The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kos kerosakan yang disebabkan oleh perisian hasad telah meningkat di dunia. Biasanya, malwares dibungkus supaya ia tidak dikesan. Ia adalah tugas yang sukar walaupun penganalisis perisian hasad profesional untuk mengenal pasti pembungkus terutamanya apabila perisian hasad padat berbilang lapisan. Dalam surat ini, kami mencadangkan kaedah untuk mengenal pasti pembungkus untuk perisian hasad berbilang lapisan yang dibungkus dengan menggunakan k-algoritma jiran terdekat dengan analisis entropi untuk malware.
Ryoto OMACHI
Osaka Electro-Communication University
Yasuyuki MURAKAMI
Osaka Electro-Communication University
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Salinan
Ryoto OMACHI, Yasuyuki MURAKAMI, "Packer Identification Method for Multi-Layer Executables Using Entropy Analysis with k-Nearest Neighbor Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E106-A, no. 3, pp. 355-357, March 2023, doi: 10.1587/transfun.2022CIL0002.
Abstract: The damage cost caused by malware has been increasing in the world. Usually, malwares are packed so that it is not detected. It is a hard task even for professional malware analysts to identify the packers especially when the malwares are multi-layer packed. In this letter, we propose a method to identify the packers for multi-layer packed malwares by using k-nearest neighbor algorithm with entropy-analysis for the malwares.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2022CIL0002/_p
Salinan
@ARTICLE{e106-a_3_355,
author={Ryoto OMACHI, Yasuyuki MURAKAMI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Packer Identification Method for Multi-Layer Executables Using Entropy Analysis with k-Nearest Neighbor Algorithm},
year={2023},
volume={E106-A},
number={3},
pages={355-357},
abstract={The damage cost caused by malware has been increasing in the world. Usually, malwares are packed so that it is not detected. It is a hard task even for professional malware analysts to identify the packers especially when the malwares are multi-layer packed. In this letter, we propose a method to identify the packers for multi-layer packed malwares by using k-nearest neighbor algorithm with entropy-analysis for the malwares.},
keywords={},
doi={10.1587/transfun.2022CIL0002},
ISSN={1745-1337},
month={March},}
Salinan
TY - JOUR
TI - Packer Identification Method for Multi-Layer Executables Using Entropy Analysis with k-Nearest Neighbor Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 355
EP - 357
AU - Ryoto OMACHI
AU - Yasuyuki MURAKAMI
PY - 2023
DO - 10.1587/transfun.2022CIL0002
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E106-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2023
AB - The damage cost caused by malware has been increasing in the world. Usually, malwares are packed so that it is not detected. It is a hard task even for professional malware analysts to identify the packers especially when the malwares are multi-layer packed. In this letter, we propose a method to identify the packers for multi-layer packed malwares by using k-nearest neighbor algorithm with entropy-analysis for the malwares.
ER -