We created various types of network attacks in Internet of Things (IoT) environment for academic purpose. Two typical smart home devices -- SKT NUGU (NU 100) and EZVIZ Wi-Fi Camera (C2C Mini O Plus 1080P) -- were used. All devices, including some laptops or smart phones, were connected to the same wireless network. The dataset consists of 42 raw network packet files (pcap) at different time points.

* The packet files are captured by using monitor mode of wireless network adapter. The wireless headers are removed by Aircrack-ng.

Dataset Files

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[1] Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, Huy Kang Kim, "IoT network intrusion dataset", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/q70p-q449. Accessed: Oct. 05, 2024.
@data{q70p-q449-19,
doi = {10.21227/q70p-q449},
url = {http://dx.doi.org/10.21227/q70p-q449},
author = {Hyunjae Kang; Dong Hyun Ahn; Gyung Min Lee; Jeong Do Yoo; Kyung Ho Park; Huy Kang Kim },
publisher = {IEEE Dataport},
title = {IoT network intrusion dataset},
year = {2019} }
TY - DATA
T1 - IoT network intrusion dataset
AU - Hyunjae Kang; Dong Hyun Ahn; Gyung Min Lee; Jeong Do Yoo; Kyung Ho Park; Huy Kang Kim
PY - 2019
PB - IEEE Dataport
UR - 10.21227/q70p-q449
ER -
Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, Huy Kang Kim. (2019). IoT network intrusion dataset. IEEE Dataport. http://dx.doi.org/10.21227/q70p-q449
Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, Huy Kang Kim, 2019. IoT network intrusion dataset. Available at: http://dx.doi.org/10.21227/q70p-q449.
Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, Huy Kang Kim. (2019). "IoT network intrusion dataset." Web.
1. Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, Huy Kang Kim. IoT network intrusion dataset [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/q70p-q449
Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, Huy Kang Kim. "IoT network intrusion dataset." doi: 10.21227/q70p-q449