A hash collision occurs when two distinct pieces of data produce the same hash value using a hash function. This situation arises because hash functions map input data of arbitrary size to fixed-size values, and the number of possible input values typically exceeds the number of possible hash values. Consequently, different inputs can sometimes result in the same hash value, leading to a collision.
Causes of Hash Collisions
Pigeonhole Principle: Given a large enough set of inputs, the finite number of hash values means that some inputs will inevitably share the same hash value[1].
Birthday Paradox: The probability of collisions increases with the number of inputs, similar to the probability of two people sharing the same birthday in a group[1].
Impact of Hash Collisions
Hash collisions can have various impacts depending on the application:
Data Management: Collisions can lead to inefficiencies in data retrieval and storage.
Security: In cryptographic applications, collisions can be exploited by attackers to forge data or bypass security mechanisms[1][4].
Collision Resolution Techniques
To handle hash collisions, several resolution techniques are employed:
Open Addressing: This method involves probing the hash table to find an empty slot for the colliding data. Types of probing include:
Linear Probing: Sequentially checks the next slots until an empty one is found[2][3].
Quadratic Probing: Uses a quadratic function to determine the next slot, reducing clustering issues[2][3].
Double Hashing: Uses a second hash function to calculate the probe sequence, minimizing clustering[2][3].
Separate Chaining: This technique involves storing all colliding elements in a linked list at the same hash table index. Each slot in the hash table points to a linked list containing all elements that hash to that slot[2][3][5].
Cache-Conscious Collision Resolution: This method, less common than the others, involves storing hash values in a contiguous list of items, which is more efficient for string hash tables[1].
Examples of Hash Collisions
MD5 Collisions: The MD5 hashing algorithm is known for producing many collisions, making it unsuitable for cryptographic purposes[4].
SHA-1 Collisions: Similar vulnerabilities have been found in SHA-1, leading to its deprecation in favor of more secure algorithms like SHA-2 and S...
