Machine Learning Algorithms on Botnet Traffic-Reference-Cited by-同舟云学术

Machine Learning Algorithms on Botnet Traffic

Published:2019-03-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 3rd International Conference on Compute and Data Analysis
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Author:

McKay Rob¹,Pendleton Brian¹,Britt James¹,Nakhavanit Ben¹

Affiliation:

1. Marymount University, School of Business and Technology, Arlington, VA

Publisher

ACM

Reference17 articles.

1. Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection

2. Canadian Institute for Cybersecurity. (2017). Intrusion Detection Evaluation Dataset (CICS2017){dataset}. Retrieved from https://www.unb.ca/cic/datasets/ids-2017.html. Canadian Institute for Cybersecurity. (2017). Intrusion Detection Evaluation Dataset (CICS2017){dataset}. Retrieved from https://www.unb.ca/cic/datasets/ids-2017.html.

3. Council of Economic Advisers. (2018) Retrieved from https://www.whitehouse.gov/wp-content/uploads/ 2018/02/The-Cost-of-Malicious-Cyber-Activity-to-the-U.S.-Economy.pdf. Council of Economic Advisers. (2018) Retrieved from https://www.whitehouse.gov/wp-content/uploads/ 2018/02/The-Cost-of-Malicious-Cyber-Activity-to-the-U.S.-Economy.pdf.

4. Department of Defense. (2015). The Department of Defense Cyber Strategy. https://www.defense.gov/Portals/ /1/features/2015/0415_cyberstrategy/Final_2015_DoD_ Department of Defense. (2015). The Department of Defense Cyber Strategy. https://www.defense.gov/Portals/ /1/features/2015/0415_cyberstrategy/Final_2015_DoD_

5. A review on feature selection in mobile malware detection

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