A good hash function will provide a near uniform distribution over the key space. This reduces the question to how do I convert a random 32 bit number to a 3 byte RGB space. I see nothing wrong with just taking the low 3 bytes. int hash = string.getHashCode(); int r = (hash & 0xFF0000) … Read more
Of all bit-operations XOR has the best bit shuffling properties. This truth-table explains why: A B AND 0 0 0 0 1 0 1 0 0 1 1 1 A B OR 0 0 0 0 1 1 1 0 1 1 1 1 A B XOR 0 0 0 0 1 1 1 0 … Read more
In your case, breaking the hash algorithm is equivalent to finding a collision in the hash algorithm. That means you don’t need to find the password itself (which would be a preimage attack), you just need to find an output of the hash function that is equal to the hash of a valid password (thus … Read more
The CRC32 found in zip and a lot of other places uses the polynomial 0x04C11DB7; its reversed form 0xEDB88320 is perhaps better known, being often found in little-endian implementations. CRC32C uses a different polynomial (0x1EDC6F41, reversed 0x82F63B78) but otherwise the computation is the same. The results are different, naturally. This is also known as the … Read more
The hash package is helpful for this. Note it’s an abstraction over specific hash implementations. Some ready made are found in the package subdirectories. Example: package main import ( “fmt” “hash/fnv” ) func hash(s string) uint32 { h := fnv.New32a() h.Write([]byte(s)) return h.Sum32() } func main() { fmt.Println(hash(“HelloWorld”)) fmt.Println(hash(“HelloWorld.”)) } (Also here) Output: 926844193 107706013
With “salt round” they actually mean the cost factor. The cost factor controls how much time is needed to calculate a single BCrypt hash. The higher the cost factor, the more hashing rounds are done. Increasing the cost factor by 1 doubles the necessary time. The more time is necessary, the more difficult is brute-forcing. … Read more
This hash function is similar to a Linear Congruential Generator (LCG – a simple class of functions that generate a series of psuedo-random numbers), which generally has the form: X = (a * X) + c; // “mod M”, where M = 2^32 or 2^64 typically Note the similarity to the djb2 hash function… a=33, … Read more
You’re correct that it cannot guarantee uniqueness, however there are approximately 3.402823669209387e+38 different values in a 32 digit hex value (16^32). That means that, assuming the math behind the algorithm gives a good distribution, your odds are phenomenally small that there will be a duplicate. You do have to keep in mind that it IS … Read more
It has been noted by many well respected developers such as Brian Goetz and Josh Bloch that : If an object’s hashCode() value can change based on its state, then we must be careful when using such objects as keys in hash-based collections to ensure that we don’t allow their state to change when they … Read more
Are the 160 bit hash values generated by SHA-1 large enough to ensure the fingerprint of every block is unique? Assuming random hash values with a uniform distribution, a collection of n different data blocks and a hash function that generates b bits, the probability p that there will be one or more collisions is … Read more