@inproceedings{20cb8c01fb0f456998e7697fd974d7ea,
title = "Machine learning for analyzing malware",
abstract = "The Internet has become an indispensable part of people{\textquoteright}s work and life. It provides favorable communication conditions for malwares. Therefore, malwares are endless and spread faster and become one of the main threats of current network security. Based on the malware analysis process, from the original feature extraction and feature selection to malware detection, this paper introduces the machine learning algorithm such as clustering, classification and association analysis, and how to use the machine learning algorithm to malware and its variants for effective analysis.",
keywords = "Analyzing malware, Association analysis, Classification, Clustering, Machine learning",
author = "Yajie Dong and Zhenyan Liu and Yida Yan and Yong Wang and Tu Peng and Ji Zhang",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 11th International Conference on Network and System Security, NSS 2017 ; Conference date: 21-08-2017 Through 23-08-2017",
year = "2017",
doi = "10.1007/978-3-319-64701-2_28",
language = "English",
isbn = "9783319647005",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "386--398",
editor = "Zheng Yan and Refik Molva and Wojciech Mazurczyk and Raimo Kantola",
booktitle = "Network and System Security - 11th International Conference, NSS 2017, Proceedings",
address = "Germany",
}