Fuzzy Regular Expressions Research Articles

Multifamily Classification of Android Malware With a Fuzzy Strategy to Resist Polymorphic Familial Variants

The Multifamily classification of Android malware aims to identify a malicious sample as one of the given malware families. This problem is believed to be much more significant than the binary classification (simply identify a sample as malicious or benign) because it is able to reveal the behaviour patterns of multiple malware families and bring deep insights into the working mechanism of malicious payload. The main challenges of the multifamily classification involve two aspects: recognizing the behaviour patterns of malware families as well as addressing the issues of code obfuscation and polymorphic variants that are commonly used by adversaries to evade rigorous detections. To address these challenges, in this article, we utilize the regular expressions of callbacks to describe the behaviour patterns of malware families, and propose a two-step fuzzy processing strategy to resist potential polymorphic familial variants. The alphabet of such regular expressions only consists of security-sensitive API calls, this enables the regular expressions to resist various kinds of code obfuscation and metamorphism. The proposed fuzzy strategy, applied to the regular expressions, comprises two steps: the first step transforms an original regular expression to such a fuzzy regular expression that possesses a broader meaning than the original one; the second step further relaxes precise plaintext match between two regular expressions to a fuzzy match by introducing the notion of similarity of regular expressions. Applying this strategy promotes the abstract level of a regular expression and enables the behaviour pattern specified by the regular expression to be more resilient to code obfuscation and polymorphic variants. Furthermore, selecting the fuzzy regular expressions as features, we use text mining techniques to train a multifamily 1-NN classifier over 3270 samples of 65 families. The experimental results show that our approach outperforms most of the state-of-the-art approaches and tools, confirming the effectiveness of our approach.

INVESTIGATION OF METHODS OF INTELLECTUAL ANALYSIS OF BIBLIOGRAPHIC DESCRIPTIONS AND DEVELOPMENT OF PROGRAM SYSTEM FOR ANALYSIS OF LITERATURE LIST

Context. The problem of analyzing a bibliographic list is examined with the purpose of automating the verification of the correctness of its compilation. The object of the study was the process of creating bibliographic descriptions based on existing standards. The subject of the study is models and methods of intellectual analysis for checking and correcting bibliographic descriptions. Objective. The goal of the work is to increase the effectiveness of scientific and pedagogical activity through the use of an intellectual system to check the list of literary sources in the students’ course and diploma papers. Method. The standard is analyzed and the elements composing the bibliographic description are listed. Existing tools for forming and checking the list of literature sources are considered, their shortcomings are revealed, the necessity of creating a software tool for checking bibliographic descriptions is grounded. The research of methods of intellectual analysis is given: methods of regular expressions, fuzzy search with application of fuzzy regular expressions, finite automaton and neural network of Hamming are considered. A previously existing model for checking the bibliographic description for compliance with existing standards was created, based on the methods of regular expressions, fuzzy search, the finite automaton and the neural network of Hamming. An object-oriented model of the projected computer system in the language of visual modeling of UML is presented. The work of computer implementation of the software system implemented in the C # visual programming environment is described. Results. A software system was developed – an intelligent decision-making system – to check the bibliographic description and partially automated correction with user instructions generated based on the knowledge base. Conclusions. The developed intellectual system allows to reveal and correct mistakes of registration of the bibliographic description. The basis of the program is the knowledge base, which can be supplemented if there are any unforeseen situations. In addition, this system makes it possible to accumulate a database of already verified lists of literature. The developed system can be improved without interfering with the source code of the program. At the same time, the level of its capabilities and correctness of corrections, the issuance of comments directly depends on the completeness and correctness of the compiled knowledge base. The prospects for further research include the use of other styles for the design of a list of literature other than DSTU 7.1: 2006, such as the IEEE.

Conversion of fuzzy automata into fuzzy regular expressions using transitive closure

The concept of transitive closure is useful for the conversion of classical finite automata into regular expressions. In this paper, we generalize and extend the concept of transitive closure for the conversion of fuzzy automata into fuzzy regular expressions. We prove that, for a fuzzy automaton M where r is a fuzzy regular expression obtained using the proposed approach, L(M)=L(r). Finally, a numerical example illustrates this conversion.

Parallel Fuzzy Regular Expression and its Conversion to Epsilon-Free Fuzzy Automaton

Parallel Fuzzy Regular Expression and its Conversion to Epsilon-Free Fuzzy Automaton

Fuzzy Lexical Analyser: Design and Implementation

The aim of this paper is to handle the errors, due to insertion, deletion, substitution, letter sequencing and typing in the lexical analysis phase of compiler. Fuzzy keywords, their fuzzy regular expressions and minimized fuzzy deterministic automaton are constructed. The issue of membership of fuzzy keyword is successfully tackled with the help of an algorithm. Full implementation of fuzzy lexical analyzer is also described.

