Perceptual hashing
Perceptual hashing is the use of an algorithm that produces a snippet or fingerprint of various forms of multimedia.[1][2] Perceptual hash functions are analogous if features are similar, whereas cryptographic rely on the avalanche effect of a small change in input value creating a drastic change in output value. Perceptual hash functions are widely used in finding cases of online copyright infringement as well as in digital forensics because of the ability to have a correlation between hashes so similar data can be found (for instance with a differing watermark). For example, Wikipedia could maintain a database of text hashes of popular online books or articles for which the authors hold copyrights to, anytime a Wikipedia user uploads an online book or article that has a copyright, the hashes will be almost exactly the same and could be flagged as plagiarism. This same flagging system can be used for any multimedia or text file.
References
- ↑ Buldas, Ahto, Andres Kroonmaa, and Risto Laanoja. "Keyless Signatures' Infrastructure: How to Build Global Distributed Hash-Trees - Springer." Keyless Signatures' Infrastructure: How to Build Global Distributed Hash-Trees - Springer. Springer Link, 18 Oct. 2013. Web. 03 Nov. 2014.
- ↑ Klinger, Evan, and David Starkweather. "PHash." .org: Home of , the Open Source Perceptual Hash Library. N.p., n.d. Web. 02 Nov. 2014.
External links
- pHash - an open source perceptual hash library
- Blockhash.io - an open standard for perceptual hashes
- Elog.io - open source blockhash.io implementations
- Insight - a perceptual hash tutorial