N-BaIoT processed for anomaly detection

Published: 1 October 2021| Version 1 | DOI: 10.17632/hpbszmrns7.1
Malgorzata Gutowska


The original data comes from the work of Meidan et al. [1]. It was preprocessed in this setting for comparative analysis of anomaly detection. The following steps have been taken as preprocessing: (1) five devices have been selected: Danmini doorbell, Ecobee thermostat, Philips baby monitor, Provision security camera, Samsung webcam, (2) for each botnet, the malicious traffic of all five behaviour types have been merged, (3) for each device and botnet combination, malicious requests have been sampled to comprise 5% of the final dataset. [1] Meidan, Y., Bohadana, M., Mathov, Y., Mirsky, Y., Shabtai, A., Breitenbacher, D., & Elovici, Y. (2018). N-baiot—network-based detection of iot botnet attacks using deep autoencoders. IEEE Pervasive Computing, 17(3), 12-22.



Intrusion Detection, Internet of Things, Outlier