Programming Concepts: Hashing

how is hashing used, describe an algorithm to do this. Why would you use hashing?

As you should know from studying databases we often have to search for data in tables using the primary key. That is the unique value that is stored about each record. This is normally a number, but if we didn't have a primary key we would still have to be able to search through data. For example the table below shows details about some students in a class, and we are going to search on the name of each student:

Name	Date of Birth	Hair Colour
John Smith	19072000	Brown
Lisa Smith	07031999	Red
Sam Doe	12121954	Blonde
Sandra Dee	01012006	Blonde
Aubrey Carringtoe	12101967	Blonde
Aubrey Carring	22102000	Black
Aubrey Carrington	22102000	Blonde
Aubrey Carringy	31092007	None
Aubrey Carringtone	04042004	Blonde
...	...	...

Searching on the name of each student could take some time as we might be searching for:

Anthony Tarkovsky

This might take checking thousands of different records and 17 characters before we were sure that we found them. If the data was even larger it could take much longer than that. What is needed is a quick way to apply an index key to each data item so we can quickly search through the data. Attaching an index key to each data item (or hashing key) is called Hashing and the index value is called the Hashing Value. This Hashing Value isn't random, but is dependent on the Hashing Key being hashed, so that each time you apply the hashing code to the same data, you'll get the same hash value. It isn't random!

For example if we hashed each name (or hash key) and Anthony Tarkovsky's hash value was 12 and Aubrey Carringtone's hash value was 26. If we were to look for "Aubrey Carrington" we would know that this name had the value of 26 and would only need to check the hashing table to see if 26 existed instead of searching through the name field for all 17 characters.

As you can't work out the original value from the hashed value, Hashing is also used to store passwords. Very silly companies keep passwords in text fields, doing this would leave them open to script kiddies stealing user login details. Much smarter companies do the following:

1. user enters password "thisisreallym3"
2. database system hashes password to "fjj34N6*34£sdf234&" and stores this in the Database.

Now when a customer returns to the site and enters their password the system does the following:

1. user enters password
2. this is immediately hashed and the hashed value compared against the database value
3. if values are the same let them in, if values are different kick them out

This also has the benefit of dealing with the following situation:

1. Script kiddie cracks into system and steals user database
2. they get user details with only the hashed password
3. hashed passwords are useless for finding out real passwords without the hashing algorithm (and mostly useless with it!)
4. Users don't find they have had accounts on other websites compromised as they use the same password everywhere

In summary Hashing is used for two things:

• Save computation time in searching through data
• Provides a secure way of storing sensitive data
• Verifying data has transmitted correctly

Hashing tables

To build a set of hashing values we use a hashing algorithm to create a Hashing table. Take a look at diagram below, by applying a hashing algorithm each data item (or hashing key) has a hashing value.

A minimal perfect hash function for the four names shown

Now if we decided to look for:

Hash Key	Hashing Function	Hash Value
"Sam Doe"	Apply Hashing Function	Hash Value=3

Searching the hashing table for hashing value 3, we find it and we know that Sam Doe does exist.

But what about searching for an item that doesn't exist? Take a look at this example:

Hash Key	Hashing Function	Hash Value
"John Thompson"	Apply Hashing Function	Hash Value=9

We can now search the hashing table and can see that there is no entry for Hash Value=9, therefore that data doesn't exist and we didn't have to search through all the data to prove this.

Hashing Algorithms

We know that a hash is supposed to be repeatable, that means each time we apply it to the same data we should get the same hash value out. This requires that we create a hashing algorithm or function:

Take a look at this (if you've forgotten how MOD works, go check it out!)

hashKey MOD 6

If we apply this to the following list of hash keys:

Hash Key	Hashing Algorithm	Hashing Value
12345	12345 MOD 6	3
67564	67564 MOD 6	4
34237	34237 MOD 6	1
23423	23423 MOD 6	5
00332	00332 MOD 6	2

Once we have calculated the Hash Values we can start to build the Hashing Table, notice because we are using MOD 6 we have 6 different possible Hashing Values:

