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.
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.
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.
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.
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.
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.
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.
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.
36437069
iDistance Techniques
7981345
Similarity search: a matching based approach
Similarity search is a crucial task in multimedia retrieval and data mining. Most existing work has modelled this problem as the nearest neighbor (NN) problem, which considers the distance between the query object and the data objects over a fixed set of features. Such an approach has two drawbacks: 1) it leaves many partial similarities uncovered; 2) the distance is often affected by a few dimensions with high dissimilarity. To overcome these drawbacks, we propose the k-n-match problem in this paper.The k-n-match problem models similarity search as matching between the query object and the data objects in n dimensions, where n is a given integer smaller than dimensionality d and these n dimensions are determined dynamically to make the query object and the data objects returned in the answer set match best. The k-n-match query is expected to be superior to the kNN query in discovering partial similarities, however, it may not be as good in identifying full similarity since a single value of n may only correspond to a particular aspect of an object instead of the entirety. To address this problem, we further introduce the frequent k-n-match problem, which finds a set of objects that appears in the k-n-match answers most frequently for a range of n values. Moreover, we propose search algorithms for both problems. We prove that our proposed algorithm is optimal in terms of the number of individual attributes retrieved, which is especially useful for information retrieval from multiple systems. We can also apply the proposed algorithmic strategy to achieve a disk based algorithm for the (frequent) k-n-match query. By a thorough experimental study using both real and synthetic data sets, we show that: 1) the k-n-match query yields better result than the kNN query in identifying similar objects by partial similarities; 2) our proposed method (for processing the frequent k-n-match query) outperforms existing techniques for similarity search in terms of both effectiveness and efficiency.