Exact String Matching Algorithm Research Articles

Homomorphic encrypted Yara rules evaluation

Malware signatures represent a powerful tool for malware detection and classification, widely used by security researchers and security solution providers. Yara rules describe malware based on string patterns that are evaluated on targeted files. Generally, the security provider sends signatures to the client endpoints and the rule evaluation is performed locally, such that the scanned files do not leave the client machines. However, if a zero-day vulnerability is discovered and the security provider exposes the corresponding signature, there is a considerable risk to also disclose the unpatched vulnerability. A solution is represented by homomorphic encrypted Yara rules, which can be evaluated on targeted files without being decrypted. In this article, we propose a homomorphic Yara rules evaluation method and do a comparative analysis with the HENFA method (Homomorphic Encryption for Finite Automata (Genise et al., 2019)). For our method, we propose a fully homomorphic exact string matching algorithm based on the TFHE scheme (Fully Homomorphic Encryption over the Torus (Chillotti et al., 2020)). In order to determine how suitable is the exact string matching approach in practice, we analyze a public Yara rules repository and generate various statistics about the patterns used in the Yara rules. For the two homomorphic Yara rules matching methods, both theoretical and experimental comparative evaluations are presented. Our proposed method implies ciphertexts with smaller sizes and has better efficiency in the average testing scenarios compared to the HENFA method.

Parallel processing of E-Atheer algorithm using pthread paradigm

The development in the field of computer technology, and the increase in the growth rate of database, alongside the extraction of certain data from a huge pool of database involve intricate and complex processes. The processes comprise text mining, pattern recognition, retrieval of information and text processing. Thus, the need for enhancing the performance of string matching algorithms is required, which is considered as one of the challenges to the researchers. Consequently, one of the resolution to address this problem is the parallelization for exact string matching algorithms. In this study, we implemented the parallel exact string matching algorithm termed as E-Atheer with multi-core processing utilizing Pthread (POSIX) for the reduction of time consumption. The Pitch, XML, Protein, and DNA database types are utilized to test the impact of the proposed parallel algorithm. The parallelization algorithm obtained positive results in the parallel execution time, and a more superior expediting capabilities, in comparison to the sequential result. The Pitch database indicated optimal results in parallel execution time, and when utilizing long and short pattern lengths. The DNA database indicated optimal speedup performance when utilizing short and long pattern length, meanwhile the XML and Protein on the other hand indicated the worst results.

On the Complexity of String Matching for Graphs

Exact string matching in labeled graphs is the problem of searching paths of a graph G=(V, E) such that the concatenation of their node labels is equal to a given pattern string P [1. m ]. This basic problem can be found at the heart of more complex operations on variation graphs in computational biology, of query operations in graph databases, and of analysis operations in heterogeneous networks. We prove a conditional lower bound stating that, for any constant ε > 0, an O (| E | 1 - ε m ) time, or an O (| E | m 1 - ε )time algorithm for exact string matching in graphs, with node labels and pattern drawn from a binary alphabet, cannot be achieved unless the Strong Exponential Time Hypothesis ( SETH ) is false. This holds even if restricted to undirected graphs with maximum node degree 2—that is, to zig-zag matching in bidirectional strings , or to deterministic directed acyclic graphs whose nodes have maximum sum of indegree and outdegree 3. These restricted cases make the lower bound stricter than what can be directly derived from related bounds on regular expression matching (Backurs and Indyk, FOCS’16). In fact, our bounds are tight in the sense that lowering the degree or the alphabet size yields linear time solvable problems. An interesting corollary is that exact and approximate matching are equally hard (i.e., quadratic time) in graphs under SETH . In comparison, the same problems restricted to strings have linear time vs quadratic time solutions, respectively (approximate pattern matching having also a matching SETH lower bound (Backurs and Indyk, STOC’15)).

Finding Experts in Community Question Answering System Using Trie String Matching Algorithm with Domain Knowledge

In recent days, different community question-answering systems have been evolving as online forums for knowledge sharing among users across the world. However, finding experts on the questions is a key issue in the community question-answering system. To address this issue, a novel approach is proposed in this paper for finding experts from the community question-answering website using an exact string-matching algorithm along with domain knowledge. The proposed system is designed with three phases: i) User Profile Modeling, ii) Question Preprocessing, and iii) Expert Recommendation. Initially, the matrix factorization model is adopted for user profile modeling where the tags and the answerer’s information are represented in the form of a matrix. Then, the domain-wise grouping of tags is done to minimize the search time of the tags. The question preprocessing is done using a keyword extraction algorithm to extract the keywords. Finally, the expert recommendation is accomplished using the trie string matching algorithm and key-value mapping process. For doing experiments, a stack overflow community question-answering website is utilized in this work. The performance of the system is measured and the results section proved that the system achieved 91.2% accuracy.

