Please use this identifier to cite or link to this item: http://hdl.handle.net/10263/7159
Full metadata record
DC FieldValueLanguage
dc.contributor.authorDe, Shankhadeep-
dc.date.accessioned2021-07-05T05:59:47Z-
dc.date.available2021-07-05T05:59:47Z-
dc.date.issued2020-07-
dc.identifier.citation17p.en_US
dc.identifier.urihttp://hdl.handle.net/10263/7159-
dc.descriptionDissertation under the supervision of Dr. Dr. Debrup Chakraborty,Associate Professor,Cryptology and Security Research Uniten_US
dc.description.abstractThe existence of evasion attacks during the test phase of machine learning algorithms repre- sents a signi cant challenge to their deployment and understanding. These attacks are carried out by adding imperceptible perturbations to the inputs to generate adversarial examples. As of now designing good robust classi ers in real life seems very di cult. But so far most of the studies depict the relationship between computational power of adversary and robustness of the classi er. In this report, we have used some of the cryptographic schemes to create robust classi ers and show the dependency of robustness with adversarial budget.en_US
dc.language.isoenen_US
dc.publisherIndian Statistical Institute, Kolkataen_US
dc.relation.ispartofseriesDissertation;;2020-8-
dc.subjectHash Functionsen_US
dc.subjectHoe ding's inequalityen_US
dc.titleConstructing Robust Classi ers using Cryptographic objectsen_US
dc.typeOtheren_US
Appears in Collections:Dissertations - M Tech (CS)

Files in This Item:
File Description SizeFormat 
CS1828_ Shankhadeep De Dissertation.pdf323.65 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.