All You Need Is Hashing: Defending Against Data Reconstruction Attack in Vertical Federated Learning. (arXiv:2212.00325v1 [cs.CR])

Vertical federated learning is a trending solution for multi-party
collaboration in training machine learning models. Industrial frameworks adopt
secure multi-party computation methods such as homomorphic encryption to
guarantee data security and privacy. However, a line of work has revealed that
there are still leakage risks in VFL. The leakage is caused by the correlation
between the intermediate representations and the raw data. Due to the powerful
approximation ability of deep neural networks, an adversary can capture the
correlation precisely and …

attack data federated learning hashing