LATAM-DDoS-IoT dataset

Citation Author(s):
Josue Genaro
Almaraz-Rivera
Tecnologico de Monterrey
Jesus Arturo
Perez-Diaz
Tecnologico de Monterrey
Jose Antonio
Cantoral-Ceballos
Tecnologico de Monterrey
Juan Felipe
Botero
Universidad de Antioquia
Luis A.
Trejo
Tecnologico de Monterrey
Submitted by:
Josue Almaraz-Rivera
Last updated:
Fri, 10/14/2022 - 17:34
DOI:
10.21227/rwtj-dd43
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Abstract 

Anomaly detection is a well-known topic in cybersecurity. Its application to the Internet of Things can lead to suitable protection techniques against problems such as denial of service attacks. However, Intrusion Detection Systems based on Artificial Intelligence, as a defense mechanism, need robust data sources to achieve strong generalization levels from the knowledge domain of interest. Therefore, here we present the LATAM-DDoS-IoT dataset, which results from a collaboration among Aligo, Universidad de Antioquia, and Tecnologico de Monterrey. The LATAM-DDoS-IoT dataset includes attack traffic to physical Internet of Things devices and normal traffic from real external users consuming actual services from Aligo's production network.

Instructions: 

The LATAM-DDoS-IoT dataset was designed and created during a collaboration among Aligo, Universidad de Antioquia, and Tecnologico de Monterrey. Thanks to Aligo's support, we built and implemented a testbed for DoS and DDoS attacks. This testbed is mainly based on physical IoT devices and real users consuming real services from a production network. We provide the ground truth pcap files and the generated network flows, their features, and the labeled categories and subcategories to facilitate the implementation of supervised learning methods.

The total number of samples for the DoS version of our new dataset is 30,662,911 flows with 20 attributes, and for the DDoS version 49,666,991 flows with the same number of attributes. In total, there is more than 300 GB of information, including .argus, .csv, and .pcap files.

Funding Agency: 
This work was supported in part by the Fondo Regional para la Innovación Digital en América Latina y el Caribe (FRIDA), and in part by the Project ‘‘Red temática Ciencia y Tecnología para el Desarrollo (CYTED)’’.
Grant Number: 
519RT0580

Comments

research purpose

Submitted by Sultan Almeghlef on Sat, 06/25/2022 - 02:45

data science

Submitted by jaime sanchez on Thu, 08/25/2022 - 00:10

how are dear? i am MSc student from Ethiopia how can i get free access to this dataset i need it for research purpose? could help me please

Submitted by habtamu belachew on Thu, 01/12/2023 - 04:50