Anomaly based Detection Analysis for Intrusion Detection System using Big Data Technique with Learning Vector Quantization (LVQ) and Principal Component Analysis (PCA)-Reference-Cited by-同舟云学术

Anomaly based Detection Analysis for Intrusion Detection System using Big Data Technique with Learning Vector Quantization (LVQ) and Principal Component Analysis (PCA)

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Artificial Intelligence and Virtual Reality - AIVR 2018
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Author:

Salman Muhammad¹,Husna Diyanatul¹,Apriliani Stella Gabriella¹,Pinem Josua Geovani¹

Affiliation:

1. Department of Electrical Engineering, Universitas Indonesia, Depok, Indonesia

Funder

DRPM Universitas Indonesia

Publisher

ACM Press

Reference14 articles.

1. D. S. Terzi, R. Terzi and S. Sagiroglu, "A survey on security and privacy issues in big data," dalam 10th International Conference for Internet Technology and Secured Transactions (ICITST), London, pp. 202--207, 2015.

2. R. Bloor. "Why do Machine Learning on Big Data?" (n.d.). [Online]. Available:http://www.skytree.net/machine-learning/why-do-machine-lear ning-big-data/. [23 October 2016]

3. P.G. Prathiba and E.D. Dileesh, "Design of a Hybrid Intrusion Detection System using Snoort and Hadoop," in International Journal of Computer Applications, vol 73, pp. 5--10.10 Juli 2013

4. Apache Spark (n.d.) "Apache Spark." [Online]. Available: http://spark.apach e.org/ [23 October 2016]

5. Garg and P. Maheshwari, "A hybrid intrusion detection system: A review," 2016 10th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, 2016, pp. 1--5.

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