SALSA: A Secure, Adaptive and Label-Agnostic Scalable Algorithm for Machine Unlearning

Owais Makroo, Atif Hassan, Swanand Khare

Keywords: machine unlearning, efficiency, deep learning

TL;DR: We propose SALSA, a Secure, Adaptive, Label-Agnostic Algorithm for Machine Unlearning in MLaaS, achieving 25 times speedup over baselines while best approximating exact unlearning among all competitors.

Abstract:

Machine Learning as a Service (MLaaS) has simplified access to powerful machine learning models but faces challenges in complying with the “right to be forgotten” while resisting adversarial threats.
Machine Unlearning (MU) addresses these issues by enabling selective data removal from models.
However, existing methods are slow, label-dependent, vulnerable to black-box attacks, and computationally impractical for large-scale MLaaS deployments.
We introduce SALSA, a Secure, Adaptive, Label-Agnostic, Scalable Algorithm for efficient and robust machine unlearning tailored to classification tasks in MLaaS.
SALSA redistributes the class-wise predicted probabilities of data to be forgotten and optimizes a novel loss function that minimizes the divergence between redistributed and predicted probabilities while anchoring model parameters near their initialization.
This ensures simultaneous unlearning and generalization.
SALSA requires neither labels nor access to the remaining data, making it ideal for MLaaS environments.
It is exceptionally fast, achieving at least $25\times$ faster unlearning, on average, than the fastest baseline, while consistently outperforming five state-of-the-art MU techniques across eight metrics on benchmark datasets.
Experiments on synthetic data show that SALSA’s altered decision boundaries closely approximate exact unlearning.
Rigorous evaluations against state-of-the-art black-box attacks demonstrate its resilience to security threats.
Thus, SALSA redefines practical machine unlearning, offering a scalable and resilient solution for safeguarding privacy in modern MLaaS systems.

Code Link: https://github.com/atif-hassan/SALSA-machine-unlearning

Readers: auai.org/UAI/2025/Conference, auai.org/UAI/2025/Conference/Area_Chairs, auai.org/UAI/2025/Conference/Reviewers, auai.org/UAI/2025/Conference/Submission755/Authors, auai.org/UAI/2025/Conference/Submission755/Reproducibility_Reviewers

Submission Number: 755