Hashing Value	Hashing Key
0
1	34237
2	00332
3	12345
4	67564
5	23423

Now if you were asked whether the hashing key 23448 was a member of the data you have been given you would do the following:

1. Use the Hashing Key, apply the hashing algorithm and calculate the hashing value
2. Check for the hashing value in the hashing table
3. If it exists, you have found the data, if it doesn't the data isn't there

23448 MOD 6 = 0
Nothing attached to 0 in the hashing table
Therefore 23448 isn't stored

Exercise: Hashing tables Create a hashing table for the following hashing keys and hashing algorithm: HashKey MOD 8 Hashing Key 0353 8996 2530 6413 9119 3931 Answer : Hashing Value Hashing Key 0 1 0353 2 2530 3 3931 4 8996 5 6413 6 7 9119 Create a hashing table for the following hashing keys and hashing algorithm: (HashKey + 12) MOD 8 Hashing Key 12345 04187 34237 23423 00324 23448 Answer : Hashing Value Hashing Key 0 00324 1 34237 2 3 23423 4 23448 5 12345 6 7 04187 Can you find the hashing key 3245 stored in the following hashing table, built on the hashing algorithm: ((HashKey + 67)) MOD 8: Hashing Value Hashing Key 0 1 3... 2 3 3... 4 3... 5 2... 6 7 3... Answer : No. As (3245 + 67) MOD 8 = 0, and there is no data stored against that key in the Hashing Table Describe the following: Hashing Key Hashing Algorithm Hashing Value Answer : All of them – everything is done by consensus. Describe how you create a hashing table Answer : All of them – everything is done by consensus. Explain how you using hashed values to check if something exists: Answer : All of them – everything is done by consensus.

Collisions

Collision - When two or more hash keys result in the same hash value

Perfect Hashing	Colliding Keys
A perfect hash function for the four names shown	A hash function that maps names to integers from 0 to 15.. There is a collision between keys "John Smith" and "Sandra Dee".

You might have already noticed this, what happens when we run out of unique hashing values, when two hashing keys give the same hashing value? Take a look at the final row of the following example, built on the hashing algorithm of HashKey MOD 6:

Hash Key	Hashing Algorithm	Hashing Value
12345	12345 MOD 6	3
67564	67564 MOD 6	4
34237	34237 MOD 6	1
23423	23423 MOD 6	5
00332	00332 MOD 6	2
00338	00338 MOD 6	2 !!! Collision!

When two hash keys result in the same hash value this is called a Collision. This causes a problem as we can no longer quickly find whether data is in our hashing table or not, as another piece of data might have the same hashing value. There are several ways of solving this, we are going to look at two:

Open Hashing (Closed Addressing)

Hash collision resolved by open addressing with linear probing (interval=1). Note that "Ted Baker" has a unique hash, but nevertheless collided with "Sandra Dee" that had previously collided with "John Smith".

When two hash keys create the same hash value we place the colliding keys in next free hash value.

Closed Hashing (Open Addressing)

Hash collision by separate chaining with head records in the bucket array.

When two hash keys create the same hash value we place the colliding keys in the same location, by utilising a linked list to link together all the values that match that hashing value.

Uses of Hashing

Sending files

MD5

MD5("The quick brown fox jumps over the lazy dog")
= 9e107d9d372bb6826bd81d3542a419d6

Even a small change in the message will (with overwhelming probability) result in a mostly different hash:

MD5("The quick brown fox jumps over the lazy dog.")
= e4d909c290d0fb1ca068ffaddf22cbd0

Passwords

Some companies don't hash passwords, meaning that if a cracker gets into their system they can steal them. This is particularly bad when a user has the same password for multiple sites!

By hashing a password a company protects user information. Even if a cracker breaks in they don't have access to the plain text password.

When a user logs in the company doesn't store the plain text password anywhere, all they need is the hash key, this can then be used to see if the password is correct. The wrong password would produce a wrong hash key and the user wouldn't be allowed to log in.

Encryption

Hashing algorithms should do the following-

1. Have few collisions
2. Produce a wide range of hashed values
3. Produce the hashed output every time for the same input