Malware Subspecies Detection Method by Suffix Arrays and Machine Learning

K, Kita; Uda, Ryuya

doi:10.1109/ciss50987.2021.9400219

Cited by 4 publications

(2 citation statements)

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“…In our paper at CISS 2021 [6], we wrote the size of modulo was one byte, but that was a mistake. We apologize for our mistake.…”

Section: Malware Detection Methods With N-grams Of Instruc-mentioning

confidence: 99%

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Fast Preprocessing by Suffix Arrays for Managing Byte n-grams to Detect Malware Subspecies by Machine Learning

Kita,

Uda

2024

Journal of Information Processing

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Although machine learning methods with byte n-grams have been marking high score for classifying malware and benignware, they seem not to be used for current anti-virus software. A performance bottleneck of the methods is dealing with byte n-grams in preprocessing such as top-k selection. It takes a long time to extract all byte n-grams which are required for selecting top-k n-grams. Moreover, if several "n"s are wanted to be used such as 4grams, 8-grams and 16-grams, n-grams with each "n" must be extracted again and again. Therefore, we proposed a fast preprocessing method of extracting n-grams by applying a suffix array algorithm. Furthermore, our method can manage multi-length byte n-grams at the same time. In addition, selecting feature n-grams like top-k n-grams with information gain is also included in our method. On the other hand, our method has a limitation that it is only applicable to a large number of samples in the same malware subspecies family, which become extinct. We evaluated the speed of our method by comparing with usual ways. We also evaluated our method by machine learning with actual samples in four old malware subspecies families. We think there is a hope that our method may be applicable to detecting current targeted malware.

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“…In our paper at CISS 2021 [6], we wrote the size of modulo was one byte, but that was a mistake. We apologize for our mistake.…”

Section: Malware Detection Methods With N-grams Of Instruc-mentioning

confidence: 99%

“…Note that, this paper is a revised version of a paper published in proceedings of an international conference [6].…”

Section: Introductionmentioning

confidence: 99%