Datasets‎ > ‎

IoT Network Intrusion Dataset

1. Dataset

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.
* All attacks except Mirai Botnet category are the packets captured while simulating attacks using tools such as Nmap. The case of Mirai Botnet category, the attack packets were generated on a laptop and then manipulated to make it appear as if it originated from the IoT device.

Revision History
* Three more packet files of Mirai Botnet -- Host Discovery and Telnet Bruteforce -- were added on September 20, 2019.

2. Summary of Our Dataset

CategorySub-category# of Packets 
ScanningHost Discovery2,454
ScanningPort Scanning20,939
ScanningOS/Version Detection1,817
Man in the Middle (MITM)ARP Spoofing101,885
Denial of Service (DoS)SYN Flooding64,646
Mirai BotnetHost Discovery673
Mirai BotnetTelnet Bruteforce1,924
Mirai BotnetUDP Flooding949,284
Mirai BotnetACK Flooding75,632
Mirai BotnetHTTP Flooding10,464


For academic purposes, we are happy to release our dataset.
After you submit your application form, we'll send the dataset download link to the email address you provided.

4. Citation 

Please cite our dataset's page when you use this dataset as follows. 

Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, and Huy Kang Kim, "IoT Network Intrusion Dataset.",, 2019


Hyunjae Kang, Dong Hyun Ahn, Gyung Min Lee, Jeong Do Yoo, Kyung Ho Park, and Huy Kang Kim, "IoT network intrusion dataset", IEEE Dataport, 2019. [Online]. Available: Accessed: Sep. 30, 2019.

5. Contact
Hyunjae Kang ( or Huy Kang Kim (

2019. 9. 19. 오후 10:24