 |
HAL-LAAS Open Archive Laboratory for Analysis and Architecture of Systems |  |
Conference papers
IoT Attack Detection with Deep Learning
Abstract : In this paper, we analyze the network attacks that can be launched against IoT gateways, identify the relevant metrics to detect them, and explain how they can be computed from packet captures. We also present the principles and design of a deep learning-based approach for the online detection of network attacks. Empirical validation results on packet captures in which attacks were inserted show that the Deep Neural Network correctly detects attacks.
Cited literature [24 references]
https://hal.laas.fr/hal-02062091
Contributor : Olivier Brun <>
Submitted on : Friday, March 8, 2019 - 3:25:10 PM
Last modification on : Thursday, June 10, 2021 - 3:03:08 AM
Long-term archiving on: : Monday, June 10, 2019 - 3:25:03 PM
Contributor : Olivier Brun <>
Submitted on : Friday, March 8, 2019 - 3:25:10 PM
Last modification on : Thursday, June 10, 2021 - 3:03:08 AM
Long-term archiving on: : Monday, June 10, 2019 - 3:25:03 PM
File
article.pdf
Files produced by the author(s)