8,922 research outputs found
ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks
Hash codes are efficient data representations for coping with the ever
growing amounts of data. In this paper, we introduce a random forest semantic
hashing scheme that embeds tiny convolutional neural networks (CNN) into
shallow random forests, with near-optimal information-theoretic code
aggregation among trees. We start with a simple hashing scheme, where random
trees in a forest act as hashing functions by setting `1' for the visited tree
leaf, and `0' for the rest. We show that traditional random forests fail to
generate hashes that preserve the underlying similarity between the trees,
rendering the random forests approach to hashing challenging. To address this,
we propose to first randomly group arriving classes at each tree split node
into two groups, obtaining a significantly simplified two-class classification
problem, which can be handled using a light-weight CNN weak learner. Such
random class grouping scheme enables code uniqueness by enforcing each class to
share its code with different classes in different trees. A non-conventional
low-rank loss is further adopted for the CNN weak learners to encourage code
consistency by minimizing intra-class variations and maximizing inter-class
distance for the two random class groups. Finally, we introduce an
information-theoretic approach for aggregating codes of individual trees into a
single hash code, producing a near-optimal unique hash for each class. The
proposed approach significantly outperforms state-of-the-art hashing methods
for image retrieval tasks on large-scale public datasets, while performing at
the level of other state-of-the-art image classification techniques while
utilizing a more compact and efficient scalable representation. This work
proposes a principled and robust procedure to train and deploy in parallel an
ensemble of light-weight CNNs, instead of simply going deeper.Comment: Accepted to ECCV 201
Towards an Information Theoretic Analysis of Searchable Encryption (Extended Version)
Searchable encryption is a technique that allows a client to store
data in encrypted form on a curious server, such that data can be
retrieved while leaking a minimal amount of information to the
server. Many searchable encryption schemes have been proposed and
proved secure in their own computational model. In this paper we
propose a generic model for the analysis of searchable
encryptions. We then identify the security parameters of
searchable encryption schemes and prove information theoretical
bounds on the security of the parameters. We argue that perfectly
secure searchable encryption schemes cannot be efficient. We
classify the seminal schemes in two categories: the schemes that
leak information upfront during the storage phase, and schemes
that leak some information at every search. This helps designers
to choose the right scheme for an application
Group theory in cryptography
This paper is a guide for the pure mathematician who would like to know more
about cryptography based on group theory. The paper gives a brief overview of
the subject, and provides pointers to good textbooks, key research papers and
recent survey papers in the area.Comment: 25 pages References updated, and a few extra references added. Minor
typographical changes. To appear in Proceedings of Groups St Andrews 2009 in
Bath, U
Distributed Private Heavy Hitters
In this paper, we give efficient algorithms and lower bounds for solving the
heavy hitters problem while preserving differential privacy in the fully
distributed local model. In this model, there are n parties, each of which
possesses a single element from a universe of size N. The heavy hitters problem
is to find the identity of the most common element shared amongst the n
parties. In the local model, there is no trusted database administrator, and so
the algorithm must interact with each of the parties separately, using a
differentially private protocol. We give tight information-theoretic upper and
lower bounds on the accuracy to which this problem can be solved in the local
model (giving a separation between the local model and the more common
centralized model of privacy), as well as computationally efficient algorithms
even in the case where the data universe N may be exponentially large
Key recycling in authentication
In their seminal work on authentication, Wegman and Carter propose that to
authenticate multiple messages, it is sufficient to reuse the same hash
function as long as each tag is encrypted with a one-time pad. They argue that
because the one-time pad is perfectly hiding, the hash function used remains
completely unknown to the adversary.
Since their proof is not composable, we revisit it using a composable
security framework. It turns out that the above argument is insufficient: if
the adversary learns whether a corrupted message was accepted or rejected,
information about the hash function is leaked, and after a bounded finite
amount of rounds it is completely known. We show however that this leak is very
small: Wegman and Carter's protocol is still -secure, if
-almost strongly universal hash functions are used. This implies
that the secret key corresponding to the choice of hash function can be reused
in the next round of authentication without any additional error than this
.
We also show that if the players have a mild form of synchronization, namely
that the receiver knows when a message should be received, the key can be
recycled for any arbitrary task, not only new rounds of authentication.Comment: 17+3 pages. 11 figures. v3: Rewritten with AC instead of UC. Extended
the main result to both synchronous and asynchronous networks. Matches
published version up to layout and updated references. v2: updated
introduction and reference
ARPA Whitepaper
We propose a secure computation solution for blockchain networks. The
correctness of computation is verifiable even under malicious majority
condition using information-theoretic Message Authentication Code (MAC), and
the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty
computation protocol and a layer2 solution, our privacy-preserving computation
guarantees data security on blockchain, cryptographically, while reducing the
heavy-lifting computation job to a few nodes. This breakthrough has several
implications on the future of decentralized networks. First, secure computation
can be used to support Private Smart Contracts, where consensus is reached
without exposing the information in the public contract. Second, it enables
data to be shared and used in trustless network, without disclosing the raw
data during data-at-use, where data ownership and data usage is safely
separated. Last but not least, computation and verification processes are
separated, which can be perceived as computational sharding, this effectively
makes the transaction processing speed linear to the number of participating
nodes. Our objective is to deploy our secure computation network as an layer2
solution to any blockchain system. Smart Contracts\cite{smartcontract} will be
used as bridge to link the blockchain and computation networks. Additionally,
they will be used as verifier to ensure that outsourced computation is
completed correctly. In order to achieve this, we first develop a general MPC
network with advanced features, such as: 1) Secure Computation, 2) Off-chain
Computation, 3) Verifiable Computation, and 4)Support dApps' needs like
privacy-preserving data exchange
Universal Secure Multiplex Network Coding with Dependent and Non-Uniform Messages
We consider the random linear precoder at the source node as a secure network
coding. We prove that it is strongly secure in the sense of Harada and Yamamoto
and universal secure in the sense of Silva and Kschischang, while allowing
arbitrary small but nonzero mutual information to the eavesdropper. Our
security proof allows statistically dependent and non-uniform multiple secret
messages, while all previous constructions of weakly or strongly secure network
coding assumed independent and uniform messages, which are difficult to be
ensured in practice.Comment: 10 pages, 1 figure, IEEEtrans.cls. Online published in IEEE Trans.
Inform. Theor
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