| dc.date.accessioned | 2023-12-18T21:48:25Z | |
| dc.date.available | 2023-12-18T21:48:25Z | |
| dc.date.issued | 2023-12-18 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/153202 | |
| dc.description.abstract | The MIT Lincoln Laboratory project Poisoning Cyberattacks to Design of Artificial Intelligence (PoCyDAIn) aims to develop a framework for assessing the impact of poisoning attacks on cyber-ML systems. | en_US |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | The Bulletin; | |
| dc.rights | Attribution-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
| dc.subject | Machine Learning | en_US |
| dc.title | Poisoning Cyberattacks to Design of Artificial Intelligence | en_US |
| dc.type | Article | en_US |
