RabinFingerprinting

Rabinfingerprinting, also known as Rabin fingerprinting, is a technique for assigning compact fingerprints to sequences of bytes by computing a rolling polynomial hash over a finite field. It enables efficient similarity detection and data deduplication by allowing quick updates as the input window slides, so that the fingerprint of a substring can be updated in constant time when a new byte enters the window and an old byte leaves.

In practice, data is treated as coefficients of a polynomial modulo a prime or over GF(2^w). Fingerprints are typically 64-bit or 128-bit values chosen to keep collision probabilities low in practical workloads. During streaming processing, a sliding window computes a fingerprint for the current window; as the window advances, the new fingerprint is updated without a full recomputation.

Applications include content-defined chunking for data backup and synchronization, where boundaries are placed when the fingerprint matches a boundary condition. This enables deduplication of similar content across files and systems. Rabinfingerprinting is also used in file synchronization, versioning systems, and integrity checking where fast, scalable similarity detection is beneficial.

Advantages include fast incremental updates, predictable performance, and low collision probability at standard fingerprint sizes. Limitations include a non-zero risk of hash collisions, sensitivity to parameter choices such as window size and modulus, and the fact that it is not a cryptographic hash suitable for security-critical integrity guarantees. It is typically used as a probabilistic, performance-oriented tool in combination with stronger cryptographic hashes when authenticity is required.

Related concepts include the Rabin-Karp algorithm, rolling hashes, content-defined chunking, and data deduplication.