  Launched in 2013, LivDet-Iris is an international competition series open to
academia and industry with the aim to assess and report advances in iris
Presentation Attack Detection (PAD). This paper presents results from the
fourth competition of the series: LivDet-Iris 2020. This year's competition
introduced several novel elements: (a) incorporated new types of attacks
(samples displayed on a screen, cadaver eyes and prosthetic eyes), (b)
initiated LivDet-Iris as an on-going effort, with a testing protocol available
now to everyone via the Biometrics Evaluation and Testing
(BEAT)(https://www.idiap.ch/software/beat/) open-source platform to facilitate
reproducibility and benchmarking of new algorithms continuously, and (c)
performance comparison of the submitted entries with three baseline methods
(offered by the University of Notre Dame and Michigan State University), and
three open-source iris PAD methods available in the public domain. The best
performing entry to the competition reported a weighted average APCER of
59.10\% and a BPCER of 0.46\% over all five attack types. This paper serves as
the latest evaluation of iris PAD on a large spectrum of presentation attack
instruments.