PARALLEL PROCESSING OUTCOMES OF E-ABDULRAZZAQ ALGORITHM USING MULTI-CORE TECHNIQUE

The string matching problem is considered one of the substantial problems in the fields of computer science like speech and pattern recognition, signal and image processing, and artificial intelligence (AI). The increase in the speedup of performance is considered an important factor in meeting the growth rate of databases, Subsequently, one of the determinations to address this issue is the parallelization for exact string matching algorithms. In this study, the E-Abdulrazzaq string matching algorithm is chosen to be executed with the multi-core environment utilizing the OpenMP paradigm which can be utilized to decrease the execution time and increase the speedup of the algorithm. The parallelization algorithm got positive results within the parallel execution time, and excellent speeding-up capabilities, in comparison to the successive result. The Protein database showed optimal results in parallel execution time, and when utilizing short and long pattern lengths. The DNA database showed optimal speedup execution when utilizing short and long pattern lengths, while no specific database obtained the worst results.

Multiple exact string matching algorithm based on q-gram hash comparison for DNA sequences

Dizi eşleştirme algoritmaları tıp, biyoinformatik, biyoloji gibi birçok alandaki çeşitli uygulamaları nedeniyle bilgisayar bilimindeki önemli çalışma konularından olmuştur. Son yıllarda yeni algoritmalar geliştirilerek metin üzerinde dizi eşleştirme işlemleri hızlandırılmıştır. Dizi eşleştirme algoritmaları tekli ve çoklu olmak üzere iki kısma ayrılır. Çoklu kesin dizi eşleştirme algoritmaları verilen bir T metni içinde d adet P desenlerinin bulunmasını içerir. Bu çalışmada, hash tabanlı çoklu kesin dizi eşleştirme algoritmalarından olan Wu-Manber algoritması ele alınmıştır. Wu-Manber algoritması etkili bir algoritma olmasına rağmen hash çakışmaları gibi bazı kısıtlamalara sahiptir. Çalışmamızda bu eksikliklere yönelik yeni yaklaşım önerilmiştir. Önerilen yaklaşımda, geleneksel Wu-Manber algoritmasının aksine, DNA sekanslarında hash çakışmasını kaldıran hash fonksiyonu kullanarak dizilerdeki arama işlemi q-gram hash karşılaştırması ile gerçekleştirilmiştir. Önerilen yaklaşım literatürde sıkça kullanılan çoklu kesin dizi eşleştirme algoritmalarıyla E. Coli ve Human Chromosome1 veri setinde karşılaştırmalar yapılmıştır. Yapılan deneysel çalışmalar sonucu önerilen yöntemin Wu-Manber algoritmasına kıyasla önerilen yaklaşımda ortalama çalışma zamanı, ortalama karakter ve hash karşılaştırma sayısı gibi performans metrikleri açısından daha iyi sonuçlar elde edilmiştir. Ayrıca, önerilen yaklaşımın Aho Corasick (AC) ve Commentz Walter (CW) gibi iyi bilinen algoritmalardan daha verimli olduğu gösterilmiştir.

Similarity Identification Based on Word Trigrams Using Exact String Matching Algorithms

Several studies regarding excellent exact string matching algorithms can be used to identify similarity, including the Rabin-Karp, Winnowing, and Horspool Boyer-Moore algorithms. In determining similarities, the Rabin-Karp and Winnowing algorithms use fingerprints, while the Horspool Boyer-Moore algorithm uses a bad-character table. However, previous research focused on identifying similarities using these algorithms based on character n-gram. In contrast, identification based on the word n-gram to determine the similarity based on its linguistic meaning, especially for longer strings, had not been covered yet. Therefore, a word-level trigram was proposed to identify similarities based on the word trigrams using the three algorithms and compare each performance. Based on precision, recall, and running time comparison, the Rabin-Karp algorithm results were 100%, 100%, and 0.19 ms, respectively; the Winnowing algorithm results with the smallest window were 100%, 56%, and 0.18 ms, respectively; and the Horspool algorithm results were 100%, 100%, and 0.06 ms. From these results, it can be concluded that the performance of the Horspool Boyer-Moore algorithm is better in terms of precision, recall, and running time.

