Characteristics of Hash Functions in Solidity

A hash function in Solidity should be almost impossible to create another different input that can create a hash value that originally belongs to another input

The following are typical characteristics of hash functions:

1. Output with a Fixed Length (Hash Value)

• The hash function converts data of any length to data of a specific length. This method is referred to as hashing the data in some circles.

• As a rule, the hash function is significantly smaller than the input data, which is why hash functions are often referred to as compression functions in some circles.

• Because a hash is a condensed representation of a bigger piece of data, it is also referred to as a digest in some circles.

• An n-bit hash function is a hash function that has an output of n bits and is referred to as such. Popular hash functions give results ranging from 160 to 512 bits in length.

1. Increased Operational Efficiency

• In general, given any hash function h with input x, the computation of h(x) is a quick operation that takes little time.

• A symmetric encryption method is significantly slower than a computational hash function.

The following characteristics of a hash function are desired for it to be a successful cryptographic tool:

• Resistance to the Pre-Image - This feature implies that reversing a hash function should be computationally difficult to accomplish. To put it another way, if a hash function h produces a hash value z, then finding any input value x that hashes to z should be a tough operation. This property protects against an attacker who only has a hash value and is attempting to decipher the input value from the hash value.

• Resistance to the Second Pre-Image - This feature indicates that given input and its hash, it should be difficult to identify a different input with the same hash in the same situation. As a result of the fact that each given input value x produces the hash value h(x), it should be impossible to locate any other input value y for which the hash function (h) equals the value of the input value h(x) (x). In this way, a malicious attacker who has access to an input value and its hash but wishes to replace a different value as a legal value instead of the original input value is prevented from gaining access to the data.

• Resistance to Collisions - This characteristic indicates that it should be difficult to identify two separate inputs of any length that result in the same hash value. This characteristic is regarded as a collision-free hash function in some circumstances. To put it another way, for a hash function h, it is difficult to identify any two independent inputs x and y such that h(x) = h(y) (y). Because a hash function is a compression function with a defined hash length, a hash function can't be completely free of collisions. This virtue of being collision-free only serves to reinforce the notion that these collisions should be difficult to detect. The fact that this feature exists makes it extremely difficult for an attacker to locate two input values that have the same hash value. Furthermore, if a hash function is collision-resistant, it is also resistant to second pre-image collisions.

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