Labels of normal and attack classes in the CICIDS-2017 dataset.

<p>Labels of normal and attack classes in the CICIDS-2017 dataset.</p>

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Bibliographic Details
Main Author:	Islam Zada (21755819) (author)
Other Authors:	Esraa Omran (6392693) (author), Salman Jan (21755822) (author), Hessa Alfraihi (21755825) (author), Seetah Alsalamah (21755828) (author), Abdullah Alshahrani (9458515) (author), Shaukat Hayat (14634285) (author), Nguyen Phi (21755831) (author)
Published:	2025
Subjects:	Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified visual evaluation metrics visual analytics approach optimal detection efficiency minimal computational overhead important attack categories 100 percent accuracy extreme learning machine enhancing iot cybersecurity changing cyber threats cyber threats ensemble learning xlink "> world usage statistical verification sql injection smart cities provides scalable making process like portscan industrial internet greatly minimized genetic algorithm false positives efficiently ported dynamical growth brute force bootstrap aggregation 2017 dataset
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