Generation of Labelled Datasets to Quantify the Impact of Security Threats to Cloud Data Centers

ISSN Print: 2153-1234
ISSN Online: 2153-1242
www.scirp.org/journal/jis
E-mail: jis@scirp.org

"Generation of Labelled Datasets to Quantify the Impact of Security Threats to Cloud Data Centers"
written by Sai Kiran Mukkavilli, Sachin Shetty, Liang Hong,
published by Journal of Information Security, Vol.7 No.3, 2016

has been cited by the following article(s):

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[8]	A Study on Labeling Network Hostile Behavior with Intelligent Interactive Tools
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[10]	Generation of DDoS Attack Dataset for Effective IDS Development and Evaluation
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[1]	Network Intrusion Detection via Flow-to-Image Conversion and Vision Transformer Classification IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3200034

[2]	RTL-DL: A Hybrid Deep Learning Framework for DDoS Attack Detection in a Big Data Environment International journal of Computer Networks & Communications, 2022 DOI:10.5121/ijcnc.2022.14604

[3]	Active learning approach to label network traffic datasets Journal of Information Security and Applications, 2019 DOI:10.1016/j.jisa.2019.102388

[4]	A Study on Labeling Network Hostile Behavior with Intelligent Interactive Tools 2019 IEEE Symposium on Visualization for Cyber Security (VizSec), 2019 DOI:10.1109/VizSec48167.2019.9161489

[5]	Trusted Transport Telemetry by Using Distributed Databases 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), 2019 DOI:10.1109/EIConRus.2019.8657215