Pattern String Matching Algorithm Research Articles

Analysis of SQL Injection Detection and Prevention

Objectives: SQL Injection Attack (SQLIA) is a frequent and a severe security issue in the web applications. In SQLIA, hacker can obtain the benefit of poor input validation and weak coded web application. Due to the successful execution of a SQLIA, integrity and confidentiality of data are lost which results in the degrading organization’s market value. This paper gives a valuable analysis of various types of SQLIAs, methods and mechanisms. It also explores various detection and prevention techniques. Methods/Analysis: A rigorous survey has been conducted and consequently, comparative analysis of various detection and prevention techniques is done with respect to various types of attacks. In current research various pattern matching algorithms for the detection and prevention of SQLIA are analyzed and few are tested. Findings: Comparative analysis of Boyer Moore pattern matching algorithm is done with Naive String pattern matching algorithm. The time and memory consumption taken by both the algorithms has been analyzed. The results show that Boyer Moore is more efficient to detect and prevent the SQLIAs as compared to Naive string. Novelty/Improvement: In future it aims to propose an algorithm which will enhance in terms of efficiency and resource usage. The approach needs to be implemented for every pattern matching algorithm to find the best solution regarding detection and prevention of SQLIA.

A Survey of Automatic Extraction of Personal Name Alias from the Web

The survey paper explains about the extraction and retrieval of personal name alias using various techniques from the web with the help of web crawls. The existing methods help to improve the depth of knowledge relevant to alias extraction and retrieval process. It also describes about how the aliases are ranked, then page counts on the web, word co-occurrence using anchor text and techniques like term frequency (tf), inverse document frequency (idf), log likelihood ratio. Chi-squared tests etc.., are used for measuring the association and similarities between words. The existing method consists of pattern extraction algorithm or string matching algorithm for extracting patterns from snippets instead of using these algorithms. The survey helps to discover a proposed method as graph mining to extract personal name aliases from the web.

정규 표현식을 이용한 패턴 매칭 엔진 개발

스트링 패턴 매칭 알고리즘은 특정 검색어, 키워드를 검색하는 속도에서는 우수성이 다양한 방법으로 입증되었지만 다양한 패턴에 대해서는 기존의 알고리즘으로는 한계를 가지고 있다. 본 논문에서는 정규 표현식을 이용하여 특정 키워드를 포함하여 다양한 패턴의 검색어에 대해서도 효율적인 패턴 매칭을 수행하여 패턴 검색의 효율을 높이고자 한다. 이러한 연구는 기존의 단순한 키워드 매칭에 비해 각종 유해한 스트링 패턴을 효과적으로 검색할 수 있으며 스트링 패턴 매칭 속도에서도 기존의 알고리즘에 비해 우수성을 갖는다. 본 연구에서 제안한 LEX로부터 생성된 스트링 검색 엔진은 패턴 검색 속도에 대한 실험에서 패턴의 수가 1000개 이상인 경우에서는 BM&AC 알고리즘보다 효율적이지만 키워드 검색에서는 유사한 결과를 얻었다. In various manners, string pattern matching algorithm has been proven for prominence in speed of searching particular queries and keywords. Whereas, the existing algorithms are limited in terms of various pattern. In this paper, regular expression has been utilized to improve efficiency of pattern matching through efficient execution towards various pattern of queries including particular keywords. Such as this research would enable to search various harmful string pattern more efficiently, rather than matching simple keywords, which also implies excellent speed of string pattern matching compared to that of those existing algorism. In this research, the proposed string search engine generated from the LEX are more efficient than BM & AC algorithm for a string patterns search speed in cases of 1000 with more than patterns, but we have got similar results for the keywords pattern matching.

A method of reduction e-mails using replacement and repression

E-mail systems are one of the most useful communication tools for business, education, etc., but missing e-mail information becomes a very serious problem. Therefore, it is important to retrieve the meaning of messages efficiently, that is to say, finding important portions from messages by changing pages are inefficient actions. This paper presents a method of reducing messages by keeping the meaning of massages. This solution is useful for small size devices such as PDA, handy phones and so on. The presented method defines replacement and repression patterns, but the text's meaning is sometimes altered. In order to solve this problem, this paper introduces a meaning distortion rate and the criterion of reducing texts uniformly. For the real time process, an extension of a string pattern-matching algorithm is discussed. From the simulation results by using reduction knowledge with 15,000 patterns for e-mail, it turns out that the rate of reducing texts by the presented method is about 75%, the rate of keeping meanings of the original messages is 95% and the time of processing one mail becomes 0.1 ms.

A new string-pattern matching algorithm using partitioning and hashing efficiently

In this paper, we present a new string-pattern matching algorithm that partitions the text into segments of the input pattern length and searches for pattern occurrences using a simple hashing scheme. Unlike the well known Boyer-Moore style algorithm, our algorithm does not compute variable shift length, thus providing a conceptually simpler way to search for patterns. Empirical evaluation shows that our algorithm runs significantly faster than Sunday's and Horspool's extensions of the Boyer-Moore algorithm. The notion of the non-occurrence heuristic used in our algorithm, together with a text partitioning scheme, leads to a simplified scheme for searching for pattern occurrences, thus yielding better run time performance.

A method for the expansion and contraction of text's size by using the string replacement algorithm

This paper describes a method for the expansion of the size of texts using an efficient string replacement algorithm. A method for the expansion of the size of texts by use of morpheme replacements is supported by the rules for expansion morphemes. This paper explains the text expansion method using the example of text reduction. Morpheme replacements are defined as a combination of a pattern of categories and restrictions on morphemes. A replaceable pattern is efficiently detected through an extension of Aho's string pattern-matching algorithm. This extension consists of the application of a matching algorithm that replaces the input morpheme. Results of simulations upon several texts show that reduced texts are between 5% and 10% shorter than their original counterparts. Also, by use of this pattern-matching algorithm for detection of the suitable reducing rules, the number of state translations can be reduced to 1 7 of that when using Aho's pattern-matching algorithm.

A string pattern—matching algorithm

A string pattern-matching algorithm uses a character string, pattern, to search another character string, text, for the first or all occurrence(s) of the pattern in the text. This article presents a string patternmatching algorithm using a mapping table and an automaton. The number of states of the automaton is equal to the length of the pattern and its number of inputs is one more than the number of different characters in the pattern. During the search, when a mismatch occurs between a pattern character and a text character, the jump to the next position for comparison is made optimal based on the information in the automaton. For non case-sensitive pattern matching, the translation of cases is all done in the mapping table in linear time of the sum of the pattern length and the size of the alphabet; the search part does not do any translation. Experimental results confirm that the ratio of the number of characters inspected over the number of characters passed is better than that of the Boyer-Moore algorithm. The search loop is also very simple and machine independent. Therefore, the algorithm should appeal to anyone who needs a universal search routine that does not depend on statistics of characters.