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Hashing:     more books (56)

Design of Hashing Algorithms (Lecture Notes in Computer Science) by Josef Pieprzyk, Babak Sadeghiyan, 1994-01-07 Half a Mind: Hashing : The Outrageous Running Sport by Alice Johnson, 1990-04 Hashing Out Encryption Solutions.: An article from: Security Management by John N. Bumgarner, 2001-06-01 Hi-Tech, FDA still hashing out January '99 inspection.(Brief Article): An article from: Inspection Monitor Design and Analysis of Coalesced Hashing (International Monographs on Computer Science) by Jeffrey Scott Vitter, Wen-chin Chen, 1986-10-16 Things of Each Possible Relation Hashing Against One Another by Juliana Spahr, 2003-11 Perfect hashing for external files (Research report. University of Waterloo. Department of Computer Science) by M. V Ramakrishna, 1986 Internal hashing for dynamic and static tables by T. G Lewis, 1988 Deletion algorithms for coalesced hashing (Technical report / Brown University, Dept. of Computer Science) by Wen-Chin Chen, 1984 Technical report by D Murthy, 1988 Computational character processing: Character coding, input, output, synthesis, ordering, conversion, text compression, encryption, display hashing, literate programming : bibliography (Infolingua) by Conrad Sabourin, 1994 Robin Hood hashing (Research report. University of Waterloo. Department of Computer Science) by Pedro Celis, 1986 Analysis of some new variants of coalesced hashing (Techincal report / Brown University, Dept. of Computer Science) by Wen-Chin Chen, 1984 An experimental method of study for minimal perfect hashing function: Reciprocal hashing by Dusaneya Somsiri, 1987

lists with details

1. What Is Hashing? - A Definition From Whatis.com - See Also: Hash, Hash Function
   hashing is the transformation of a string of character s into a usually shorter fixedlength value or key that represents the original string.  
   http://searchsqlserver.techtarget.com/sDefinition/0,,sid87_gci212230,00.html
   
   Extractions: hashing Home SQL Server Definitions - Hashing SearchSQLServer.com Definitions (Powered by WhatIs.com) EMAIL THIS LOOK UP TECH TERMS Powered by: Search listings for thousands of IT terms: Browse tech terms alphabetically: A B C D ... Z - Hashing is the transformation of a string of character s into a usually shorter fixed-length value or key that represents the original string. Hashing is used to index and retrieve items in a database because it is faster to find the item using the shorter hashed key than to find it using the original value. It is also used in many encryption algorithms. As a simple example of the using of hashing in databases, a group of people could be arranged in a database like this: Abernathy, Sara Epperdingle, Roscoe Moore, Wilfred Smith, David (and many more sorted into alphabetical order) Each of these names would be the key in the database for that person's data. A database search mechanism would first have to start looking character-by-character across the name for matches until it found the match (or ruled the other entries out). But if each of the names were hashed, it might be possible (depending on the number of names in the database) to generate a unique four-digit key for each name. For example: 7864 Abernathy, Sara 9802 Epperdingle, Roscoe 1990 Moore, Wilfred 8822 Smith, David (and so forth)

2. Hash House Harrier Information
   Historical Information on the Hash House Harriers, compiled from various sources.  
   http://half-mind.com/Hashing/who.php
   
   Extractions: Navigating this site requires JavaScript. Use the Sitemap Harrier Net is also an excellent source of information on hashing. Hashing . . . it's a mixture of athleticism and sociability, hedonism and hard work; a refreshing break from the nine-to-five routine. Hashing is an exhilaratingly fun combination of running, orienteering, and partying, where bands of harriers and harriettes chase hares on eight-to-ten kilometer-long trails through town, country, jungle, and desert, all in search of exercise, camaraderie, and good times. aka the "Hash House." Hash House Harrier runs were patterned after the traditional British public school paper chase. A "hare" would be given a short head start to blaze a trail, marking his devious way with shreds of paper, soon to be pursued by a shouting pack of "harriers." Only the hare knew where he was going . . . the harriers followed his marks to stay on trail. Apart from the excitement of chasing down the wily hare, solving the hare's marks and reaching the end was its own reward, for there, thirsty harriers would find a tub of iced-down beer. Hashing died during World War II (Japanese occupying forces being notoriously opposed to civilian fun), but came back to life in the post-war years, spreading slowly through Singapore, Indonesia, Australia, and New Zealand, then exploding in popularity in the late 70s and early 80s. Today there are thousands of Hash House Harrier clubs in all parts of the world, complete with newsletters, directories, and regional and world hashing conventions.

