Publication result detail

GenRex: Leveraging Regular Expressions for Dynamic Malware Detection

REGÉCIOVÁ, D.; KOLÁŘ, D.

Original Title

GenRex: Leveraging Regular Expressions for Dynamic Malware Detection

English Title

GenRex: Leveraging Regular Expressions for Dynamic Malware Detection

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

GenRex is a unique tool for detecting similarities in artifacts (extracted data) from executable files and for generating regular expressions from them. It implements an advanced algorithm to create regular expressions, improves state-of-the-art algorithms, and includes domain-specific optimizations and pattern detections for optimal results.

Generated regular expressions can be used for malware detections, for example, with YARA or any other pattern-matching tool. In this paper, we present the benefits of using this tool, the key features of GenRex that other existing solutions are missing, the algorithm for the automatic generation of YARA rules, and the benefits of using behavioral data for malware detection in general. We also tested GenRex on publicly available behavioral reports and achieved a high True Positive Rate of 92.34% and a low False Positive Rate of 0.01%.

English abstract

GenRex is a unique tool for detecting similarities in artifacts (extracted data) from executable files and for generating regular expressions from them. It implements an advanced algorithm to create regular expressions, improves state-of-the-art algorithms, and includes domain-specific optimizations and pattern detections for optimal results.

Generated regular expressions can be used for malware detections, for example, with YARA or any other pattern-matching tool. In this paper, we present the benefits of using this tool, the key features of GenRex that other existing solutions are missing, the algorithm for the automatic generation of YARA rules, and the benefits of using behavioral data for malware detection in general. We also tested GenRex on publicly available behavioral reports and achieved a high True Positive Rate of 92.34% and a low False Positive Rate of 0.01%.

Keywords

Malware detection, dynamic analysis, pattern generation algorithm, regular expressions, rules generation algorithm, YARA, GenRex

Key words in English

Malware detection, dynamic analysis, pattern generation algorithm, regular expressions, rules generation algorithm, YARA, GenRex

Authors

REGÉCIOVÁ, D.; KOLÁŘ, D.

RIV year

2025

Released

01.11.2023

Publisher

Institute of Electrical and Electronics Engineers

Location

Exeter

ISBN

979-8-3503-8199-3

Book

IEEE Xplore

Pages from

857

Pages to

864

Pages count

8

URL

https://ieeexplore.ieee.org/document/10538538

BibTex

@inproceedings{BUT185111,
  author="Dominika {Regéciová} and Dušan {Kolář}",
  title="GenRex: Leveraging Regular Expressions for Dynamic Malware Detection",
  booktitle="IEEE Xplore",
  year="2023",
  pages="857--864",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Exeter",
  doi="10.1109/TrustCom60117.2023.00123",
  isbn="979-8-3503-8199-3",
  url="https://ieeexplore.ieee.org/document/10538538"
}