Collision (computer science)

Not to be confused with wireless packet collision or hash table collisions.

In computer science, a collision or clash is a situation that occurs when two distinct pieces of data have the same hash value, checksum, fingerprint, or cryptographic digest.[1]

Collisions are unavoidable whenever members of a very large set (such as all possible person names, or all possible computer files) are mapped to a relatively short bit string. This is merely an instance of the pigeonhole principle.[1]

The impact of collisions depends on the application. When hash functions and fingerprints are used to identify similar data, such as homologous DNA sequences or similar audio files, the functions are designed so as to maximize the probability of collision between distinct but similar data. Checksums, on the other hand, are designed to minimize the probability of collisions between similar inputs, without regard for collisions between very different inputs.

Half-duplex Data Communications Networks

Half-duplex (HDX) data communications networks have the possibility that more than one node will transmit at the same or overlapping time. This event is referred to as a collision. The messages sent by the transmitting nodes are corrupted. The receiving nodes will receive (in most but not all cases) random data. In half-duplex networks, the transmitting node must ensure that the network is quiet prior to transmitting, and in addition there is usually some mechanism for transmitting nodes to detect overlapping transmissions. See also Collision domain.

See also

References

  1. 1 2 Jered Floyd (2008-07-18). "What do Hash Collisions Really Mean?". http://permabit.wordpress.com/: Permabits and Petabytes. Retrieved 2011-03-24. For the long explanation on cryptographic hashes and hash collisions, I wrote a column a bit back for SNW Online, “What you need to know about cryptographic hashes and enterprise storage”. The short version is that deduplicating systems that use cryptographic hashes use those hashes to generate shorter “fingerprints” to uniquely identify each piece of data, and determine if that data already exists in the system. The trouble is, by a mathematical rule called the “pigeonhole principle”, you can’t uniquely map any possible files or file chunk to a shorter fingerprint. Statistically, there are multiple possible files that have the same hash.


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