8910317
Continuous Intersection Joins Over Moving Objects
The continuous intersection join query is computationally expensive yet important for various applications on moving objects. No previous study has specifically addressed this query type. We can adopt a naive algorithm or extend an existing technique (TP-Join) to process the query. However, they compute the answer for either too long or too short a time interval, which results in either a very large computation cost per object update or too frequent answer updates, respectively. This motivates us to optimize the query processing in the time dimension. In this study, we achieve this optimization by introducing the new concept of time-constrained (TC) processing. Further, TC processing enables a set of effective improvement techniques on traditional intersection join algorithms. With a thorough experimental study, we show that our algorithm outperforms the best adapted existing solution by several orders of magnitude.
36437069
iDistance Techniques
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.
7607256
Making the pyramid technique robust to query types and workloads
The effectiveness of many existing high-dimensional indexing structures is limited to specific types of queries and workloads. For example, while the Pyramid technique and the iMinMax are efficient for window queries, the iDistance is superior for kNN queries. We present a new structure, called the P/sup +/-tree, that supports both window queries and kNN queries under different workloads efficiently. In the P/sup +/-tree, a B/sup +/-tree is employed to index the data points as follows. The data space is partitioned into subspaces based on clustering, and points in each subspace are mapped onto a single dimensional space using the Pyramid technique, and stored in the B/sup +/ -tree. The crux of the scheme lies in the transformation of the data which has two crucial properties. First, it maps each subspace into a hypercube so that the Pyramid technique can be applied. Second, it shifts the cluster center to the top of the pyramid, which is the case that the Pyramid technique works very efficiently. We present window and kNN query processing algorithms for the P/sup +/-tree. Through an extensive performance study, we show that the P/sup +/-tree has considerable speedup over the Pyramid technique and the iMinMax for window queries and outperforms the iDistance for kNN queries.
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.
8154859
Improvements on Security Proofs of Some Identity Based Encryption Schemes
Concrete security reduction plays an important role in practice, because it explicitly bounds an adversary’s success probability as a function of their resources. In this paper, we study the security reductions of Boneh-Franklin identity based encryption (IBE) schemes and its variants, focusing on the efficiency of their security reductions: 
 
Improvements on proofs of Boneh-Franklin IBE and variants. The proof of the Boneh-Franklin IBE (BF-IBE) scheme was long believed to be correct until recently, Galindo pointed out a flawed step in the proof and gave a new proof, however, the new reduction was even looser. We give a new proof of the BF-IBE scheme that essentially improves previously known results. Very interestingly, our result is even better than the original underestimated one. Similar analysis can also be applied to Galindo’s BF-IBE variant, resulting in a tighter reduction. 
 
A new BF-IBE variant with tighter security reductions. We propose another variant of the BF-IBE that admits better security reduction, however, the scheme relies on a stronger assumption, namely the Gap Bilinear Diffie-Hellman (GBDH) assumption.
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.
207469
A Generalized Global Convergence Theory of Projection-Type Neural Networks for Optimization
The projection-type neural networks $\tau \frac{dx}{dt}=-x+P_{\Omega }(x-\Lambda (t)\partial ^{0}E(x))$are generic and useful models for solving the constrained optimization problems min {E(x)|x∈Ω}. In the existing convergence/ stability analysis, the most are deduced based on the assumptions that E is uniformly or strictly convex and Ω is box-shaped. In this talk we present a generalized theory on convergence/stability of the networks. In the general setting that E is only convex and Ω is any closed bounded convex set, it is shown the global convergence/asymptotic stability of the networks in a specified sense. The presented theory sharpens and generalizes the existing results, and, consequently, underlies the applicability of the neural networks for a broader type of optimization problems.
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.
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.