What is a collision in a hash function?
2 inputs map to the same output
There are few outputs, but a lot of inputs.
There are few inputs, but a lot of outputs.
2 outputs come from the same input
A collision in a hash function refers to a situation where two different inputs produce the same output or hash value. It means that two distinct inputs result in an identical hash value, which can occur due to the limited range of the output space compared to the potentially infinite input space. This can create complications in certain applications that rely on hash functions, such as data storage and retrieval, as it can lead to data integrity issues or inefficiencies.
A collision in a hash function refers to the situation where two different inputs produce the same output. Essentially, it means that multiple inputs map to the same hash value. There can be different scenarios leading to collisions, such as having more inputs than outputs, where the hash function is forced to map multiple inputs to the same output value. Conversely, there can also be cases where there are more outputs than inputs, resulting in some outputs being produced by multiple inputs. In either case, collisions can have implications for the effectiveness and security of a hash function.
A collision in a hash function occurs when two different inputs produce the same output value or hash value. In other words, it means that there is a possibility of multiple inputs mapping to the same hash value.
To understand this concept, let's first understand what a hash function is. A hash function is a mathematical function that takes an input (such as a data string) and produces a fixed-size output, which is usually a unique sequence of characters or numbers called the hash value or hash code. This hash value is typically used to uniquely identify the input data.
However, due to the nature of hash functions, collisions can occur. There are three common types of collisions:
1. Collision by having two different inputs (data strings) that result in the same hash value.
2. Collision by having a small range of output values and a large number of potential input values.
3. Collision by having the same input (data string) producing two different hash values.
These collisions are unavoidable in hash functions because they need to map an infinite number of inputs to a finite number of outputs. The likelihood of collisions depends on the quality of the hash function and the size of the output space. Generally, a good hash function aims to minimize the chances of collisions by evenly distributing the hash values across the output space.