Serial Number: 103
Year: 2021
Kind of Traffic: Real
Publicly Available: Yes
Count of Records: 25.35GB
Features Count:
No. of citations: 41
Attack Type: port scanning, DDoS traffic, etc
Download Links: https://ieee-dataport.org/open-access/iot-bda-botnet-analysis-dataset
Abstract: Trajanovski et.al presented dataset IOT-BDA. The dataset reveals results from a study carried out by the IoT-BDA Framework, the analysis involved 4077 distinct IoT botnet samples collected via honeypots. Using sandbox execution, the framework conducted static, behavioral, and network analyses to detect signs of compromise and attack, as well as tactics such as anti-dynamic-analysis, anti-static-analysis, anti-forensics, and persistence utilized by IoT botnets. Each sample underwent scanning via Virustotal, with the AVClass malware classifier attributing the most probable malware familyThe dataset enables the grouping of IoT botnet samples according to their static, behavioral, and network characteristics through clustering techniques. It encompasses the botnet samples (ELF files), recorded system call behaviors, and captured network traffic (.pcap), providing comprehensive insights into IoT botnet behaviors and characteristics.