125681
Strengthening Zero-Knowledge Protocols Using Signatures
AbstractRecently there has been an interest in zero-knowledge protocols
with stronger properties, such as concurrency, simulation
soundness, non-malleability, and universal composability.
In this paper we show a novel technique to convert a large class of
existing honest-verifier zero-knowledge protocols into ones with these
stronger properties in the common reference string model.
More precisely, our technique utilizes a signature scheme
existentially unforgeable against adaptive chosen-message attacks, and
transforms any Σ-protocol (which is honest-verifier
zero-knowledge) into a simulation sound concurrent
zero-knowledge protocol. We also introduce Ω-protocols, a variant of
Σ-protocols for which our technique further achieves the properties of non-malleability and/or universal composability. In addition to its conceptual simplicity, a main advantage of this new technique over previous ones is that
it avoids the Cook-Levin theorem, which tends to be rather
inefficient. Indeed, our technique allows for very efficient instantiation
based on the security of some efficient signature schemes and standard
number-theoretic assumptions. For instance, one instantiation of our technique yields a universally composable zero-knowledge protocol under the
Strong RSA assumption, incurring an overhead of
a small constant number of exponentiations, plus the generation of two
signatures.
5253044
Towards the classical communication complexity of entanglement distillation protocols with incomplete information
Entanglement is an essential resource for quantum communication and quantum computation, similar to shared random bits in the classical world. Entanglement distillation extracts nearly-perfect entanglement from imperfect entangled state. The classical communication complexity of these protocols is the minimal amount of classical information that needs to be exchanged for the conversion. In this paper, we focus on the communication complexity of protocols that operate with incomplete information, i.e., where the inputs are mixed states and/or prepared adversarially. We consider three models of imperfect entanglement, namely, the bounded measurement model, the depolarization model, and the fidelity model. We describe these models as well as the motivations for studying them. For the bounded measurement model and the depolarization model, we prove tight and almost-tight bounds on the output quality of non-interactive protocols. For the fidelity model, we prove a lower bound that matches the upper bound given by Ambainis et al., and thus completely characterizes communication complexity of entanglement distillation protocols for this model. Our result also suggests the optimality of the BB84 protocol in terms of communication complexity. We emphasize that although some of the results appear intuitively straightforward, their proofs are not. In fact, two novel techniques are developed for proving these results. We believe that these techniques are of independent interests, too.
1745284
On Simulation-Sound Trapdoor Commitments
We study the recently introduced notion of a simulation-sound trapdoor commitment (SSTC) scheme. In this paper, we present a new, simpler definition for an SSTC scheme that admits more efficient constructions and can be used in a larger set of applications. Specifically, we show how to construct SSTC schemes from any one-way functions, and how to construct very efficient SSTC schemes based on specific number-theoretic assumptions. We also show how to construct simulation-sound, non-malleable, and universally-composable zero-knowledge protocols using SSTC schemes, yielding, for instance, the most efficient universally-composable zero-knowledge protocols known. Finally, we explore the relation between SSTC schemes and non-malleable commitment schemes by presenting a sequence of implication and separation results, which in particular imply that SSTC schemes are non-malleable.
454393
Private Keyword-Based Push and Pull with Applications to Anonymous Communication
We propose a new keyword-based Private Information Retrieval (PIR) model that allows private modification of the database from which information is requested. In our model, the database is distributed over n servers, any one of which can act as a transparent interface for clients. We present protocols that support operations for accessing data, focusing on privately appending labelled records to the database (push) and privately retrieving the next unseen record appended under a given label (pull). The communication complexity between the client and servers is independent of the number of records in the database (or more generally, the number of previous push and pull operations) and of the number of servers. Our scheme also supports access control oblivious to the database servers by implicitly including a public key in each push, so that only the party holding the private key can retrieve the record via pull. To our knowledge, this is the first system that achieves the following properties: private database modification, private retrieval of multiple records with the same keyword, and oblivious access control. We also provide a number of extensions to our protocols and, as a demonstrative application, an unlinkable anonymous communication service using them.
5335881
On statistical query sampling and NMR quantum computing
We introduce a "statistical query sampling" model, in which the goal of an algorithm is to produce an element in a hidden set S/spl sube/{0,1}/sup n/ with reasonable probability. The algorithm gains information about S through oracle calls (statistical queries), where the algorithm submits a query function g(/spl middot/) and receives an approximation to Pr/sub x/spl isin/S/[g(x)=1]. We show how this model is related to NMR quantum computing, in which only statistical properties of an ensemble of quantum systems can be measured, and in particular to the question of whether one can translate standard quantum algorithms to the NMR setting without putting all of their classical postprocessing into the quantum system. Using Fourier analysis techniques developed in the related context of statistical query learning, we prove a number of lower bounds (both information-theoretic and cryptographic) on the ability of algorithms to produce an x/spl isin/S, even when the set S is fairly simple. These lower bounds point out a difficulty in efficiently applying NMR quantum computing to algorithms such as Shor's and Simon's algorithm that involve significant classical postprocessing. We also explicitly relate the notion of statistical query sampling to that of statistical query learning.
