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20112019
most citedStealing Neural Networks via Timing Side Channels

88 citations · 177 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CR2019★ 12 cited

Fault Tolerance of Neural Networks in Adversarial Settings

Vasisht Duddu, N. Rajesh Pillai, D. Vijay Rao +1

Artificial Intelligence systems require a through assessment of different pillars of trust, namely, fairness, interpretability, data and model privacy, reliability (safety) and rob…

cs.CR2018★ 88 cited

Stealing Neural Networks via Timing Side Channels

Vasisht Duddu, Debasis Samanta, D Vijay Rao +1

Deep learning is gaining importance in many applications. However, Neural Networks face several security and privacy threats. This is particularly significant in the scenario where…

eess.IV2018★ 3 cited

Cross-Sensor Iris Recognition: LG4000-to-LG2200 Comparison

Nicolaie Popescu-Bodorin, Lucian Stefanita Grigore, Valentina Emilia Balas +9

Cross-sensor comparison experimental results reported here show that the procedure defined and simulated during the Cross-Sensor Comparison Competition 2013 by our team for migrati…

cs.CV2012

The Biometric Menagerie - A Fuzzy and Inconsistent Concept

Nicolaie Popescu-Bodorin, Valentina E. Balas, Iulia M. Motoc

This paper proves that in iris recognition, the concepts of sheep, goats, lambs and wolves - as proposed by Doddington and Yager in the so-called Biometric Menagerie, are at most f…

cs.CV2012

Combined Haar-Hilbert and Log-Gabor Based Iris Encoders

Valentina E. Balas, Iulia M. Motoc, Alina Barbulescu

This chapter shows that combining Haar-Hilbert and Log-Gabor improves iris recognition performance leading to a less ambiguous biometric decision landscape in which the overlap bet…

cs.AI2011★ 19 cited

8-Valent Fuzzy Logic for Iris Recognition and Biometry

N. Popescu-Bodorin, V. E. Balas, I. M. Motoc

This paper shows that maintaining logical consistency of an iris recognition system is a matter of finding a suitable partitioning of the input space in enrollable and unenrollable…