Q‐frame hash comparison based exact string matching algorithms for DNA sequences

AbstractThe importance of string matching is due to its applications in many fields, such as medicine and bioinformatics. Various string matching algorithms are developed to speed up the search. Especially, hash‐based exact string matching algorithms are among the most time‐efficient ones. The efficiency of hash‐based approaches depends on the hash function. Hence, perfect hashing plays an essential role in hash‐based string matching. In this study, two q‐frame hash comparison‐based exact string matching algorithms, Hq‐QF and HqBM‐QF, are proposed. We have used a collision‐free perfect hash function for DNA sequences in the proposed algorithms. In the first approach, after hash values match for the last qcharacters, the character comparisons in the Hash‐q algorithm are replaced with q‐frame hash comparison. In the second approach, we improved the first approach by utilizing the shift size indicated at the th entry in the good suffix shift table. Since the number of character comparisons is minimized, the worst‐case time complexity of the proposed algorithms is . In both approaches, q‐frame hash comparisons replace most character comparisons as a trade‐off. The results show that the proposed approaches are more efficient than the Hash‐q algorithm in terms of runtime efficiency and the number of character comparisons.

The WM-q multiple exact string matching algorithm for DNA sequences

The string matching algorithms are among the essential fields in computer science, such as text search, intrusion detection systems, fraud detection, sequence search in bioinformatics. The exact string matching algorithms are divided into two parts: single and multiple. Multiple string matching algorithms involve finding elements of the pattern set P in a given input text T. String matching processes should be done in a time-efficient manner for DNA sequences. As the volume of the text T increases and the number of search patterns increases, the total runtime increases. Efficient algorithms should be selected to perform these search operations as soon as possible. In this study, the Wu-Manber algorithm, one of the multiple exact string matching algorithms, is improved. Although the Wu-Manber algorithm is effective, it has some limitations, such as hash collisions. In this study, the WM-q algorithm, a version of the Wu-Manber algorithm based on the perfect hash function for DNA sequences, is proposed. String matching is performed using different block lengths provided by the perfect hash function instead of using the fixed block length as in the traditional Wu-Manber algorithm. The proposed approach has been compared with E. Coli and Human Chromosome1 datasets, frequently used in the literature, using multiple exact string matching algorithms. The proposed algorithm gives better results for performance metrics such as the average runtime, the average number of characters and hash comparisons.

Improving hash-q exact string matching algorithm with perfect hashing for DNA sequences

Exact string matching algorithms involve finding all occurrences of a pattern P in a text T. These algorithms have been extensively studied in computer science, primarily because of their applications in various fields such as text search and computational biology. The main goal of exact string matching algorithms is to find all pattern matches correctly within the shortest possible time frame. Although hash-based string matching algorithms run fast, there are shortcomings, such as hash collisions. In this study, a novel hash function has been proposed that eliminates hash collisions for DNA sequences. It provides us perfect hashing and produces hash values in a time-efficient manner. We have proposed two exact string matching algorithms based on the proposed hash function. In the first approach, we replace the traditional Hash-q algorithm's hash function with the proposed one. In the second approach, we improved the first approach by utilizing the shift size indicated at the (m−1)th entry in the good suffix shift table when an exact matching is found. In these approaches, we eliminate the need to compare the last q characters of the pattern and text. We have included six algorithms from the literature in our evaluations. E. Coli and Human Chromosome1 datasets from the literature and a synthetic dataset produced randomly are utilized for comparisons. The results show that the proposed approaches achieve better performance metrics in terms of the average runtime, the average number of character comparisons, and the average number of hash comparisons.

Parallel Scalable Approximate Matching Algorithm for Network Intrusion Detection Systems

Matching algorithms are working to find the exact or the approximate matching between text “T” and pattern “P”, due to the development of a computer processor, which currently contains a set of multi-cores, multitasks can be performed simultaneously. This technology makes these algorithms work in parallel to improve their speed matching performance. Several exact string matching and approximate matching algorithms have been developed to work in parallel to find the correspondence between text “T” and pattern “P”. This paper proposed two models: First, parallelized the Direct Matching Algorithm (PDMA) in multi-cores architecture using OpenMP technology. Second, the PDMA implemented in Network Intrusion Detection Systems (NIDS) to enhance the speed of the NIDS detection engine. The PDMA can be achieved more than 19.7% in parallel processing time compared with sequential matching processing. In addition, the performance of the NIDS detection engine improved for more than 8% compared to the current SNORT-NIDS detection engine

CDKAM: a taxonomic classification tool using discriminative k-mers and approximate matching strategies