A comment on “Construction of fuzzy automata from fuzzy regular expressions”

The aim of this comment is to point out that the fuzzy language recognized by a nondeterministic finite automaton, which is associated with a fuzzy regular expression, in the context of Stamenković–Ćirić's method (Stamenković and Ćirić (2012) [11]), is recognized by a fuzzy finite automaton with ε-moves. Every fuzzy automaton with ε-moves is also equivalent to a fuzzy automaton and there are effective methods for removing ε-moves in order to obtain the equivalent fuzzy automaton. In this way, our proposal to convert a fuzzy regular expression to a fuzzy finite automaton is based on the construction of a fuzzy automaton with ε-moves for the fuzzy regular expression and the construction of an equivalent fuzzy finite automaton by means of ε-removal operation.

Construction of fuzzy automata from fuzzy regular expressions

Li and Pedrycz have proved fundamental results that provide different equivalent ways to represent fuzzy languages with membership values in a lattice-ordered monoid, and generalize the well-known results of the classical theory of formal languages. In particular, they have shown that a fuzzy language over an integral lattice-ordered monoid can be represented by a fuzzy regular expression if and only if it can be recognized by a fuzzy finite automaton. However, they did not give any efficient method for constructing an equivalent fuzzy finite automaton from a given fuzzy regular expression. In this paper we provide such an efficient method. Transforming scalars appearing in a fuzzy regular expression αinto letters of the new extended alphabet, we convert the fuzzy regular expression αto an ordinary regular expression αR. Then, starting from an arbitrary nondeterministic finite automaton A that recognizes the language ‖αR‖ represented by the regular expression αR, we construct fuzzy finite automata Aα and Aαr with the same or even less number of states than the automaton A, which recognize the fuzzy language ‖α‖represented by the fuzzy regular expression α. The starting nondeterministic finite automaton A can be obtained from αR using any of the well-known constructions for converting regular expressions to nondeterministic finite automata, such as Glushkov–McNaughton–Yamada's position automaton, Brzozowski's derivative automaton, Antimirov's partial derivative automaton, or Ilie–Yu's follow automaton.

Grammar theory based on lattice-ordered monoid

Motivated by Li and Pedrycz's work on fuzzy finite automata and fuzzy regular expressions with membership values in lattice-ordered monoids and inspired by the close relationship between the automata theory and the theory of formal grammars, we have established a fundamental framework of L -valued grammar. It is shown that the set of L -valued regular languages coincides with the set of L -languages recognized by nondeterministic L -fuzzy finite automata and every L -language recognized by a deterministic L -fuzzy finite automaton is an L -valued regular language.

Determinization of fuzzy automata with membership values in complete residuated lattices

In this paper we introduce a new method for determinization of fuzzy finite automata with membership values in complete residuated lattices. In comparison with the previous methods, developed by Bělohlávek [R. Bělohlávek, Determinism and fuzzy automata, Information Sciences 143 (2002), 205–209] and Li and Pedrycz [Y.M. Li, W. Pedrycz, Fuzzy finite automata and fuzzy regular expressions with membership values in lattice ordered monoids, Fuzzy Sets and Systems 156 (2005), 68–92], our method always gives a smaller automaton, and in some cases, when the previous methods result in infinite automata, our method can result in a finite one. We also show that determinization of fuzzy automata is closely related to fuzzy right congruences on a free monoid and fuzzy automata associated with them, and in particular, to the concept of the Nerode’s fuzzy right congruence of a fuzzy automaton, which we introduce and study here.

Fuzzy finite automata and fuzzy regular expressions with membership values in lattice-ordered monoids

We study fuzzy finite automata in which all fuzzy sets are defined by membership functions whose codomain forms a lattice-ordered monoid L . For these L -fuzzy finite automata ( L -FFA, for short), we provide necessary and sufficient conditions for the extendability of the state-transition function. It is shown that nondeterministic L -FFA (N L -FFA, for short) are more powerful than deterministic L -FFA (D L -FFA, for short). Then, we give necessary and sufficient conditions for the simulation of an N L -FFA by an equivalent D L -FFA. Next, we turn to the closure properties of languages defined by L -FFAs: we establish closure under the regular operations and provide conditions for closure under intersection and reversal, in particular we show that the family of fuzzy languages accepted by D L -FFAs is not closed under Kleene closure operation, and the family of fuzzy languages accepted by N L -FFAs is not closed under complement operation. Furthermore, we introduce the notions of L -fuzzy regular expressions and give the Kleene theorem for N L -FFAs. The description of D L -FFAs by L -fuzzy regular expressions is also given. Finally, we investigate the level structures of L -FFAs. Our results provide some insight as to what extend properties of L -FFAs and their languages depend on the algebraic properties of L .

An efficient algorithm for finding kleene closure of regular expression matrices

An efficient algorithm for finding the Kleene closure of regular expressions matrices or fuzzy regular expression matrices is presented and illustrated by examples. Properties of Kleene closure are also investigated. The results may have useful applications in automata theory, pattern recognition, and pictorial information systems.