@inproceedings{083c24e9719e4e748cbccea186aeb757,
title = "Hierarchical similarity hash for fast malware detection",
abstract = "Hundreds of thousands of new malicious files are being created every day. Existing pattern-based vaccine engines cannot detect these new malicious files. To solve these problems, artificial intelligence based malicious file detection methods have been proposed. However, artificial intelligence based malicious file detection method has a disadvantage that takes long time because it requires dynamic analysis. We can use similarity hashes to solve these problems and find similar files. However, it also takes a long time to compare similarity hashes when there are many files. To solve this problem, this paper proposes a method to generate hierarchical similarity hash based on M-tree.",
keywords = "M-tree, Similarity hash",
author = "Sunoh Choi",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 15th International Conference on Future Information Technology, Future Tech 2020 ; Conference date: 17-08-2020 Through 19-08-2020",
year = "2021",
doi = "10.1007/978-981-15-9309-3\_19",
language = "English",
isbn = "9789811593086",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "127--131",
editor = "Park, \{James J.\} and Vincenzo Loia and Yi Pan and Yunsick Sung",
booktitle = "Advanced Multimedia and Ubiquitous Engineering - MUE-FutureTech 2020",
}