Breaking and Fixing Secure Similarity Approximations: Dealing with Adversarially Perturbed Inputs
Computing similarity between data is a fundamental problem in information retrieval and data mining. To address the relevant performance and scalability challenges, approximation methods are employed for large-scale similarity computation. A common characteristic among all privacypreserving approximation protocols based on sketching is that the sketching is performed locally and is based on common