On Length Independent Security Bounds for the PMAC Family

At FSE 2017, Gaži et al. demonstrated a pseudorandom function (PRF) distinguisher (Gaži et al., ToSC 2016(2)) on PMAC with Ω(lq2/2n) advantage, where q, l, and n, denote the number of queries, maximum permissible query length (in terms of n-bit blocks), and block size of the underlying block cipher. This, in combination with the upper bounds of Ο(lq2/2n) (Minematsu and Matsushima, FSE 2007) and Ο(qσ/2n) (Nandi and Mandal, J. Mathematical Cryptology 2008(2)), resolved the long-standing problem of exact security of PMAC. Gaži et al. also showed that the dependency on l can be dropped (i.e. O(q2/2n) bound up to l ≤ 2n/2) for a simplified version of PMAC, called sPMAC, by replacing the Gray code-based masking in PMAC with any 4-wise independent universal hash-based masking. Recently, Naito proposed another variant of PMAC with two powering-up maskings (Naito, ToSC 2019(2)) that achieves l-free bound of O(q2/2n), provided l ≤ 2n/2. In this work, we first identify a flaw in the analysis of Naito’s PMAC variant that invalidates the security proof. Apparently, the flaw is not easy to fix under the existing proof setup. We then formulate an equivalent problem which must be solved in order to achieve l-free security bounds for this variant. Second, we show that sPMAC achieves O(q2/2n) bound for a weaker notion of universality as compared to the earlier condition of 4-wise independence. Third, we analyze the security of PMAC1 (a popular variant of PMAC) with a simple modification in the linear combination of block cipher outputs. We show that this simple modification of PMAC1 has tight security O(q2/2n) provided l ≤ 2n/4. Even if l < 2n/4, we still achieve same tight bound as long as total number of blocks in all queries is less than 22n/3.

Examination of Effects of Time Constraint and Task Type on Users’ Query Typing Behaviors

Contextual factors have been found to be an important factor in information searching behaviors, however, little attention has been paid to the influence of contextual factors on users’ query typing behaviors. This study aims to explore the influence of two different contextual factors (with or without time constraint and two kinds of task type) on users’ query typing behaviors. We recruited 40 college students and conducted a user experiment, in which each participant completed two types of search tasks (Fact Finding and Information Understanding) in two different time conditions. The results show that time constraint encourages users to increase their query typing speed. Furthermore, the task type affects query length and rate of keystroke errors.

Scalable Correlated Sampling for Join Query Estimations on Big Data

Estimate query results within limited time constraints is a challenging problem in the research of big data management. Query estimation based on simple random samples per- forms well for simple selection queries; however, return results with extremely high relative errors for complex join queries. Existing methods only work well with foreign key joins, and the sample size can grow dramatically as the dataset gets larger. This research implements a scalable sampling scheme in a big data environment, namely correlated sampling in map-reduce, that can speed up search query length results, give precise join query estimations, and minimize storage costs when presented with big data. Extensive experiments with large TPC-H datasets in Apache Hive show that our sampling method produces fast and accurate query estimations on big data.

Efficient Textual Web Retrieval using Wavelet Tree

Searching on the web is one of the most progressive and expanding field nowadays. A large amount of information is available on the World Wide Web, motivating the need of efficient text indexing method that support fast text retrieval. In the past, two main indexing techniques: Signature files and Inverted files have been proposed. First require much larger space to store index and are more expensive to construct and update than inverted files. Second has been efficiently implemented using different structures like Sorted array and B-Tree. Sorted array was very expensive in updating the indices while appending a new keyword and B-tree method breaks down if there are many words with the same prefix. This paper presents a modified index structure for text retrieval that keeps a good result to optimize the space needed to store and time to search document. The proposed index is designed using the Wavelet Tree (WT), which was originally designed as wavelet transform for images. Experimental results show that on increasing the query length, the WT based index performs better than others.

A BIT-PARALLEL DYNAMIC PROGRAMMING ALGORITHM SUITABLE FOR DNA SEQUENCE ALIGNMENT

Myers' elegant and powerful bit-parallel dynamic programming algorithm for approximate string matching has a restriction that the query length should be within the word size of the computer, typically 64. We propose a modification of Myers' algorithm, in which the modification has a restriction not on the query length but on the maximum number of mismatches (substitutions, insertions, or deletions), which should be less than half of the word size. The time complexity is O(m log |Σ|), where m is the query length and |Σ| is the size of the alphabet Σ. Thus, it is particularly suited for sequences on a small alphabet such as DNA sequences. In particular, it is useful in quickly extending a large number of seed alignments against a reference genome for high-throughput short-read data produced by next-generation DNA sequencers.