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Hashing allows us to map data of arbitrary length to data of fixed length. If we consider a table that contains thousands of objects, searching for a particular object could have a significant runtime cost if the objects require complex comparisons. Binary search would reduce that cost, however the cost of sorting the objects and then maintaining the order can be just as significant. Instead, we use a hash table.
With a suitable hashing function, any object can be reduced to a single value. The range of output values is usually much smaller than the range of input values, thus two or more objects may well produce the same hash value. However, with an appropriate hash function, objects can be evenly distributed throughout the range of hash values. If we suppose that a single hash might be associated with up to n objects, then the size of the hash table will be up to n times smaller than the object table and can therefore be sorted and maintained n times more quickly than the object table. We then only need to sort n objects per hash to create an efficient hash lookup table.
To search for an individual object, we pass the object through the hash function to obtain its hash and then search the hash table using a trivial binary search. If the hash exists (with a fixed-length table it is guaranteed to exist), we then use the more complex object comparisons to binary search the n objects associated with that hash value. The end result is that we narrow the search down to a much smaller subset of objects, thus significantly reducing the cost of searching.
Hashing has other uses, particularly in cryptography. While it is possible to reverse engineer a hash value to produce n possible values for a given hash, cryptographic hashing is one-way only; we cannot use the hash to reproduce the input. Thus instead of storing passwords, we need only store the hashes produced by those passwords. Even knowing the precise implementation details of the hashing function won't help an attacker because in order to produce a particular hash value you'd still need to know which input actually produces it and that means testing each potential input individually. Doing it for just one input is hard enough, but doing it for two or more is nigh-on impossible (usernames, IP addresses, secret questions and answers and all other security information can also be hashed).
What else can I help you with?
What is hashing function in data structure?
If you read up on hashing, why hashing is done, what are its uses. Then you will be able to answer your own question. More to the point you will have studied the material that your homework question is intended to make you study. It is educational.
What are hashing techniques that allow dynamic file expansion in dbms?
Dynamic hashing techniques, such as Extendible Hashing and Linear Hashing, allow for efficient file expansion in database management systems (DBMS). Extendible Hashing uses a directory structure that can grow as needed, allowing new buckets to be created without reorganizing existing data. Linear Hashing incrementally splits buckets based on a predetermined growth factor, enabling dynamic adjustment of the hash structure while maintaining efficient access. These techniques help manage variable data sizes and maintain performance as data volume changes.
Define hashing and describe briefly including types of hashing and where it is used and advantages and disadvantages of hashing?
Hashing is performed on arbitrary data by a hash function. A hash function is any function that can convert data to either a number or an alphanumeric code. There are possibly as many types of hashing as there are data. How precisely the hash function works depends on what data it is meant to generate a hash code from. Hashing is used for a variety of things. For example, a hash table is a data structure used for storing data in memory. Instead of iterating through the structure to find a specific item, we associate a key (hash code) to a particular item (data). A hash code can be generated from a file or disk image. If the data does not match the code, then the data is assumed to be corrupted. Hashing has the advantage of taking a larger amount of data and representing it as a smaller amount of data (hash code). The code generated is unique to the data it came from. Generating a hash code can take time however, depending on the function and the data. Some hash functions include Bernstein hash, Fowler-Noll-Vo hash, Jenkins hash, MurmurHash, Pearson hashing and Zobrist hashing.
What is Homomorphic Hashing?
Homomorphic Hashing is a algorithm technique used for verifying data.
What is double hashing in data structure?
if collision is occurred in hash function then we can solve this problem by using double hash function
How does bucket hashing work to efficiently distribute data into different buckets based on a specific hashing function?
Bucket hashing works by using a hashing function to assign each data item to a specific bucket. The hashing function calculates a unique hash value for each item, which determines the bucket it belongs to. This helps distribute the data evenly across different buckets, making it easier to retrieve and manage the data efficiently.
Why do you use hashing and not array?
Hashing provides a method to search for data.Hashing provides a method to search for data.Hashing provides a method to search for data.Hashing provides a method to search for data.
How does hashing work in computer science and what are its applications in data security and encryption?
Hashing in computer science involves taking input data and generating a fixed-size string of characters, known as a hash value, using a specific algorithm. This hash value is unique to the input data and is used for various purposes, including data security and encryption. In data security, hashing is used to verify the integrity of data by comparing hash values before and after transmission or storage. If the hash values match, it indicates that the data has not been tampered with. Hashing is also used in password storage, where passwords are hashed before being stored in a database to protect them from unauthorized access. In encryption, hashing is used to securely store sensitive information, such as credit card numbers or personal data. Hashing algorithms are also used in digital signatures to verify the authenticity of a message or document. Overall, hashing plays a crucial role in data security and encryption by providing a way to securely store and verify data integrity.
Where and in which area can the data structure concepts be used?
You use a data structure when you have data to store and:You have more data than you can store in an arrayYou want to be able to find it efficientlyYou want to be able to organise it in different ways
What does hashing mean and how is it used in computer science and cryptography?
Hashing is a process in computer science and cryptography where data is converted into a fixed-size string of characters, known as a hash value. This hash value is unique to the input data and is used for various purposes such as data retrieval, data integrity verification, and password storage. In cryptography, hashing is used to securely store passwords and verify data integrity by comparing hash values.
Explain the distinction between closed an open hashing Discuss the relative merits of each technique in database application?
A hash table is where data storage for a key-value pair is done by generating an index using a hash function. Open Hashing (aka Separate chaining) is simpler to implement, and more efficient for large records or sparse tables. Closed Hashing (aka Open Addressing) is more complex but can be more efficient, especially for small data records.
What are data models in dbms?
A data model is a collection of concepts that can be used to describe the structure of a database. Data models can be broadly distinguished into 3 main categories- 1)high-level or conceptual data models (based on entities & relationships) It provides concepts that are close to the way many users perceive data. 2)lowlevel or physical data models It provides concepts that describe the details of how data is stored in the computer. These concepts are meant for computer specialist, not for typical end users. 3)representational or implementation data models (record-based,object-oriented) It provide concepts that can be understood by end users. These hide some details of data storage but can be implemented on a computer system directly.
