Show simple item record Goel, Akhil Singh, Anirudh Vatsa, Mayank (Advisor) Singh, Richa (Advisor) 2019-10-09T07:40:10Z 2019-10-09T07:40:10Z 2019-04-30
dc.description.abstract Extensive research on attacks on deep learning models has shown that these models are not as robust as they seem. A carefully designed low magnitude perturbation is enough to cause havoc and completely confuse the model. This project addresses this pitfall by first developing a benchmarking adversarial detection and adversary mitigation toolbox for face recognition, then by proposing a defense technique that alleviates the embedded imperceptible noise and nally by proposing a blockchain-based architecture for the deep learning models. en_US
dc.language.iso en_US en_US
dc.publisher IIITD-Delhi en_US
dc.subject Adversarial Attacks en_US
dc.subject Adversarial Mitigation en_US
dc.subject Adversarial Detection en_US
dc.subject Deep Learning en_US
dc.subject Security en_US
dc.title Adversary detection tool en_US
dc.type Other en_US

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository

Advanced Search


My Account