39624890
Strong Anonymous Signatures
The notion of anonymous signatures has recently been formalized by [18], which captures an interesting property that a digital signature can sometimes hide the identity of the signer, if the message is hidden from the verifier. However, in many practical applications, e.g., an anonymous paper review system mentioned in [18], the message for anonymous authentication is actually known to the verifier. This implies that the effectiveness of previous anonymous signatures may be unjustified in these applications. In this paper, we extend the previous models, and develop a related primitive called strong anonymous signatures. For strong anonymous signatures, the identity of the signer remains secret even if the challenge message is chosen by an adversary. We then demonstrate some efficient constructions and prove their security in our model.
2046540
Generic Combination of Public Key Encryption with Keyword Search and Public Key Encryption
In this paper, we study the problem of secure integrating public key encryption with keyword search (PEKS) with public key data encryption (PKE). We argue the previous security model is not complete regarding keyword privacy and the previous constructions are secure only in the random oracle model. We solve these problems by first defining a new security model, then give a generic construction which is secure in the new security model without random oracles. Our construction is based on secure PEKS and tag-KEM/DEM schemes and achieves modular design. We also point out some applications and extensions for our construction. For example, instantiate our construction with proper components, we have a concrete scheme without random oracles, whose performance is even competitive to the previous schemes with random oracles.
17395662
On the Security of Cryptosystems with All-or-Nothing Transform
An AONT is an efficiently computable transform with two properties. Given all the bits of its output, it is easy to retrieve the message. On the other hand, if sufficiently many bits of the output are missing, it is computationally infeasible for an polynomial-time adversary to learn any information about the message. The natural intuition then may be deduced that if an secure AONT is used in a cryptosystem, the whole system will be secure as long as sufficiently many bits are “protected”. However, we show this is not enough. Our results are three-fold: First we answer an open problem raised in [6], showing that previous definitions are not sufficient to guarantee a provably secure cryptosystem with strong data privacy, namely, indistinguishability against chosen ciphertext attack (IND-CCA). Second, we give a new definition to AONT, showing this definition suffices to guarantee an AONT integrated with any encryption functions to acquire IND-CCA secure cryptosystems. Third, we give concrete constructions that satisfy the new definition.
61878
Formal Security Treatments for IBE-to-Signature Transformation: Relations among Security Notions
In a seminal paper of identity based encryption (IBE), Boneh and Franklin [6] mentioned an interesting transform from an IBE scheme to a signature scheme, which was observed by Moni Naor. In this paper, we give formal security treatments for this transform and discover several implications and separations among security notions of IBE and transformed signature. For example, we show for such a successful transform, one-wayness of IBE is an essential condition. Additionally, we give a sufficient and necessary condition for converting a semantically secure IBE scheme into an existentially unforgeable signature scheme. Our results help establish strategies on design and automatic security proof of signature schemes from (possibly weak) IBE schemes. We also show some separation results which strongly support that one-wayness, rather than semantic security, of IBE captures an essential condition to achieve secure signature.
36775607
Short Signature and Universal Designated Verifier Signature Without Random Oracles
We propose the first universal designated verifier signature (UDVS) scheme whose security can be proven without random oracles, whereas the security of all previously known UDVS schemes are proven only when random oracles are assumed. To achieve our goal, we present a new short signature scheme without random oracles, which is a variant of BB04 scheme [4]. We also give new security definitions to UDVS. We note that our weakest security definitions are even stronger than any of previously known security definitions: We allow adversaries to behave more adaptively in oracle accessing and we also consider adaptive chosen public key attacks. The security of our UDVS scheme is then proven according to the new security definitions.
10170990
Tweaking TBE/IBE to PKE Transforms with Chameleon Hash Functions
We present two transforms to acquire chosen ciphertext security from tag based techniques. The first one requires the separability of underlying primitives. By separability, informally, we mean the encryption algorithm has special structures and can process the identity and the message independently. Compared with generic transforms [8],it significantly reduces the ciphertext size overhead with only marginal computation cost. Compared with [11], the only known technique which directly achieves chosen ciphertext secure public key encryption from separable identity based primitives, it only requires selective-Tag/ID security of underlying primitives. Our second transform is less efficient but performs generically. Both transforms preserve the public verifiability of underlying primitives, and can be extended to hierarchical identity based encryption (HIBE) and threshold settings. As an independent interest, we also investigate the security requirements of chameleon hash functions to build strongly unforgeable one-time signatures.
