304 research outputs found
Communication Complexity and Secure Function Evaluation
We suggest two new methodologies for the design of efficient secure
protocols, that differ with respect to their underlying computational models.
In one methodology we utilize the communication complexity tree (or branching
for f and transform it into a secure protocol. In other words, "any function f
that can be computed using communication complexity c can be can be computed
securely using communication complexity that is polynomial in c and a security
parameter". The second methodology uses the circuit computing f, enhanced with
look-up tables as its underlying computational model. It is possible to
simulate any RAM machine in this model with polylogarithmic blowup. Hence it is
possible to start with a computation of f on a RAM machine and transform it
into a secure protocol.
We show many applications of these new methodologies resulting in protocols
efficient either in communication or in computation. In particular, we
exemplify a protocol for the "millionaires problem", where two participants
want to compare their values but reveal no other information. Our protocol is
more efficient than previously known ones in either communication or
computation
Some Applications of Coding Theory in Computational Complexity
Error-correcting codes and related combinatorial constructs play an important
role in several recent (and old) results in computational complexity theory. In
this paper we survey results on locally-testable and locally-decodable
error-correcting codes, and their applications to complexity theory and to
cryptography.
Locally decodable codes are error-correcting codes with sub-linear time
error-correcting algorithms. They are related to private information retrieval
(a type of cryptographic protocol), and they are used in average-case
complexity and to construct ``hard-core predicates'' for one-way permutations.
Locally testable codes are error-correcting codes with sub-linear time
error-detection algorithms, and they are the combinatorial core of
probabilistically checkable proofs
An Effective Private Data storage and Retrieval System using Secret sharing scheme based on Secure Multi-party Computation
Privacy of the outsourced data is one of the major challenge.Insecurity of
the network environment and untrustworthiness of the service providers are
obstacles of making the database as a service.Collection and storage of
personally identifiable information is a major privacy concern.On-line public
databases and resources pose a significant risk to user privacy, since a
malicious database owner may monitor user queries and infer useful information
about the customer.The challenge in data privacy is to share data with
third-party and at the same time securing the valuable information from
unauthorized access and use by third party.A Private Information Retrieval(PIR)
scheme allows a user to query database while hiding the identity of the data
retrieved.The naive solution for confidentiality is to encrypt data before
outsourcing.Query execution,key management and statistical inference are major
challenges in this case.The proposed system suggests a mechanism for secure
storage and retrieval of private data using the secret sharing technique.The
idea is to develop a mechanism to store private information with a highly
available storage provider which could be accessed from anywhere using queries
while hiding the actual data values from the storage provider.The private
information retrieval system is implemented using Secure Multi-party
Computation(SMC) technique which is based on secret sharing. Multi-party
Computation enable parties to compute some joint function over their private
inputs.The query results are obtained by performing a secure computation on the
shares owned by the different servers.Comment: Data Science & Engineering (ICDSE), 2014 International Conference,
CUSA
Sub-logarithmic Distributed Oblivious RAM with Small Block Size
Oblivious RAM (ORAM) is a cryptographic primitive that allows a client to
securely execute RAM programs over data that is stored in an untrusted server.
Distributed Oblivious RAM is a variant of ORAM, where the data is stored in
servers. Extensive research over the last few decades have succeeded to
reduce the bandwidth overhead of ORAM schemes, both in the single-server and
the multi-server setting, from to . However, all known
protocols that achieve a sub-logarithmic overhead either require heavy
server-side computation (e.g. homomorphic encryption), or a large block size of
at least .
In this paper, we present a family of distributed ORAM constructions that
follow the hierarchical approach of Goldreich and Ostrovsky [GO96]. We enhance
known techniques, and develop new ones, to take better advantage of the
existence of multiple servers. By plugging efficient known hashing schemes in
our constructions, we get the following results:
1. For any , we show an -server ORAM scheme with overhead, and block size . This scheme is
private even against an -server collusion. 2. A 3-server ORAM
construction with overhead and a block size
almost logarithmic, i.e. .
We also investigate a model where the servers are allowed to perform a linear
amount of light local computations, and show that constant overhead is
achievable in this model, through a simple four-server ORAM protocol
Private Database Queries Using Quantum States with Limited Coherence Times
We describe a method for private database queries using exchange of quantum
states with bits encoded in mutually incompatible bases. For technology with
limited coherence time, the database vendor can announce the encoding after a
suitable delay to allow the user to privately learn one of two items in the
database without the ability to also definitely infer the second item. This
quantum approach also allows the user to choose to learn other functions of the
items, such as the exclusive-or of their bits, but not to gain more information
than equivalent to learning one item, on average. This method is especially
useful for items consisting of a few bits by avoiding the substantial overhead
of conventional cryptographic approaches.Comment: extended to generalized (POVM) measurement
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