without any additional architectural and deployment costs.Comment: 10 pages, double colum
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
Anonymous subject identification and privacy information management in video surveillance
The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework
The capacity of symmetric Private information retrieval
Private information retrieval (PIR) is the problem of retrieving as efficiently as possible, one out of K messages from N non-communicating replicated databases (each holds all K messages) while keeping the identity of the desired message index a secret from each individual database. Symmetric PIR (SPIR) is a generalization of PIR to include the requirement that beyond the desired message, the user learns nothing about the other K - 1 messages. The information theoretic capacity of SPIR (equivalently, the reciprocal of minimum download cost) is the maximum number of bits of desired information that can be privately retrieved per bit of downloaded information. We show that the capacity of SPIR is 1-1/N regardless of the number of messages K, if the databases have access to common randomness (not available to the user) that is independent of the messages, in the amount that is at least 1/(N - 1) bits per desired message bit, and zero otherwise
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