Operating System Security Fundamentals
... – Use a consistent naming convention – Always provide a password to an account and force the user to change it at the first logon – Protect passwords – Do not use default passwords ...
... – Use a consistent naming convention – Always provide a password to an account and force the user to change it at the first logon – Protect passwords – Do not use default passwords ...
Chapter 27 Hashing Why Hashing? Objectives Map
... A map is a data structure that stores entries. Each entry contains two parts: key and value. The key is also called a search key, which is used to search for the corresponding value. For example, a dictionary can be stored in a map, where the words are the keys and the definitions of the words are t ...
... A map is a data structure that stores entries. Each entry contains two parts: key and value. The key is also called a search key, which is used to search for the corresponding value. For example, a dictionary can be stored in a map, where the words are the keys and the definitions of the words are t ...
In-memory hash tables for accumulating text vocabularies
... a threshold of 2.0. The reason for this is, perhaps, surprising: it appears that a significant additional cost is that the compiler cannot optimise the code as well with a variable table size. In these experiments we restricted table sizes to be powers of 2 so that bitmasks could be used in place of ...
... a threshold of 2.0. The reason for this is, perhaps, surprising: it appears that a significant additional cost is that the compiler cannot optimise the code as well with a variable table size. In these experiments we restricted table sizes to be powers of 2 so that bitmasks could be used in place of ...
CPSC 335 - University of Calgary
... keys. Also, the simple operations tries use during lookup, such as array indexing using a character, are fast on real machines. Tries can require less space when they contain a large number of short strings, because the keys are not stored explicitly and nodes are shared between keys with common ini ...
... keys. Also, the simple operations tries use during lookup, such as array indexing using a character, are fast on real machines. Tries can require less space when they contain a large number of short strings, because the keys are not stored explicitly and nodes are shared between keys with common ini ...
213-Hashing
... An unsuccessful search costs the same as insertion. The cost of a successful search of X is equal to the cost of inserting X at the time X was inserted. For λ = 0.5 the average cost of insertion is 2.5. The average cost of finding the newly inserted item will be 2.5 no matter how many insertio ...
... An unsuccessful search costs the same as insertion. The cost of a successful search of X is equal to the cost of inserting X at the time X was inserted. For λ = 0.5 the average cost of insertion is 2.5. The average cost of finding the newly inserted item will be 2.5 no matter how many insertio ...
Hashing - METU OCW
... can always be found, but the time to do so can get quite large. • Worse, even if the table is relatively empty, blocks of occupied cells start forming. • This effect is known as primary clustering. • Any key that hashes into the cluster will require several attempts to resolve the collision, and the ...
... can always be found, but the time to do so can get quite large. • Worse, even if the table is relatively empty, blocks of occupied cells start forming. • This effect is known as primary clustering. • Any key that hashes into the cluster will require several attempts to resolve the collision, and the ...
Hashing
... can always be found, but the time to do so can get quite large. • Worse, even if the table is relatively empty, blocks of occupied cells start forming. • This effect is known as primary clustering. • Any key that hashes into the cluster will require several attempts to resolve the collision, and the ...
... can always be found, but the time to do so can get quite large. • Worse, even if the table is relatively empty, blocks of occupied cells start forming. • This effect is known as primary clustering. • Any key that hashes into the cluster will require several attempts to resolve the collision, and the ...
Hashing - METU Computer Engineering
... can always be found, but the time to do so can get quite large. • Worse, even if the table is relatively empty, blocks of occupied cells start forming. • This effect is known as primary clustering. • Any key that hashes into the cluster will require several attempts to resolve the collision, and the ...
... can always be found, but the time to do so can get quite large. • Worse, even if the table is relatively empty, blocks of occupied cells start forming. • This effect is known as primary clustering. • Any key that hashes into the cluster will require several attempts to resolve the collision, and the ...
Hashing
... • An unsuccessful search costs the same as insertion. • The cost of a successful search of X is equal to the cost of inserting X at the time X was inserted. • For λ = 0.5 the average cost of insertion is 2.5. The average cost of finding the newly inserted item will be 2.5 no matter how many insertio ...
... • An unsuccessful search costs the same as insertion. • The cost of a successful search of X is equal to the cost of inserting X at the time X was inserted. • For λ = 0.5 the average cost of insertion is 2.5. The average cost of finding the newly inserted item will be 2.5 no matter how many insertio ...
Dictionaries and Hash Tables
... insertions and removals on a hash table take O(n) time The worst case occurs when all the keys inserted into the dictionary collide The load factor a = n/N affects the performance of a hash table Assuming that the hash values are like random numbers, it can be shown that the expected number of probe ...
... insertions and removals on a hash table take O(n) time The worst case occurs when all the keys inserted into the dictionary collide The load factor a = n/N affects the performance of a hash table Assuming that the hash values are like random numbers, it can be shown that the expected number of probe ...
CSE 331. Computer Organization
... Associative access can be realized by sequential scanning, which happens for complicated queries. ...
... Associative access can be realized by sequential scanning, which happens for complicated queries. ...
hash 2 (x)
... • Since TableSize is prime and i and j are distinct (also less than floor(TableSize)), this is not possible. It follows that the first M/2 alternative are all distinct, and an insertion must succeed if the table is at least half full. Izmir University of Economics ...
... • Since TableSize is prime and i and j are distinct (also less than floor(TableSize)), this is not possible. It follows that the first M/2 alternative are all distinct, and an insertion must succeed if the table is at least half full. Izmir University of Economics ...
Chapter 12: Dictionary (Hash Tables)
... name into an integer index value, then use this value to index into a table. This is faster than an ordered data structure, indeed almost as fast as a subscript calculation. What Amy has discovered is called a perfect hash function. A hash function is a function that takes as input an element and r ...
... name into an integer index value, then use this value to index into a table. This is faster than an ordered data structure, indeed almost as fast as a subscript calculation. What Amy has discovered is called a perfect hash function. A hash function is a function that takes as input an element and r ...
Symbol Tables - Lehigh CORAL
... With a hash function, we can use a very efficient arraybased implementation to store items in the table. ...
... With a hash function, we can use a very efficient arraybased implementation to store items in the table. ...
Password Security
... Disclaimer: These links are provided because they have information that may be useful. The Center for Internet Security (CIS) does not warrant the accuracy of any information contained in the links and neither endorses nor intends to promote the advertising of the resources listed herein. The opinio ...
... Disclaimer: These links are provided because they have information that may be useful. The Center for Internet Security (CIS) does not warrant the accuracy of any information contained in the links and neither endorses nor intends to promote the advertising of the resources listed herein. The opinio ...
Design and Implementation of a High
... client: “OK, but to save bits, I will send a joint hash for 8 matches to check if all of them are correct” server: “apparently not all 8 are correct. Let’s back off” client: “OK, how about this joint hash for two matches?” ...
... client: “OK, but to save bits, I will send a joint hash for 8 matches to check if all of them are correct” server: “apparently not all 8 are correct. Let’s back off” client: “OK, how about this joint hash for two matches?” ...
slides
... Open Addressing • Basic idea (details in Section 12.4): – To insert: if slot is full, try another slot, …, until an open slot is found (probing) – To search, follow same sequence of probes as would be used when inserting the element • If reach element with correct key, return it • If reach a NULL p ...
... Open Addressing • Basic idea (details in Section 12.4): – To insert: if slot is full, try another slot, …, until an open slot is found (probing) – To search, follow same sequence of probes as would be used when inserting the element • If reach element with correct key, return it • If reach a NULL p ...
csci 210: Data Structures Maps and Hash Tables
... • Chaining is easiest to implement and does not need guessing n • rule of thumb: load factor < .9 for O(1) performance, but not vital • Hashing can provide better performance than binary search trees if the keys are sufficiently random so that a good hash function can be developed ...
... • Chaining is easiest to implement and does not need guessing n • rule of thumb: load factor < .9 for O(1) performance, but not vital • Hashing can provide better performance than binary search trees if the keys are sufficiently random so that a good hash function can be developed ...
Problem Solving
... field that is computed on creation and kept up to date as the database is updated • By using the index, the database software is able to quickly retrieve the record given the field value ...
... field that is computed on creation and kept up to date as the database is updated • By using the index, the database software is able to quickly retrieve the record given the field value ...
Priority Queues and Hashing
... Each node holds information about how many nodes are there in its right and left subtrees. You can use this information to put a new node into the subtree that has fewer elements. Clearly, when inserting a new value in a new node, you also have to update these counters. If you have found out where t ...
... Each node holds information about how many nodes are there in its right and left subtrees. You can use this information to put a new node into the subtree that has fewer elements. Clearly, when inserting a new value in a new node, you also have to update these counters. If you have found out where t ...
LinkedDateStructure-PartB
... May have to search entire list On average would expect to search half of the list, or n/2 In big-O notation, this is O(n) ...
... May have to search entire list On average would expect to search half of the list, or n/2 In big-O notation, this is O(n) ...
Rainbow table
A rainbow table is a precomputed table for reversing cryptographic hash functions, usually for cracking password hashes. Tables are usually used in recovering a plaintext password up to a certain length consisting of a limited set of characters. It is a practical example of a space/time trade-off, using less computer processing time and more storage than a brute-force attack which calculates a hash on every attempt, but more processing time and less storage than a simple lookup table with one entry per hash. Use of a key derivation function that employs a salt makes this attack infeasible.Rainbow tables are an application of an earlier, simpler algorithm by Martin Hellman.