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

Structural Identity-Based Encryption

In this paper, we introduce the concept of structural identity-based encryption (SIBE). Similar to hierarchical identity-based encryption (HIBE), entities in the system are organized into hierarchy. An entity in SIBE can decrypt ciphertext for all its ancestors. It can be seen as an opposite of HIBE, where an entity can decrypt the ciphertext for all its descendants. We formalize the notion and security requirements, propose an efficient construction and show that our construction is secure under appropriate assumptions in the random oracle model

Exclusion-Intersection Encryption

Identity-based encryption (IBE) has shown to be a useful cryptographic scheme enabling secure yet flexible role-based access control. We propose a new variant of IBE named as exclusion-intersection encryption: during encryption, the sender can specify the targeted groups that are legitimate and interested in reading the documents; there exists a trusted key generation centre generating the intersection private decryption keys on request. This special private key can only be used to decrypt the ciphertext which is of all the specified groups\u27 interests, its holders are excluded from decrypting when the documents are not targeted to all these groups (e.g., the ciphertext of only a single group\u27s interest). While recent advances in cryptographic techniques (e.g., attribute-based encryption or wicked IBE) can support a more general access control policy, the private key size may be as long as the number of attributes or identifiers that can be specified in a ciphertext, which is undesirable, especially when each user may receive a number of such keys for different decryption power. One of the applications of our notion is to support an ad-hoc joint project of two or more groups which needs extra helpers that are not from any particular group. We also present an online/offline variant such that encryption can be computed quickly after offline pre-computation

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

Practical Attribute Based Inner Product Functional Encryption from Simple Assumptions

Functional encryption (FE) that bases on user attributes has many useful practical applications. For example, a company may only authorize department heads of other sections to query the average sale figures of the sales department from the encrypted sales amounts of all sales. However, FE schemes that can solve this problem are based on new, but not well-studied assumptions (such as indistinguishable obfuscation or multilinear maps). It is not clear if these FE schemes are secure. In this paper, we develop the first functional encryption scheme (ABFE) from simple and well-studied assumptions that can authorize a user base on the user\u27s attributes to obtain a functional value of the encrypted data