Finger Vein

The University of Twente Finger Vascular Pattern (UTFVP) Database is made publically available in order to support and stimulate research efforts in the area of developing, testing and evaluating algorithms for vascular patter recognition. The University of Twente, Enschede, The Netherlands (henceforth, UT) owns copyright of and serves as the source for the UTFVP database, which is now distributed to any research group approved by the UTFVP principal investigator.

Charge : License agreement
Supplied : Dataset


ForenFace is a facial image and video database. It contains video sequences and extracted images of 98 subjects recorded with six different surveillance camera of various types. Moreover, it also contains high resolution images and 3D scans. A subset of 435 images (87 subjects, five images per subject) has been manually annotated, yielding a unique and very rich annotation containing almost 19.000 entries. It also contains a training/testing protocol.

This dataset is hosted by the Netherlands Forensic Institute (NFI). Please contact Arnout Ruifrok for further information on how to obtain this dataset.‚Äč 

On Request :
Supplied : Dataset

Copula Fusion Framework

This program is a matlab implementation of the score level fusion method described in the paper ''Semiparametric Likelihood-ratio-based Score Level Fusion via Parametric Copula''

Charge : Free of charge
Supplied : Software

University of Twente - Faces At Distances (UT-FAD)

This face database contains face images taken at multiple distances.

  • Distances from 1m to 10m, 1m step.
  • 22 subjects
  • Controlled Pose and Illumination

Ideal for studying the effect of distance for face recognition. 

Charge : License agreement
Supplied : Dataset

Data Exfiltration Malware (DEM)

Data Exfiltration Malware (DEM) contains network captures (.pcap) mainly of info-stealer malware. The dataset also contains the traffic we generated using the VM. We used this traffic for training in our analysis, and the malware for testing. This dataset is made publicly available to foster research in data exfiltration detection and prevention. The dataset is not licensed, but we kindly ask you to cite the following work in case you make use of it:

Decanter: Detection of Anomalous Outbound HTTP Traffic By Passive Application Fingerprinting. Riccardo Bortolameotti, Thijs van Ede, Marco Caselli, Rick Hofstede, Maarten H. Everts, Willem Jonker, Pieter Hartel and Andreas Peter. To appear in Proceedings of the 33rd Annual Computer Security Applications Conference (ACSAC). December 2017, Orlando, FL. 

Charge : Free of charge
Supplied : Dataset