7619448
Generalized multidimensional data mapping and query processing
Multidimensional data points can be mapped to one-dimensional space to exploit single dimensional indexing structures such as the B+-tree. In this article we present a Generalized structure for data Mapping and query Processing (GiMP), which supports extensible mapping methods and query processing. GiMP can be easily customized to behave like many competent indexing mechanisms for multi-dimensional indexing, such as the UB-Tree, the Pyramid technique, the iMinMax, and the iDistance. Besides being an extendible indexing structure, GiMP also serves as a framework to study the characteristics of the mapping and hence the efficiency of the indexing scheme. Specifically, we introduce a metric called mapping redundancy to characterize the efficiency of a mapping method in terms of disk page accesses and analyze its behavior for point, range and kNN queries. We also address the fundamental problem of whether an efficient mapping exists and how to define such a mapping for a given data set.
18050648
Optimized algorithms for predictive range and KNN queries on moving objects
There have been many studies on management of moving objects recently. Most of them try to optimize the performance of predictive window queries. However, not much attention is paid to two other important query types: the predictive range query and the predictive k nearest neighbor query. In this article, we focus on these two types of queries. The novelty of our work mainly lies in the introduction of the Transformed Minkowski Sum, which can be used to determine whether a moving bounding rectangle intersects a moving circular query region. This enables us to use the traditional tree traversal algorithms to perform range and kNN searches. We theoretically show that our algorithms based on the Transformed Minkowski Sum are optimal in terms of the number of tree node accesses. We also experimentally verify the effectiveness of our technique and show that our algorithms outperform alternative approaches.
49680
High-dimensional kNN joins with incremental updates
The k Nearest Neighbor (kNN) join operation associates each data object in one data set with its k nearest neighbors from the same or a different data set. The kNN join on high-dimensional data (high-dimensional kNN join) is a very expensive operation. Existing high-dimensional kNN join algorithms were designed for static data sets and therefore cannot handle updates efficiently. In this article, we propose a novel kNN join method, named kNNJoin+, which supports efficient incremental computation of kNN join results with updates on high-dimensional data. As a by-product, our method also provides answers for the reverse kNN queries with very little overhead. We have performed an extensive experimental study. The results show the effectiveness of kNNJoin+ for processing high-dimensional kNN joins in dynamic workloads.
7952157
Effective Density Queries on ContinuouslyMoving Objects
This paper assumes a setting where a population of objects move continuously in the Euclidean plane. The position of each object, modeled as a linear function from time to points, is assumed known. In this setting, the paper studies the querying for dense regions. In particular, the paper defines a particular type of density query with desirable properties and then proceeds to propose an algorithm for the efficient computation of density queries. While the algorithm may exploit any existing index for the current and near-future positions of moving objects, the Bx-tree is used. The paper reports on an extensive empirical study, which elicits the performance properties of the algorithm.
18170201
Streaming multiple aggregations using phantoms
Data streams characterize the high speed and large volume input of a new class of applications such as network monitoring, web content analysis and sensor networks. Among these applications, network monitoring may be the most compelling one—the backbone of a large internet service provider can generate 1 petabyte of data per day. For many network monitoring tasks such as traffic analysis and statistics collection, aggregation is a primitive operation. Various analytical and statistical needs naturally lead to related aggregate queries. In this article, we address the problem of efficiently computing multiple aggregations over high-speed data streams based on the two-level query processing architecture of GS, a real data stream management system deployed in AT & T. We discern that additionally computing and maintaining fine-granularity aggregations (called phantoms) has the benefit of supporting shared computation. Based on a thorough analysis, we propose algorithms to identify the best set of phantoms to maintain and determine allocation of resources (particularly, space) to compute the aggregations. Experiments show that our algorithm achieves near-optimal computation costs, which outperforms the best adapted algorithm by more than an order of magnitude.