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.
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.
15662668
Orthogonality between Key Privacy and Data Privacy, Revisited
Key privacy is a notion regarding the privacy of the owner of a public key, which has important applications in building (receiver) anonymous channels, or privacy-enhanced authentication/signature schemes. Key privacy is considered to be an orthogonal (i.e., independent), notion from data privacy, while the key privacy of many public key encryption schemes has not been explored, though their data privacy is comparatively well understood. In this paper, we study key privacy of many practical encryption schemes and identify evidences that key privacy is not comparable to data privacy. We also formalize key privacy in the plaintext checking attack model and point out some generic transforms to enhance the key privacy of an encryption scheme. Interestingly, these well-known techniques have been used to enhance data security. Finally, we give detailed security analyses on the signed hashed-ElGamal encryption [27] in the random oracle model, of both key privacy and data security against chosen ciphertext attack. Again, this specific example supports our claim on the relation of two notions.
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.
15452878
A generic construction of useful client puzzles
Denial of Service (DoS) attacks are serious threats for network societies. For dealing with DoS attacks, Jakobsson and Juels first proposed the notion of useful client puzzles (UCPs) which simultaneously decrease servers' burden and increase clients'. In ACM CCS'04, Diament, Lee, Keromytis, and Yung introduced the decryption-based UCPs. In this paper, we give a general framework for constructing such UCPs which is based on identity-based cryptography along with well-analyzed symmetric key authenticated encryption techniques (without random oracles). By using this framework, we can flexibly construct various UCPs according to different types of system requirements. We also give some instantiations: the first is a UCP based on the Boneh-Boyen Identity based encryption scheme, with provable security in the standard model. Another one is a UCP based on the Boneh-Gentry-Hamburg identity-based encryption scheme, which doesn't require pairings.
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.
8645725
Multiple aggregations over data streams
Monitoring aggregates on IP traffic data streams is a compelling application for data stream management systems. The need for exploratory IP traffic data analysis naturally leads to posing related aggregation queries on data streams, that differ only in the choice of grouping attributes. In this paper, we address this problem of efficiently computing multiple aggregations over high speed data streams, based on a two-level LFTA/HFTA DSMS architecture, inspired by Gigascope.Our first contribution is the insight that in such a scenario, additionally computing and maintaining fine-granularity aggregation queries (phantoms) at the LFTA has the benefit of supporting shared computation. Our second contribution is an investigation into the problem of identifying beneficial LFTA configurations of phantoms and user-queries. We formulate this problem as a cost optimization problem, which consists of two sub-optimization problems: how to choose phantoms and how to allocate space for them in the LFTA. We formally show the hardness of determining the optimal configuration, and propose cost greedy heuristics for these independent sub-problems based on detailed analyses. Our final contribution is a thorough experimental study, based on real IP traffic data, as well as synthetic data, to demonstrate the effectiveness of our techniques for identifying beneficial configurations.
44262524
Enhancing the B+-tree by dynamic node popularity caching
We propose the Cache Coherent B^+-tree (CCB^+-tree), an indexing structure that can improve search performance compared to the traditional B^+-tree. The CCB^+-tree makes use of the unused space in the internal nodes of a B^+-tree to cache frequently queried leaf node addresses, thus saving node accesses. An experimental study shows that the CCB^+-tree can outperform the traditional B^+-tree on workloads where certain queries are much more popular than the others.
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.
15606709
Mining distribution change in stock order streams
Detecting changes in stock prices is a well known problem in finance with important implications for monitoring and business intelligence. Forewarning of changes in stock price, can be made by the early detection of changes in the distributions of stock order numbers. In this paper, we address the change detection problem for streams of stock order numbers and propose a novel incremental detection algorithm. Our algorithm gains high accuracy and low delay by employing a natural Poisson distribution assumption about the nature of stock order streams. We establish that our algorithm is highly scalable and has linear complexity. We also experimentally demonstrate its effectiveness for detecting change points, via experiments using both synthetic and real-world datasets.
967678
iDistance: An adaptive B+-tree based indexing method for nearest neighbor search
In this article, we present an efficient B+-tree based indexing method, called iDistance, for K-nearest neighbor (KNN) search in a high-dimensional metric space. iDistance partitions the data based on a space- or data-partitioning strategy, and selects a reference point for each partition. The data points in each partition are transformed into a single dimensional value based on their similarity with respect to the reference point. This allows the points to be indexed using a B+-tree structure and KNN search to be performed using one-dimensional range search. The choice of partition and reference points adapts the index structure to the data distribution.We conducted extensive experiments to evaluate the iDistance technique, and report results demonstrating its effectiveness. We also present a cost model for iDistance KNN search, which can be exploited in query optimization.