Leveraging Model Distillation as a Defense Against Adversarial Attacks Based on Deep Learning
- Title
- Leveraging Model Distillation as a Defense Against Adversarial Attacks Based on Deep Learning
- Description
- 2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023 pp.921-925
- Creator
- Suresh K.; Radha J.; Thilagaraj T.; Subramani R.; Lakineni P.K.; Taqui S.N.
- Source
- <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186657477&doi=10.1109%2fICCSAI59793.2023.10421670&partnerID=40&md5=3351519ea3a7a01e55974e76f192607d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186657477&doi=10.1109%2fICCSAI59793.2023.10421670&partnerID=40&md5=3351519ea3a7a01e55974e76f192607d</a>
- Date
- 2023-01-01
Collection
Citation
Suresh K.; Radha J.; Thilagaraj T.; Subramani R.; Lakineni P.K.; Taqui S.N., “Leveraging Model Distillation as a Defense Against Adversarial Attacks Based on Deep Learning,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 8, 2025, https://archives.christuniversity.in/items/show/10025.