ARTFEED — Contemporary Art Intelligence

ArmSSL: Adversarial Robust Black-Box Watermarking for SSL Encoders

ai-technology · 2026-04-27

A new framework called ArmSSL addresses intellectual property protection for self-supervised learning (SSL) encoders. It enables black-box ownership verification when stolen encoders are used in downstream tasks, while being robust against adversarial watermark detection or removal. The method introduces paired discrepancy enlargement to enforce feature-space orthogonality between clean and watermark samples, and integrates latent representation entanglement for adversarial robustness. This work is published on arXiv (2604.22550).

Key facts

  • ArmSSL is a watermarking framework for SSL pre-trained encoders.
  • It provides black-box verifiability and adversarial robustness.
  • Paired discrepancy enlargement enforces feature-space orthogonality.
  • Latent representation entanglement enhances adversarial robustness.
  • Published on arXiv with ID 2604.22550.
  • Addresses IP protection for SSL encoders.
  • Watermark samples form a distinguishable OOD cluster.
  • No prior SSL watermarking met both requirements simultaneously.

Entities

Institutions

  • arXiv

Sources