Detecting DGA Botnet based on Malware Behavior Analysis-Reference-Cited by-同舟云学术

Detecting DGA Botnet based on Malware Behavior Analysis

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:The 11th International Symposium on Information and Communication Technology
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Author:

Nguyen Quoc Khanh¹^ORCID,Bui Tung¹^ORCID,Le Dong¹^ORCID,Tran Duc¹^ORCID,Nguyen Toan²^ORCID,Nguyen Huu Trung Nguyen³^ORCID

Affiliation:

1. Bach Khoa Cybersecurity Center, School of Information and Communications Technology, Hanoi University of Science and Technology, Viet Nam

2. Salesforce.com, Inc., Singapore

3. Cystack JSC., Viet Nam

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3568562.3568590

Reference13 articles.

1. Manos Antonakakis , Roberto Perdisci , Yacin Nadji , Nikolaos Vasiloglou , Saeed Abu-Nimeh , Wenke Lee , and David Dagon . 2012. From Throw-Away Traffic to Bots: Detecting the Rise of DGA-Based Malware. (Aug . 2012 ), 491–506. https://www.usenix.org/conference/usenixsecurity12/technical-sessions/presentation/antonakakis Manos Antonakakis, Roberto Perdisci, Yacin Nadji, Nikolaos Vasiloglou, Saeed Abu-Nimeh, Wenke Lee, and David Dagon. 2012. From Throw-Away Traffic to Bots: Detecting the Rise of DGA-Based Malware. (Aug. 2012), 491–506. https://www.usenix.org/conference/usenixsecurity12/technical-sessions/presentation/antonakakis

2. Classification of malicious domain names using support vector machine and bi-gram method;Davuth S.-R.;International Journal of Security and Its Applications,2013

3. J. Lee J. Kwon H. Lee and A. Perrig. 2016. PsyBoG: A scalable botnet detection method for large-scale DNS traffic. Computer Networks (2016) 48–73. J. Lee J. Kwon H. Lee and A. Perrig. 2016. PsyBoG: A scalable botnet detection method for large-scale DNS traffic. Computer Networks (2016) 48–73.

4. Detecting DGA malware using NetFlow

5. Hieu Mac Duc Tran Van Tong Linh Giang Nguyen and Hai Anh Tran. 2017. DGA Botnet Detection Using Supervised Learning Methods. SoICT 2017: Proceedings of the Eighth International Symposium on Information and Communication Technology(2017) 211-218. https://doi.org/10.1145/3155133.3155166 10.1145/3155133.3155166