BackgroundCurrent taxonomic classification tools use exact string matching algorithms that are effective to tackle the data from the next generation sequencing technology. However, the unique error patterns in the third generation sequencing (TGS) technologies could reduce the accuracy of these programs.ResultsWe developed a Classification tool using Discriminative K-mers and Approximate Matching algorithm (CDKAM). This approximate matching method was used for searching k-mers, which included two phases, a quick mapping phase and a dynamic programming phase. Simulated datasets as well as real TGS datasets have been tested to compare the performance of CDKAM with existing methods. We showed that CDKAM performed better in many aspects, especially when classifying TGS data with average length 1000–1500 bases.ConclusionsCDKAM is an effective program with higher accuracy and lower memory requirement for TGS metagenome sequence classification. It produces a high species-level accuracy.

Fast algorithms for single and multiple pattern Cartesian tree matching

Cartesian tree matching is the problem of finding every substring of a given text which has the same Cartesian tree as that of a given pattern. In this paper we propose fast algorithms for single and multiple pattern Cartesian tree matching by introducing new representations and encodings. For single pattern Cartesian tree matching, we present the framework of a binary filtration method and an efficient verification technique. Any exact string matching algorithm can be used as a filtration for Cartesian tree matching in our framework. For multiple pattern Cartesian tree matching, we present two fingerprinting methods, i.e., the parent-distance encoding and the binary encoding. By combining an efficient fingerprinting method and a conventional multiple string matching algorithm, we can efficiently solve multiple pattern Cartesian tree matching. By experiments we show that our matching algorithms provide good performances for both single and multiple pattern Cartesian tree matching.

Implementasi Algoritma Raita Pada Aplikasi Hukum Kanonik Berbasis Mobile

Canonical law is an internal church law governing the Catholic Church, Eastern Orthodox Church, Eastern Orthodox Church, Anglican Communion. How the laws of the church are governed, interpreted and sometimes examined differ fundamentally between the three church bodies. in all three traditions, a canon was originally a rule accepted by an assembly, these canons formed the basis for canon law. Raita algorithm is part of the exact string matching algorithm, which is matching the string exactly with the arrangement of characters in the matched string that has the same number or sequence of characters in the string. Matching strings on the raita algorithm is done through a shift from the right of the character then to the left of the character and to the middle of the character. The problem in this research is the content of canon law in general consists of a very large number of pages of books, this makes it difficult for canonical law users to find the contents needed, then in the search it takes time to find the contents of canonical law that are searched for too many search problems. that is, too much time must be needed to find the contents of the canonical law sought

Analysis of medication patterns for pediatric asthma patients in emergency department: Does the sequence placement of glucocorticoids administration matter?

Objectives: Timely glucocorticoid administration is associated with decreased admission rate and is thus a common quality metric for ED asthma care; less is known about the impact of the timing of glucocorticoids in the context of the sequence of asthma medications administered. Therefore, we investigated the distribution of asthma medication sequences in one ED and analyzed the effect of the sequence placement of glucocorticoids administration on treatment outcomes.Methods: A retrospective study using five-year electronic health record data obtained from an academic urban children’s hospital ED was conducted. We clustered the sequences of medication administration using an exact string-matching algorithm to identify the most frequently used asthma medication sequences. Then, we used the identified patterns to perform statistical tests to examine the effect of the sequence placement of glucocorticoids administration on the outcomes length-of-stay and ED disposition.Results: A total of 4,844 encounters were included in our study. The ten most common treatment sequences accounted for 43% of all encounters. Stratified analyses confirmed that treatment sequences pattern was correlated with patient severity, but ED crowding does not impact treatment sequences. In multivariable models, glucocorticoids administration earlier in the treatment sequence was associated with shorter length of stay and lower hospital admission rates.Conclusions: By analyzing medication sequence patterns for the ED encounter of pediatric asthma, we found that the earlier sequence placement of glucocorticoids administration is associated with improved outcomes. Our findings can help inform quality improvement and clinical guideline development related to ED asthma care for children.

Analisa Algoritma Raita pada Automatic Hyperlink

Today the development of technology is very rapidly developing which affects various aspects of life. The development of these technologies takes on several important roles such as business, organizational structure and organizational management. The website is a form of information technology development that presents information needed by all people in carrying out their activities such as business, social, and others. Hyperlink is a way that is used to connect a part of a website in the form of files, documents, images or so on. Arranging the appearance of interfaces that are user friendly from a website is important because if a website has so many menus, it will be difficult for someone to move from one page to another. If the menu presentation is not appropriate then indirectly it will reduce user friendly value. One way that can be done is to apply automatic hyperlinks, namely if an information that is conveyed on a page contains words that match the other information pages, it will automatically make the word into a menu. To be able to apply the automatic hyperlink, an algorithm is needed to find the words contained in a paragraph, one of the algorithms that can be used is the Raita algorithm. Raita algorithm is part of the exact string matching algorithm, which is to match the string correctly with the arrangement of characters in a matched string that has the number or sequence of characters in the same string.

