Hashing and you

Nov 29, 2011Download as ppt, pdf

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Hashing is a technique for mapping data to a key that can be used for counting, caching, searching and finding similarities in data. It works by assigning the same or similar keys to related data values. Hashing is commonly used to implement hash tables for efficient lookup, and to find duplicate data by counting occurrences of keys. However, care must be taken when using hashing for cryptography since weak hashing algorithms can enable birthday attacks that compromise security.

Hashing and You mixing it up with checksums, associative arrays and more http://en.wikipedia.org/wiki/File:Hashegg.jpg

What is "hashing"? Hashing literally means to "mix it up" hashing in the sense we are going to discuss is the simple mapping of data to a key, often times the key is simply the some trivially simple preconfigured arrangement, like the integers used in common array indexing schemes. So what are some of the uses of "hashes"...

Hashing Functions Forms trivial complex cryptography Application counting caching/searching heuristics

Counting... Hash tables can be used to count and find duplicates very cheaply due to the nature of their structure. ��You simply increment a key term. You can "massage" the keys first, like in the case of trivial differences like uppercase letters in words.

Caching... Hash tables are good for indexing and searching in general, and thus are good for keeping a cache table as well. The advantages of this are only shown as the datasets being searched, and thus indexed, are sufficiently large that you can no longer use a trivial hashing scheme.

Heuristics... hash tables can be used to find "similar" data cheaply for many of the same reasons it can be used to keep track of duplicate data. ��By assigning like keys to similar data you can then enumerate however you wish to see where patterns lie. It's for this same reason that you need to be careful NOT to do this for checksums and cryptography applications in general...

Birthday Paradox/Attack 23 people =~ 50% 57 people =~ 99% 200 people = 99.999999999% this is not intuitive to most people, but is due to the fact that no TWO people can have the SAME birthday, not choose some day and see if anyone has that SINGLE day in a year. Birthday Attacks Named due to the paradox. ��Various attacks based on weak hashing algorithms for wireless networks, digital signatures, man in the middle attacks, etc. ��

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Hashing and Hashtable, application of hashing, advantages of hashing, disadva...NaveenPeter8

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Hashing is a process that converts a key into a hash value using a hash function and mathematical algorithm. A good hash function uses a one-way hashing algorithm so the hash cannot be converted back to the original key. Hash tables store data in an array format using the hash value as an index, allowing very fast access if the index is known. Hashing provides constant-time search, insert, and delete operations on average and is widely used for applications like message digests, passwords, and data structures.

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This document provides a tutorial overview of hash table methods. It discusses calculating hash addresses to map records to table locations, handling collisions when multiple records hash to the same location, theoretical analyses of hash functions, alternatives to hashing, and areas for further research. The document aims to introduce programmers and students to hash tables for efficient searching of large files where search time is independent of file size.

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A hash table is a data structure that uses a hash function to map keys to unique indices in an underlying array. Collisions occur when two keys hash to the same index and must be resolved. Open addressing resolves collisions by probing through alternative array locations until an empty slot is found. Double hashing is an open addressing collision resolution technique that uses a secondary hash of the key as an offset when probing for the next index. Hash tables provide efficient lookup, insertion and deletion of key-value pairs and are used widely in applications like databases, caching and cryptography.

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This document discusses different searching methods like sequential, binary, and hashing. It defines searching as finding an element within a list. Sequential search searches lists sequentially until the element is found or the end is reached, with efficiency of O(n) in worst case. Binary search works on sorted arrays by eliminating half of remaining elements at each step, with efficiency of O(log n). Hashing maps keys to table positions using a hash function, allowing searches, inserts and deletes in O(1) time on average. Good hash functions uniformly distribute keys and generate different hashes for similar keys.

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This document discusses hash tables and their implementation. It begins by explaining that dictionaries map keys to values like arrays but allow any type for the key. It then discusses how dictionaries can be implemented using balanced binary search trees or hash tables. Hash tables offer constant-time lookup by using a hash function to map keys to array indices, but collisions must be handled when two keys hash to the same index. Various collision resolution techniques are presented like separate chaining, linear probing, and quadratic probing. The document provides examples and guidelines for choosing a hash function and table size to minimize collisions.

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Hashing and you

1. Hashing and You mixing it up with checksums, associative arrays and more http://en.wikipedia.org/wiki/File:Hashegg.jpg

2. What is "hashing"? Hashing literally means to "mix it up" hashing in the sense we are going to discuss is the simple mapping of data to a key, often times the key is simply the some trivially simple preconfigured arrangement, like the integers used in common array indexing schemes. So what are some of the uses of "hashes"...

3. Hashing Functions Forms trivial complex cryptography Application counting caching/searching heuristics

4. Counting... Hash tables can be used to count and find duplicates very cheaply due to the nature of their structure. ��You simply increment a key term. You can "massage" the keys first, like in the case of trivial differences like uppercase letters in words.

5. Caching... Hash tables are good for indexing and searching in general, and thus are good for keeping a cache table as well. The advantages of this are only shown as the datasets being searched, and thus indexed, are sufficiently large that you can no longer use a trivial hashing scheme.

6. Heuristics... hash tables can be used to find "similar" data cheaply for many of the same reasons it can be used to keep track of duplicate data. ��By assigning like keys to similar data you can then enumerate however you wish to see where patterns lie. It's for this same reason that you need to be careful NOT to do this for checksums and cryptography applications in general...

7. Birthday Paradox/Attack 23 people =~ 50% 57 people =~ 99% 200 people = 99.999999999% this is not intuitive to most people, but is due to the fact that no TWO people can have the SAME birthday, not choose some day and see if anyone has that SINGLE day in a year. Birthday Attacks Named due to the paradox. ��Various attacks based on weak hashing algorithms for wireless networks, digital signatures, man in the middle attacks, etc. ��

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Hashing and you

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