10078749
RoleVAT: Visual Assessment of Practical Need for Role Based Access Control
Role based access control (RBAC) is a powerful security administration concept that can simplify permission assignment management. Migration to and maintenance of RBAC requires role engineering, the identification of a set of roles that offer administrative benefit. However, establishing that RBAC is desirable in a given enterprise is lacking in current role engineering processes. To help identify the practical need for RBAC, we propose RoleVAT, a Role engineering tool for the Visual Assessment of user and permission Tendencies. User and permission clusters can be visually identified as potential user groups or roles. The benefit and impact of this visual analysis in enterprise environments is discussed and demonstrated through testing on real life as well as synthetic datasets. Our experimental results show the effectiveness of RoleVAT as well as interesting user and role tendencies in real enterprise environments.
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.
2552624
Approximate NN queries on Streams with Guaranteed Error/performance Bounds
In data stream applications, data arrive continuously and can only be scanned once as the query processor has very limited memory (relative to the size of the stream) to work with. Hence, queries on data streams do not have access to the entire data set and query answers are typically approximate. While there have been many studies on the k Nearest Neighbors (kNN) problem in conventional multi-dimensional databases, the solutions cannot be directly applied to data streams for the above reasons. In this paper, we investigate the kNN problem over data streams. We first introduce the e-approximate kNN (ekNN) problem that finds the approximate kNN answers of a query point Q such that the absolute error of the k-th nearest neighbor distance is bounded by e. To support ekNN queries over streams, we propose a technique called DISC (aDaptive Indexing on Streams by space-filling Curves). DISC can adapt to different data distributions to either (a) optimize memory utilization to answer ekNN queries under certain accuracy requirements or (b) achieve the best accuracy under a given memory constraint. At the same time, DISC provide efficient updates and query processing which are important requirements in data stream applications. Extensive experiments were conducted using both synthetic and real data sets and the results confirm the effectiveness and efficiency of DISC.
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.
16280855
Indexing Fast Moving Objects for kNN Queries Based on Nearest Landmarks
With the rapid advancements in positioning technologies such as the Global Positioning System (GPS) and wireless communications, the tracking of continuously moving objects has become more convenient. However, this development poses new challenges to database technology since maintaining up-to-date information regarding the location of moving objects incurs an enormous amount of updates. Existing indexes can no longer keep up with the high update rate while providing speedy retrieval at the same time. This study aims to improve k nearest neighbor (kNN) query performance while reducing update costs. Our approach is based on an important observation that queries usually occur around certain places or spatial landmarks of interest, called reference points. We propose the Reference-Point-based tree (RP-tree), which is a two-layer index structure that indexes moving objects according to reference points. Experimental results show that the RP-tree achieves significant improvement over the TPR-tree.
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.
37850409
Round Optimal Distributed Key Generation of Threshold Cryptosystem Based on Discrete Logarithm Problem
We propose a distributed key generation protocol for discrete logarithm problem based threshold cryptosystems by introducing an efficient (publicly) verifiable encryption scheme from any homomorphic encryption with a non-interactive proof of fairness. Previous constructions of the same kind are either only based on a narrow definition of homomorphism or only a unique encryption scheme is considered. Our construction generalizes the scope of such design to a broader range of encryption schemes with efficient constructions of proofs of fairness. Since the protocol is round optimal (one-round) in the distributed fashion, adaptive adversary is not different from a static adversary, thus a simplified protocol design is possible. Our scheme is extremely capable for an environment with already built public key infrastructure. The verifiable encryption with fairness developed here can be used as building blocks of a variety of cryptographical applications like publicly verifiable secret sharing (PVSS), e-voting and auction schemes.
4696945
Combining 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 give 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.
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.
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.
711993
On the Security of Multiple Encryption or CCA-security+CCA-security=CCA-security?
In a practical system, a message is often encrypted more than once by different encryptions, here called multiple encryption, to enhance its security. Additionally, new features may be achieved by multiple encrypting a message, such as the key-insulated cryptosystems and anonymous channels. Intuitively, a multiple encryption should remain “secure”, whenever there is one component cipher unbreakable in it. In NESSIE’s latest Portfolio of recommended cryptographic primitives (Feb. 2003), it is suggested to use multiple encryption with component ciphers based on different assumptions to acquire long term security. However, in this paper we show this needs careful discussion, especially, this may not be true according to adaptive chosen ciphertext attack (CCA), even with all component ciphers CCA-secure. We define an extended model of (standard) CCA called chosen ciphertext attack for multiple encryption (ME-CCA) emulating partial breaking of assumptions, and give constructions of multiple encryption satisfying ME-CCA-security. We further relax CCA by introducing weak ME-CCA (ME-wCCA) and study the relations among these definitions, proving ME-wCCA-security can be acquired by combining IND-CCA-secure component ciphers together. We then apply these results to key-insulated cryptosystem.