SWiM: Secure Wildcard Pattern Matching from OT Extension

We propose a protocol for the problem of secure two-party pattern matching, where Alice holds a text t?{0,1}? of length n, while Bob has a pattern p?{0,1}? of length m. The goal is for Bob to (only) learn where his pattern occurs in Alice's text, while Alice learns nothing. Private pattern matching is an important problem that has many applications in the area of DNA search, computational biology and more. Our construction guarantees full simulation in the presence of malicious, polynomial-time adversaries (assuming the hardness of DDH assumption) and exhibits computation and communication costs of O(n+m) group elements in a constant round complexity. This improves over previous work by Gennaro et al. (Public Key Cryptography, pp. 145---160, 2010) whose solution requires overhead of O(nm) group elements and exponentiations in O(m) rounds. In addition to the above, we propose a collection of protocols for important variations of the secure pattern matching problem that are significantly more efficient than the current state of art solutions: First, we deal with secure pattern matching with wildcards. In this variant the pattern may contain wildcards that match both 0 and 1. Our protocol requires O(n+m) communication and O(1) rounds using O(nm) computation. Then we treat secure approximate pattern matching. In this variant the matches may be approximated, i.e., have Hamming distance less than some threshold, ?. Our protocol requires O(n?) communication in O(1) rounds using O(nm) computation. Third, we have secure pattern matching with hidden pattern length. Here, the length, m, of Bob's pattern remains a secret. Our protocol requires O(n+M) communication in O(1) rounds using O(n+M) computation, where M is an upper bound on m. Finally, we have secure pattern matching with hidden text length. Finally, in this variant the length, n, of Alice's text remains a secret. Our protocol requires O(N+m) communication in O(1) rounds using O(N+m) computation, where N is an upper bound on n.

Efficient protocols for private wildcards pattern matching

We propose a dedicated protocol for the highly motivated problem of secure two-party pattern matching: Alice holds a text t ∈ {0,1}*. of length n, while Bob has a pattern p ∈ {0,1}*. of length m. The goal is for Bob to learn where his pattern occurs in Alice’s text. Our construction guarantees full simulation in the presence of malicious, polynomial-time adversaries (assuming that ElGamal encryption is semantically secure) and exhibits computation and communication costs of O(n + m) in a constant round complexity. In addition to the above, we propose a collection of protocols for variations of the secure pattern matching problem: The pattern may contain wildcards (O(nm) communication in O(1) rounds). The matches may be approximated, i.e., Hamming distance less than some threshold ((O(nm) communication in O(1) rounds). The length, m, of Bob’s pattern is secret (O(nm) communication in O(1) rounds). The length, n, of Alice’s text is secret (O(n + m) communication in O(1) rounds).

Given two strings: pattern $p$ of length $m$ and text $t$ of length $n$ . The string matching problem is to find all (or some) occurrences of the pattern $p$ in the text $t$ . We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.

Pattern Matching with Swaps

With the continuous development of the Internet of Things (IoT), various IoT devices create an incomprehensible amount of data all the time. However, the IoT devices have limited computing and storage resources and are difficult to process massive data locally, so they often introduce servers to help them for calculating or analyzing data. At present, the “IoT + Cloud” mode has been widely accepted. How to protect users’ privacy in the public cloud environment has become critical. Among the common methods of processing data in the server, pattern matching is an important one which aims to identify the appearance and location of a string (called pattern) within a larger string or text. There are a lot of studies on privacy-preserving pattern matching protocols, but most protocols are constructed using heavy public-key cryptographic operations, which are not applicable to IoT devices. In this paper, we propose a new protocol using secret sharing and oblivious transfer (OT) and latter improve its efficiency with OT extension, so it is very efficient for lightweight IoT devices. In addition, our protocol also supports query with wildcards which can be used for the batch search. This protocol is provable-secure against honest-but-curious adversaries. Both the theoretical and experimental results show that our protocol can be used in real-world IoT applications.

Methods for text segmentation from scene images

Intrusion Detection System has become the important part of the computer and network security because it can effectively compensate for the lack of network security measures. However, the intrusion detection technology relies heavily on pattern matching algorithms, as the choice of pattern matching algorithms directly affect the detection rate, so it is more important. First the paper is detailed analysis the characteristics of the four kinds of single pattern matching which based on prefix search, and then it tests by the number of different pattern strings. The experimental results show that the KMP algorithm can improve effectively the speed of pattern matching. So the application of KMP algorithm can improve the efficiency of intrusion detection.

The Pattern Matching problem with Swaps consists in finding all occurrences of a pattern P in a text T, when disjoint local swaps in the pattern are allowed. In the Approximate Pattern Matching problem with Swaps one seeks, for every text location with a swapped match of P, the number of swaps necessary to obtain a match at the location. In this paper we devise two general algorithms for both Standard and Approximate Pattern Matching with Swaps, named CROSS-SAMPLING and BACKWARD-CROSS-SAMPLING, with a [Formula: see text] and [Formula: see text] worst-case time complexity, respectively. Then we provide efficient implementations of them, based on bit-parallelism, which achieve [Formula: see text] and [Formula: see text] worst-case time complexity, with patterns whose length is comparable to the word-size of the target machine. From an extensive comparison with some of the most effective algorithms for the swap matching problem, it turns out that our algorithms are very flexible and achieve very good results inpractice.

We present a new backward tree pattern matching algorithm for ordered trees. The algorithm finds all occurrences of a single given tree pattern which match an input tree. It makes use of linearisations of both the given pattern and the input tree. The algorithm preserves the properties and advantages of standard backward string pattern matching approaches. The number of symbol comparisons in the backward tree pattern matching can be sublinear in the size of the input tree. As in the case of backward string pattern matching, the size of the bad character shift table used by the algorithm is linear in the size of the alphabet. We compare the new algorithm with best performing previously existing algorithms based on (non-linearised) tree pattern matching using finite tree automata or stringpath matchers and show that it outperforms these for single pattern matching.

A practical method for implementing string pattern matching machines

The problem of finding all approximate occurrences P′ of a pattern string P in a text string T such that the edit distance between P and P′ is ≤k is considered. We concentrate on a scheme in which T is first preprocessed to make the subsequent searches with different P fast. Two preprocessing methods and the corresponding search algorithms are described. The first is based suffix automata and is applicable for edit distances with general edit operation costs. The second is a special design for unit cost edit distance and is based on q-gram lists. The preprocessing needs in both cases time and space O(|T|). The search algorithms run in the worst case in time O(|P||T|) or O(k|T|), and in the best case in time O(|P|).

Alphabet dependence in parameterized matching

Secure wildcard pattern matching (WPM) allows the pattern holder to obtain the matched positions without revealing pattern and text information about both parties. However, standard secure WPM may have limitations in practical applications, as users may prefer to have access to the actual data of the match in many scenarios. Fortunately, secure wildcard pattern matching with query (SWMQ) extends standard secure WPM by allowing the pattern holder to obtain the matched positions and the actual data, which has important applications in many scenarios, such as electronic healthcare and gene matching. This also motivates the research of SWMQ in this paper. In this study, we focus on the efficient construction of SWMQ in the semihonest adversary setting. First, we propose two new primitives, hereafter referred to as shared wildcard pattern matching (Sh-WPM) and choice-sharing oblivious transfer (CSOT). Furthermore, we propose an SWMQ protocol via Shared WPM and CSOT. In addition, we evaluate the performance of SWMQ. More specifically, the running time in local area network and wide area network settings is less than 0.4 and 2 s, respectively, when the text length is 2 16 ${2}^{16}$ and the pattern length is 2 12 ${2}^{12}$ . In fact, our evaluation results suggest that SWMQ is not only more broadly functional, but also comparable in efficiency to state-of-the-art approaches.

Generation of Pattern-Matching Algorithms by Extended Regular Expressions