A data-mining approach for multiple structural alignment of proteins

Comparing the 3D structures of proteins is an important but computationally hard problem in bioinformatics. In this paper, we propose studying the problem when much less information or assumptions are available. We model the structural alignment of proteins as a combinatorial problem. In the problem, each protein is simply a set of points in the 3D space, without sequence order information, and the objective is to discover all large enough alignments for any subset of the input. We propose a data-mining approach for this problem. We first perform geometric hashing of the structures such that points with similar locations in the 3D space are hashed into the same bin in the hash table. The novelty is that we consider each bin as a coincidence group and mine for frequent patterns, which is a well-studied technique in data mining. We observe that these frequent patterns are already potentially large alignments. Then a simple heuristic is used to extend the alignments if possible. We implemented the algorithm and tested it using real protein structures. The results were compared with existing tools. They showed that the algorithm is capable of finding conserved substructures that do not preserve sequence order, especially those existing in protein interfaces. The algorithm can also identify conserved substructures of functionally similar structures within a mixture with dissimilar ones. The running time of the program was smaller or comparable to that of the existing tools

Towards Practical Homomorphic Time-Lock Puzzles: Applicability and Verifiability

Time-lock puzzle schemes allow one to encrypt messages for the future. More concretely, one can efficiently generate a time-lock puzzle for a secret/solution $s$, such that $s$ remains hidden until a specified time $T$ has elapsed, even for any parallel adversaries. However, since computation on secrets within multiple puzzles can be performed only when \emph{all} of these puzzles are solved, the usage of classical time-lock puzzles is greatly limited. Homomorphic time-lock puzzle (HTLP) schemes were thus proposed to allow evaluating functions over puzzles directly without solving them. However, although efficient HTLP schemes exist, more improvements are still needed for practicability. In this paper, we improve HTLP schemes to broaden their application scenarios from the aspects of \emph{applicability} and \emph{verifiability}. In terms of applicability, we design the \emph{first} multiplicatively HTLP scheme with the solution space over $\mathbb{Z}_n^*$, which is more expressible than the original one, \eg representing integers. Then, to fit HTLP into scenarios requiring verifiability that is missing in existing schemes, we propose three \emph{simple} and \emph{fast} protocols for both the additively HTLP scheme and our multiplicatively HTLP scheme, respectively. The first two protocols allow a puzzle solver to convince others of the correctness of the solution or the invalidity of the puzzle so that others do not need to solve the puzzle themselves. The third protocol allows a puzzle generator to prove the validity of his puzzles. It is shown that a puzzle in our scheme is only $1.25$KB, and one multiplication on puzzles takes simply $0.01$ms. Meanwhile, the overhead of each protocol is less than $0.6$KB in communication and $40$ms in computation. Hence, HTLP still demonstrates excellent efficiency in both communication and computation with these versatile properties

An Intelligent Multiple Sieve Method Based on Genetic Algorithm and Correlation Power Analysis

Correlation power analysis (CPA) is widely used in side-channel attacks on cryptographic devices. Its efficiency mostly depends on the noise produced by the devices. For parallel implementations, the power consumption during the S-box operation contains information of the whole intermediate state. When one S-box is analyzed by CPA, the others are regarded as noise. Apparently, the information of the remained S-boxes not only is wasted, but also increases the complexity of analysis. If two or more S-boxes are considered simultaneously, the complexity of exhaustive search on the corresponding key words grows exponentially. An optimal solution is to process all the S-boxes simultaneously and avoid traversing the whole candidate key space. Simple genetic algorithm was used by Zhang et al. to achieve this purpose. While, premature convergence causes failure in recovering the whole key, especially when plenty large S-boxes are employed in the target primitive, such as AES. In this paper, we study the reason of premature convergence, and propose the multiple sieve method which overcomes it and reduces the number of traces required in correlation power attacks. Operators and the corresponding parameters are chosen experimentally with respect to a parallel implementation of AES-128. Simulation experimental results show that our method reduces the number of traces by $63.7\%$ and $30.77\%$ compared to classic CPA and the simple genetic algorithm based CPA (SGA-CPA) respectively when the success rate is fixed to $90\%$. Real experiments performed on SAKURA-G confirm that the number of traces required to recover the correct key in our method is almost equal to the minimum number that makes the correlation coefficients of correct keys outstanding from the wrong ones, and is much less than classic CPA and SGA-CPA

Improved Zero-Knowledge Argument of Encrypted Extended Permutation

Extended permutation (EP) is a generalized notion of the standard permutation. Unlike the one-to-one correspondence mapping of the standard permutation, EP allows to replicate or omit elements as many times as needed during the mapping. EP is useful in the area of secure multi-party computation (MPC), especially for the problem of private function evaluation (PFE). As a special class of MPC problems, PFE focuses on the scenario where a party holds a private circuit $C$ while all other parties hold their private inputs $x_1, \ldots, x_n$, respectively. The goal of PFE protocols is to securely compute the evaluation result $C(x_1, \ldots, x_n)$, while any other information beyond $C(x_1, \ldots, x_n)$ is hidden. EP here is introduced to describe the topological structure of the circuit $C$, and it is further used to support the evaluation of $C$ privately. For an actively secure PFE protocol, it is crucial to guarantee that the private circuit provider cannot deviate from the protocol to learn more information. Hence, we need to ensure that the private circuit provider correctly performs an EP. This seeks the help of the so-called \emph{zero-knowledge argument of encrypted extended permutation} protocol. In this paper, we provide an improvement of this protocol. Our new protocol can be instantiated to be non-interactive while the previous protocol should be interactive. Meanwhile, compared with the previous protocol, our protocol is significantly (\eg more than $3.4\times$) faster, and the communication cost is only around $24\%$ of that of the previous one

Making Private Function Evaluation Safer, Faster, and Simpler

In the problem of two-party \emph{private function evaluation} (PFE), one party $P_A$ holds a \emph{private function} $f$ and (optionally) a private input $x_A$, while the other party $P_B$ possesses a private input $x_B$. Their goal is to evaluate $f$ on $x_A$ and $x_B$, and one or both parties may obtain the evaluation result $f(x_A, x_B)$ while no other information beyond $f(x_A, x_B)$ is revealed. In this paper, we revisit the two-party PFE problem and provide several enhancements. We propose the \emph{first} constant-round actively secure PFE protocol with linear complexity. Based on this result, we further provide the \emph{first} constant-round publicly verifiable covertly (PVC) secure PFE protocol with linear complexity to gain better efficiency. For instance, when the deterrence factor is $\epsilon = 1/2$, compared to the passively secure protocol, its communication cost is very close and its computation cost is around $2.6\times$. In our constructions, as a by-product, we design a specific protocol for proving that a list of ElGamal ciphertexts is derived from an \emph{extended permutation} performed on a given list of elements. It should be noted that this protocol greatly improves the previous result and may be of independent interest. In addition, a reusability property is added to our two PFE protocols. Namely, if the same function $f$ is involved in multiple executions of the protocol between $P_A$ and $P_B$, then the protocol could be executed more efficiently from the second execution. Moreover, we further extend this property to be \emph{global}, such that it supports multiple executions for the same $f$ in a reusable fashion between $P_A$ and \emph{arbitrary} parties playing the role of $P_B$