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Title: Classification of Ransomware Families Based on Hashing Techniques
Authors: Le, Tran Duc
Le, Ba Luong
Dinh, Truong Duy
Pham, Van Dai
Keywords: Ransomware
Import Hash
Fuzzy Hash
File Level Section Hashing
Issue Date: Jul-2023
Publisher: Springer Nature
Abstract: The primary objective of this research is to propose a novel method for analyzing malware through the utilization of hashing techniques. The proposed approach integrates the use of Import Hash, Fuzzy Hash, and Section Level Fuzzy Hash (SLFH) to create a highly optimized, efficient, and accurate technique to classify ransomware families. To test the proposed methodology, we collected a comprehensive dataset from reputable sources and manually labelled each sample to augment the reliability and precision of our analysis. During the development of the proposed methodology, we introduced new steps and conditions to identify ransomware families, resulting in the highest performance level. The major contributions of this research include the combination of various hashing techniques and the proposal of a hash comparison strategy that facilitates the comparison of section hashes between ransomware and the pre-build database.
Description: Lecture Notes in Networks and Systems (LNNS, volume 734); CITA: Conference on Information Technology and its Applications; pp: 37-49.
ISBN: 978-3-031-36886-8
Appears in Collections:CITA 2023 (International)

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