SIMD Implementation of the Aho-Corasick Algorithm using Intel AVX2

The Aho-Corasick (AC) algorithm is a multiple pattern exact string-matching algorithm proposed by Alfred V. Aho and Margaret J. Corasick. It is used to locate all occurrences of a finite set of patterns within an input text simultaneously. The AC algorithm is in the heart of many applications including digital forensics such as digital signatures demonstrating the authenticity of a digital message or document, full text search (utility programs such as grep, awk and sed of Unix systems), information retrieval (biological sequence analysis and gene identification), intrusion detection systems (IDS) in computer networks like SNORT, web filtering, spam filters, and antimalware solutions (virus scanner). In this paper we present a vectorized version of the AC algorithm designed with the use of packed instructions based on the Intel streaming SIMD (Single Instruction Multiple Data) extensions AVX2 (Advanced Vector Extensions 2.0) technology. This paper shows that the vectorized AC algorithm reduces significantly the time matching process comparing to the implementation of the original AC algorithm.

Exact String Matching Algorithms: Survey, Issues, and Future Research Directions

String matching has been an extensively studied research domain in the past two decades due to its various applications in the fields of text, image, signal, and speech processing. As a result, choosing an appropriate string matching algorithm for current applications and addressing challenges is difficult. Understanding different string matching approaches (such as exact string matching and approximate string matching algorithms), integrating several algorithms, and modifying algorithms to address related issues are also difficult. This paper presents a survey on single-pattern exact string matching algorithms. The main purpose of this survey is to propose new classification, identify new directions and highlight the possible challenges, current trends, and future works in the area of string matching algorithms with a core focus on exact string matching algorithms.

Average time complexity analysis of Commentz-Walter algorithm

The Commentz-Walter algorithm provides a suffix-based, exact multiple string matching procedure that combines the ideas of both Aho-Corasick and Boyer-Moore string matching algorithms. Aho-Corasick algorithm is known as the fastest exact multiple string matching algorithm with linear worst case time complexity, and Boyer-Moore algorithm utilises a shift based approach in handling mismatches in the matching phase to obtain a usually sub linear time complexity. Due to the complexity of the Commentz-Walter algorithm, a systematic and a comprehensive time complexity analysis has not yet been reported in the literature. In this article, a comprehensive average time complexity analysis of Commentz Walter algorithm is presented and it is used to formally explain empirical results reported elsewhere for exact and limited tolerance string matching. Performance analysis model permits ‘complete’ exploration of the solution space of Commentz-Walter with respect to all relevant parameters. The models developed here could be useful for other researchers to investigate the appropriateness of Commentz-Walter to specific application domains. The analysis method can be extended to cover Aho-Corasick and other string matching algorithms without much difficulty.

Parallelizing Exact and Approximate String Matching via Inclusive Scan on a GPU

In this study, to substantially improve the runtimes of exact and approximate string matching algorithms, we propose a tribrid parallel method for bit-parallel algorithms such as the Shift-Or and Wu-Manber algorithms. Our underlying idea is to interpret bit-parallel algorithms as inclusive-scan operations, which allow these bit-parallel algorithms to run efficiently on a graphics processing unit (GPU); we achieve this speed-up here because inclusive-scan operations not only eliminate duplicate searches between threads but also realize a GPU-friendly memory access pattern that maximizes memory read/write throughput. To realize our ideas, we first define two binary operators and then present a proof regarding the associativity of these operators, which is necessary for the parallelization of the inclusive-scan operations. Finally, we integrate the inclusive-scan scheme into a previous segmentation-based scheme to maximize search throughput, identifying the best tradeoff point between synchronization cost and duplicate work. Through our experiments, we compared our proposed method with previous segmentation-based methods and indexing-based sequence aligners. For online string matching, our proposed method performed 6.7-16.7 times faster than previous methods, achieving a search throughput of up to 1.88 terabits per second (Tbps) on a GeForce GTX TITAN X GPU. We therefore conclude that our proposed method is quite effective for decreasing the runtimes of online string matching of short patterns.