University of Twente Student Theses
Privacy-preserving counterfactual explanations to help humans contest AI-based decisions
Nelson, D.J. (2022) Privacy-preserving counterfactual explanations to help humans contest AI-based decisions.
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| Abstract: | In the Cybersecurity field, very little work is done that measures how vulnerable is multi-objective counterfactual explanations to adversarial attacks and to what extent the privacy of the individuals can be preserved. Through this research, we aim to answer the question- (i) How easy it is to perform a membership inference attack through counterfactual explanations (ii) what is the defense mechanism to prevent a membership inference attack? |
| Item Type: | Essay (Master) |
| Clients: | TNO |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 31 mathematics, 54 computer science |
| Programme: | Computer Science MSc (60300) |
| Link to this item: | https://purl.utwente.nl/essays/92461 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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