FLOSS: Fast Linear Online Secret-Shared Shuffling

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Randomly permuting secret data vectors is a core building block in many privacy-preserving protocols, including those for analytics, advertising, and communication. Existing approaches either rely on computation-heavy public key cryptography and zero-knowledge proofs or scale poorly for large vectors due to use of a quasilinear-sized permutation network. This work presents a preprocessing approach to enable fast linear-time online shuffles in the malicious-secure two-party computation (2PC) set