Faster Computation of Self-pairings

Self-pairings have found interesting applications in cryptographic schemes. In this paper, we present a novel method for constructing a self-pairing on supersingular elliptic curves with even embedding degrees, which we call the Ateil pairing. This new pairing improves the efficiency of the self-pairing computation on supersingular curves over finite fields with large characteristics. Based on the $\eta_T$ pairing, we propose a generalization of the Ateil pairing, which we call the Ateil$_i$ pairing. The optimal Ateil$_i$ pairing which has the shortest Miller loop is faster than previously known self-pairings on supersingular elliptic curves over finite fields with small characteristics. We also present a new self-pairing based on the Weil pairing which is faster than the self-pairing based on the Tate pairing on ordinary elliptic curves with embedding degree $one$

Reducing the Complexity of the Weil Pairing Computation

In this paper, we present some new variants based on the Weil pairing for efficient pairing computations. The new pairing variants have the short Miller iteration loop and simple final exponentiation. We then show that computing the proposed pairings is more efficient than computing the Weil pairing. Experimental results for these pairings are also given

Divisible On-line/Off-line Signatures

On-line/Off-line signatures are used in a particular scenario where the signer must respond quickly once the message to be signed is presented. The idea is to split the signing procedure into two phases: the off-line and on-line phases. The signer can do some pre-computations in off-line phase before he sees the message to be signed. In most of these schemes, when signing a message $m$, a partial signature of $m$ is computed in the off-line phase. We call this part of signature the off-line signature token of message $m$. In some special applications, the off-line signature tokens might be exposed in the off-line phase. For example, some signers might want to transmit off-line signature tokens in the off-line phase in order to save the on-line transmission bandwidth. Another example is in the case of on-line/off-line threshold signature schemes, where off-line signature tokens are unavoidably exposed to all the players in the off-line phase. This paper discusses this exposure problem and introduces a new notion: divisible on-line/off-line signatures, in which exposure of off-line signature tokens in off-line phase is allowed. An efficient construction of this type of signatures is also proposed. Furthermore, we show an important application of divisible on-line/off-line signatures in the area of on-line/off-line threshold signatures

Computing Bilinear Pairings on Elliptic Curves with Automorphisms

In this paper, we present a novel method for constructing a super-optimal pairing with great efficiency, which we call the omega pairing. The computation of the omega pairing requires the simple final exponentiation and short loop length in Miller\u27s algorithm which leads to a significant improvement over the previously known techniques on certain pairing-friendly curves. Experimental results show that the omega pairing is about 22% faster and 19% faster than the super-optimal pairing proposed by Scott at security level of AES 80 bits on certain pairing-friendly curves in affine coordinate systems and projective coordinate systems, respectively

Accelerating Sequence Searching: Dimensionality Reduction Method

Similarity search over long sequence dataset becomes increasingly popular in many emerging applications, such as text retrieval, genetic sequences exploring, etc. In this paper, a novel index structure, namely Sequence Embedding Multiset tree (SEM - tree), has been proposed to speed up the searching process over long sequences. The SEM-tree is a multi-level structure where each level represents the sequence data with different compression level of multiset, and the length of multiset increases towards the leaf level which contains original sequences. The multisets, obtained using sequence embedding algorithms, have the desirable property that they do not need to keep the character order in the sequence, i.e. shorter representation, but can reserve the majority of distance information of sequences. Each level of the tree serves to prune the search space more efficiently as the multisets utilize the predicability to finish the searching process beforehand and reduce the computational cost greatly. A set of comprehensive experiments are conducted to evaluate the performance of the SEM-tree, and the experimental results show that the proposed method is much more efficient than existing representative methods.Computer Science, Artificial IntelligenceComputer Science, Information SystemsSCI(E)6ARTICLE3301-3222

Mice with Shank3 Mutations Associated with ASD and Schizophrenia Display Both Shared and Distinct Defects

Genetic studies have revealed significant overlaps of risk genes among psychiatric disorders. However, it is not clear how different mutations of the same gene contribute to different disorders. We characterized two lines of mutant mice with Shank3 mutations linked to ASD and schizophrenia. We found both shared and distinct synaptic and behavioral phenotypes. Mice with the ASD-linked InsG3680 mutatio n manifest striatal synaptic transmission defects before weaning age and impaired juvenile social interaction, coinciding with the early onset of ASD symptoms. On the other hand, adult mice carrying the schizophrenia-linked R1117X mutation show profound synaptic defects in prefrontal cortex and social dominance behavior. Furthermore, we found differential Shank3 mRNA stability and SHANK1/2 upregulation in these two lines. These data demonstrate that different alleles of the same gene may have distinct phenotypes at molecular, synaptic, and circuit levels in mice, which may inform exploration of these relationships in human patients.National Institute of Mental Health (U.S.) (Grant 5R01MH097104)National Institute of Mental Health (U.S.) (Grant 5DP1-MH100706)National Institutes of Health (U.S.) (Grant R01-NS 07312401

Controllable ring signatures and its application to E-prosecution

This paper introduces a new concept called controllable ring signature which is ring signature with additional properties as follow. (1) Anonymous identifica-tion: by an anonymous identification protocol, the real signer can anonymously prove his authorship of the ring signature to the verifier. And this proof is non-transferable. (2) Linkable signature: the real signer can generate an anonymous signature such that every one can verify whether both this anonymous signature and the ring signature are generated by the same anonymous signer. (3) Convertibility: the real signer can convert a ring signature into an ordinary signature by revealing the secret information about the ring signature. These additional properties can fully ensure the interests of the real signer. Especially, compared with a standard ring signature, a controllable ring signature is more suitable for the classic application of leaking secrets. We construct a controllable ring signature scheme which is provably secure according to the formal definition. As an application, we design a E-prosecution scheme based on this controllable ring signature scheme and show its security. 2013 ACADEMY PUBLISHER

Energy-Balanced Data Gathering and Aggregating in WSNs: A Compressed Sensing Scheme

Compressed sensing (CS) is an emerging sampling technique by which the data sampling and aggregating can be done simultaneously, which can be applied to many fields, including data processing in wireless sensor networks (WSNs). In WSNs, data aggregating can reduce data transmission cost and improve energy efficiency. Existing CS-based data gathering work in WSNs utilizes the centralized method to process the data by a sink node, which causes the load imbalance and “coverage hole” problems, and so forth. In this paper, we propose an energy-balanced data gathering and aggregating (EDGA) scheme that integrates a clustering hierarchical structure with the CS to optimize and balance the amount of data transmitted. We also design a data reconstruction algorithm to perform data recovery tasks by utilizing the orthogonal matching pursuit theory, which helps to reconstruct the original data accurately and effectively at sink node. The advantages of the proposed scheme compared with other state-of-the-art related methods are measured on the metrics of data recovery ratio and energy efficiency. We implement our scheme on a simulation platform using a real dataset from Intel lab. Simulation results demonstrate that the proposed data gathering and aggregating scheme guarantees accurate data reconstruction performance and obtains energy efficiency significantly compared to existing methods