Fast, lightweight IoT anomaly detection using feature pruning and PCA

Author:

Carter John1,Mancoridis Spiros1,Galinkin Erick1

Affiliation:

1. Drexel University

Funder

Auerbach Berger Chair in Cybersecurity

Publisher

ACM

Reference9 articles.

1. Network Anomaly Detection: Methods, Systems and Tools

2. Run-time classification of malicious processes using system call analysis

3. Raghavendra Chalapathy and Sanjay Chawla . 2019. Deep Learning for Anomaly Detection: A Survey. CoRR abs/1901.03407 ( 2019 ). arXiv:1901.03407 http://arxiv.org/abs/1901.03407 Raghavendra Chalapathy and Sanjay Chawla. 2019. Deep Learning for Anomaly Detection: A Survey. CoRR abs/1901.03407 (2019). arXiv:1901.03407 http://arxiv.org/abs/1901.03407

4. Anomaly-based network intrusion detection: Techniques, systems and challenges

5. Attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches

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