895559
Co-Training and Expansion: Towards Bridging Theory and Practice
Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets of features. It has had a number of practical successes, yet previous theoretical analyses have needed very strong assumptions on the data that are unlikely to be satisfied in practice. 
 
In this paper, we propose a much weaker "expansion" assumption on the underlying data distribution, that we prove is sufficient for iterative co-training to succeed given appropriately strong PAC-learning algorithms on each feature set, and that to some extent is necessary as well. This expansion assumption in fact motivates the iterative nature of the original co-training algorithm, unlike stronger assumptions (such as independence given the label) that allow a simpler one-shot co-training to succeed. We also heuristically analyze the effect on performance of noise in the data. Predicted behavior is qualitatively matched in synthetic experiments on expander graphs.
7799230
Passage feedback with IRIS
We compare a user-defined passage feedback (pf) system to a document feedback (df) system. Df employed the adaptive linear model for retrieval, while pf used weighted query expansion based on positive and negative feedback. Twenty-four searchers performed the same six tasks in varying search and system-order per TREC-8 guidelines. We hypothesized that pf, which featured interactive query expansion, would outperform df, which relied on automatic query expansion. Initial analysis appeared to reject this hypothesis, as df showed slightly higher overall performance than pf. However, analysis by system-order groups indicates only the first pf use had lower performance. These data suggest that pf was more difficult to learn than df, though the second pf use yielded competitive performance. If performance of pf is indeed affected by learning, an improved pf system with usability enhancements may prove to be an effective mechanism for interactive information retrieval.
29113389
Approximate string matching in LDAP based on edit distance
As the E-Commerce rapidly grows up, searching data is almost necessary in every application. Approximate string matching problems play a very important role to search with errors. Against these problems "Edit distance" and "Soundex" are two common techniques, especially the latter one is a "sound-like" method and had been applied to the LDAP server. Nevertheless, it is not adequate for certain situations especially when we perform the symbol matching (as in DNA); it doesn't make sense to use the "sound-like" method. On the other hand, "Edit distance" has a clear definition and also is widely used in many fields of application. Since the design of LDAP server is optimized for reading, applying edit distance technique to LDAP server has the problem of lowering speed. In this paper we design efficient data structures and an algorithm to solve the speed problem, and furthermore we use three filter conditions [1] based on the n-gram technique to achieve a well filter performance. Finally we also demonstrate experimentally the benefits of applying our algorithm and its limitations.
16162932
AntSearch: An Ant Search Algorithm in Unstructured Peer-to-Peer Networks
The most prevalent peer-to-peer (P2P) application till today is file sharing, and unstructured P2P networks can support inherent heterogeneity of peers, are highly resilient to peers’ failures, and incur low overhead at peer arrivals and departures. Dynamic querying (DQ) is a new flooding technique which could estimate a proper time-to-live (TTL) value for a query flooding by estimating the popularity of the searched files, and retrieve sufficient results under controlled flooding range for reducing network traffic. Recent researches show that a large amount of peers in the P2P file sharing system are the free-riders, and queries are seldom hit by those peers. The free-riders problem causes a large amount of redundant messages in the DQ-like search algorithm. In this paper, we proposed a new search algorithm, called "AntSearch", to solve the problem. In AntSearch, each peer maintains its hit rate of previous queries, and records a list of pheromone values of its immediate neighbors. Based on the pheromone values, a query is only flooded to those peers which are not likely to be the free-riders. Our simulation results show that, compared with DQ and its enhanced algorithm DQ+, the AntSearch algorithm averagely reduces 50% network traffic at almost the same search latency as DQ+, while retrieving sufficient results for a query with a given required number of results.
37157806
An interactive WWW search engine for user-defined collections
Given the dynamic nature and the quantity of information on the WWW, many individual users and organizations compile and use focused WWW resource lists related to a particular topic or subject domain. The IRISWeb system extends this concept such that any user-defined set of WWW pages (a virtual collection) can be retrieved, indexed, and searched using a powerful full-text search engine with a relevance-feedback interface. This capability adds full-text searching to highly customized subsets of the WWW. Here we describe the IRISWeb software and an experiment that highlights its potential.
6388420
Proof: A DHT-Based Peer-to-Peer Search Engine
In this paper we focus on building a large scale keyword search service over structured peer-to-peer (P2P) networks. Current state-of-the-art keyword search approaches for structured P2P systems are based on inverted list intersection. However, the biggest challenge in those approaches is that when the indices are distributed over peers, a simple query may cause a large amount of data to be transmitted over the network. We propose a new P2P keyword search scheme, called "Proof", to reduce network traffic for queries. The key idea is storing a content summary for each Web page in the inverted list, so that a query can be processed by only transmitting a small size of candidate results. Our simulation results showed that, compared with previous DHT-based P2P systems, Proof can dramatically reduce network traffic and computation time. It provides 100% precision and 90.09% recall of search results, at an acceptable cost of storage overhead, even when the number of peers and documents increases continually