On the Limitations of Stochastic Pre-processing Defenses
–Neural Information Processing Systems
Defending against adversarial examples remains an open problem. A common belief is that randomness at inference increases the cost of finding adversarial inputs. An example of such a defense is to apply a random transformation to inputs prior to feeding them to the model.
Neural Information Processing Systems
Aug-17-2025, 04:57:33 GMT
- Country:
- Africa > Ethiopia
- Addis Ababa > Addis Ababa (0.04)
- Asia > Middle East
- Jordan (0.04)
- Europe
- Czechia > Prague (0.04)
- France (0.04)
- Sweden > Stockholm
- Stockholm (0.04)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- North America
- Canada
- Alberta > Census Division No. 15
- Improvement District No. 9 > Banff (0.04)
- British Columbia > Vancouver (0.05)
- Ontario > Toronto (0.14)
- Alberta > Census Division No. 15
- United States
- California
- Los Angeles County > Long Beach (0.14)
- San Diego County > San Diego (0.04)
- San Francisco County > San Francisco (0.14)
- Santa Clara County
- San Jose (0.04)
- Santa Clara (0.04)
- Louisiana > Orleans Parish
- New Orleans (0.04)
- Maryland > Baltimore (0.04)
- Massachusetts > Suffolk County
- Boston (0.04)
- Wisconsin > Dane County
- Madison (0.04)
- California
- Canada
- Africa > Ethiopia
- Genre:
- Research Report (0.93)
- Industry:
- Government (1.00)
- Information Technology > Security & Privacy (0.68)
- Technology: