Hashing in Cybersecurity

Jul 26, 2024

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Hashing in Cybersecurity

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Division Hashing Modulo Hashing 02 01 Perfect Hashing Multiplication Hashing 03 07 HASHING & ITS TYPES Consistent Universal 06 04 Hashing Hashing 05 Cryptographic Hashing contact@learnovita.com www.learnovita.com

Hashing

Hashing. 0 1 2 3. Search Key. Black Box. n-3 n-2 n-1. A hash function must: Be relatively easy and quick to calculate. Evenly distribute the keys throughout the table. Be easily repeatable for Finds and Deletes. Deal with collisions. (Collision Resolutions).

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Hashing

COMP171. Hashing. Hashing …. Again, a (dynamic) set of elements in which we do ‘search’, ‘insert’, and ‘delete’ Linear ones: lists, stacks, queues, … Nonlinear ones: trees, graphs (relations between elements are explicit)

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Hashing

Hashing. Motivation. The primary goal is to locate the desired record in a single access of disk. Sequential search: O(N) B+ trees: O( log k N) Hashing: O(1) In hashing, the key of a record is transformed into an address and the record is stored at that address.

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Hashing

Hashing. Text Read Weiss, § 5.1 – 5.5 Goal Perform inserts, deletes, and finds in constant average time Topics Hash table, hash function, collisions Collision handling Separate chaining Open addressing: linear probing , quadratic probing , double hashing Rehashing

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Hashing

Hashing. A very efficient method for implementing a dictionary, i.e., a set with the operations: insert find delete Applications: databases symbol tables. Hash tables and hash functions. Hash table: an array with indices that correspond to buckets

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Hashing

Hashing . Chapter 10 . Comparison of keys was the main operation used by the previous discussed searching methods . There is a different way of searching by calculates the position of the key based on the value of the key. So, the search time is reduced to O(1) from O(n) or from O(log n).

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Hashing

Hashing. Michael Tsai 2012/05/29. 有沒有一種天方夜壇. (key, data). Insert. Search. Delete. =O(1). 神秘的資料結構. Hint: “ 以空間換取時間 ”. 很多很多有編號的櫃子. 概念. 問 : “ 菜瓜布 ” 的資料去哪找 ? (“ 菜瓜布 ”, 資料 ). 管理員. 管理員 : “ 菜瓜布 ” 對應到 1028 號櫃子. 1028. 如果箱子夠多 , 則花費在一個箱子裡面尋找的時間 =O(1). Hash table. 很多很多有編號的櫃子. 概念.

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Hashing in Action

Hashing in Action. Nattee Niparnan. Operation. Insert Depends on Find Delete Depends on Find, also. Find. Find a room that should contain the value. Simple Hash. Room index. Hash Function. Name. Trying to add. Add Alice. 1. Hash Function. Alice. Add Alice. 1. Hash Function.

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Hashing

Hashing. Dashiell Fryer CS 157B Dr. Lee. Contents. Static Hashing File Organization Properties of the Hash Function Bucket Overflow Indices Dynamic Hashing Underlying Data Structure Querying and Updating Comparisons Other types of hashing Ordered Indexing vs. Hashing.

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Hashing

Hashing. CS 105. Hashing - Introduction. In a dictionary, if it can be arranged such that the key is also the index to the array that stores the entries, searching and inserting items would be very fast Example: Empdata[1000], index = employee ID number

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Hashing

Hashing. Teoricamente, técnicas de hashing permitem acesso dinâmico aos dados (inserção/remoção/ recuperação) numa complexidade que independe do número N de registros do arquivo  O(1). Hashing estático. - para arquivos que não variam de tamanho. Função de hashing.

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Hashing

Hashing. It’s not just for breakfast anymore!. Hashing: the facts. Approach that involves both storing and searching for values Behavior is linear in the worst case, but strong competitor with binary searching in the average case

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Hashing

Hashing. Hashing is another method for sorting and searching data. Hashing makes it easier to add and remove elements from a data structure. The worst-case behavior for locating a key is linear – Q (n). Java’s standard hash table class is: java.util.Hashtable. Hashing.

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Hashing

Hashing. Search. Given: Distinct keys k 1 , k 2 , …, k n and collection T of n records of the form ( k 1 , I 1 ), ( k 2 , I 2 ), …, ( k n , I n ) where I j is the information associated with key k j for 1 <= j <= n .

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HASHING

HASHING. COL 106 Shweta Agrawal, Amit Kumar Slide Courtesy : Linda Shapiro, Uwash Douglas W. Harder, UWaterloo. The Need for Speed. Data structures we have looked at so far Use comparison operations to find items Need O(log N) time for Find and Insert

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Hashing

Hashing. Lesson Plan - 8. Contents. Evocation Objective Introduction General idea Hash Tables Types of Hashing Hash function Hashing methods Hashing algorithm Mind map Summary. ANNEXURE-I Evocation. Objective. To study the basic concept of hashing techniques and algorithm.

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Hashing

Hashing. Hashing. Many applications require I NSERT , S EARCH and D ELETE functions Hashing on average time can do all of these in O (1) Based on keys Falls under two general categories: Direct-Address Tables Hash Tables. Direct-Addressing. Good for when universe U of keys is small

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Hashing in Action

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Hashing, Hashing Tables

Hashing, Hashing Tables. Chapter 8. Class Hierarchy. Introduction. Definition: Key: a key is a field or composite of fields that uniquely identifies an entry in a table. Example. Table of students in a course sorted by name --------------------------------------------------------------

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Hashing

Hashing. Reference: Chapters: 11,12. Motivation. The primary goal is to locate the desired record in a single access of disk. Sequential search: O(N) B+ trees: O(log k N) Hashing: O(1) In hashing, the key of a record is transformed into an address and the record is stored at that address.

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Hashing

Hashing. Problem: store and retrieving an item using its key (for example, ID number, name). Linked List takes O(N) time Binary Search Tree take O(logN) time Array List take O(1) time. 0. 99999. Array. ID: 41 12041 Name: Somsri Faculty: Science. ID: 41 63490 Name: Sompong

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Hashing

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