3. What Is Hashing? - A Word Definition From The Webopedia Computer Dictionary
   This page describes the term hashing and lists other pages on the Web where you can find additional information.  
   http://www.webopedia.com/TERM/H/hashing.html
   
   Extractions: You are in the: Small Business Computing Channel ECommerce-Guide Small Business Computing Webopedia ... Refer-It Enter a word for a definition... ...or choose a computer category. choose one... All Categories Communications Computer Industry Companies Computer Science Data Graphics Hardware Internet and Online Services Mobile Computing Multimedia Networks Open Source Operating Systems Programming Software Standards Types of Computers Wireless Computing World Wide Web Home hashing Last modified: Tuesday, October 14, 2003 Producing hash values for accessing data or for security . A hash value (or simply hash ), also called a message digest , is a number generated from a string of text. The hash is substantially smaller than the text itself, and is generated by a formula in such a way that it is extremely unlikely that some other text will produce the same hash value. Hashes play a role in security systems where they're used to ensure that transmitted messages have not been tampered with. The sender generates a hash of the message, encrypts it, and sends it with the message itself. The recipient then decrypts both the message and the hash, produces another hash from the received message, and compares the two hashes. If they're the same, there is a very high probability that the message was transmitted intact.

4. Hash Functions And Block Ciphers
   A hash function for hash table lookup should be fast, and it should cause as few collisions as possible. If you know the keys you will be hashing before you  
   http://www.burtleburtle.net/bob/hash/
   
   Extractions: I have a lot of material related to hashing. Functions: Tests (used to choose those functions): Analysis: A hash function for hash table lookup should be fast, and it should cause as few collisions as possible. If you know the keys you will be hashing before you choose the hash function, it is possible to get zero collisions this is called perfect hashing . Otherwise, the best you can do is to map an equal number of keys to each possible hash value and make sure that similar keys are not unusually likely to map to the same value.

5. What Is Hashing?
   hashing . . . it s a mixture of athleticism and sociability, hedonism and hard work, a refreshing escape from the nineto-five dweebs you re stuck with five  
   http://onin.com/hhh/hhhexpl.html
   
   Extractions: Hashing . . . it's a mixture of athleticism and sociability, hedonism and hard work, a refreshing escape from the nine-to-five dweebs you're stuck with five days a week. Hashing is an exhilaratingly fun combination of running, orienteering, and partying, where bands of harriers and harriettes chase hares on eight-to-ten kilometer-long trails through town, country, and desert, all in search of exercise, camaraderie, and good times. Hashing began in Kuala Lumpur, Malaysia, in 1938, when a group of British colonial officials and expatriates founded a running club called the Hash House Harriers. They named the group after their meeting place, the Selangor Club, nicknamed the "Hash House." Hash House Harrier runs were patterned after the traditional British paper chase. A "hare" was given a head start to blaze a trail, marking his devious way with shreds of paper, all the while pursued by a shouting pack of "harriers." Only the hare knew where he was going . . . the harriers followed his clues to stay on trail. Apart from the excitement of chasing the hare and solving the clues, reaching the end was its own reward . . . for there, thirsty harriers would find a tub of iced-down beer. Hashing died out during World War II (Japanese occupying forces being notoriously anti-fun) but picked up in the post-war years, spreading through the Far East, Australia, and New Zealand . . . then exploding in popularity in the mid-70s. Today there are thousands of Hash House Harrier clubs in all parts of the world, with newsletters, directories, and even regional and world hashing conventions.

6. Text* Snippets: Hashing Code
   A simple hash function from Robert Sedgwicks Algorithms in C book. I ve added some simple optimizations to the algorithm in order to speed up its hashing  
   http://textsnippets.com/user/wastepixel/tag/hashing

7. Hashing?
   So you re interested in hashing. Maybe it s because you ve seen strange flour markings on roads and trails in the Pikes Peak region (arrows, circles,  
   http://harrier.net/primer/hashing.html
   
   Extractions: A cross-country runner. Hashing? So you're interested in hashing. Maybe it's because you've seen strange flour markings on roads and trails in the Pikes Peak region (arrows, circles, and the such), or you've noticed a group of people on a Saturday afternoon senselessly running in Monument Creek or through Chapel Hills Mall. Most likely, it's because a hasher's silver tongue convinced you to consider the sport. In any event, welcome to the Pikes Peak Hash House Harriers and Harriettes (P2H4). Variously described as "the lunatic fringe of running" and "the drinking club with a running problem," the Hash House Harriers are a worldwide group with some 350 chapters in the United States, including a dozen in Colorado. Our premise is simple, one harrier (the hare) lays a trail of flour over a course (s)he chooses. The other harriers (the hounds) try to follow that trail to the end where we enjoy munchies and beer (or soft drinks for those disinclined to imbibe). The typical hash is 3-5 miles over hill and dale, through suburbs, woods, malls, et al. The hash isn't a race - no prizes to the swift. Following the trail is the challenge, camaraderie and beverages are the rewards.

8. Hashing, Hash Tables, And Scatter Tables
   hashing, Hash Tables, and Scatter Tables. A very common paradigm in data processing involves storing information in a table and then later retrieving the  
   http://www.brpreiss.com/books/opus5/html/page205.html
   
   Extractions: Data Structures and Algorithms with Object-Oriented Design Patterns in Java A very common paradigm in data processing involves storing information in a table and then later retrieving the information stored there. For example, consider a database of driver's license records. The database contains one record for each driver's license issued. Given a driver's license number, we can look up the information associated with that number. Similar operations are done by the Java compiler. The compiler uses a symbol table to keep track of the user-defined symbols in a Java program. As it compiles a program, the compiler inserts an entry in the symbol table every time a new symbol is declared. In addition, every time a symbol is used, the compiler looks up the attributes associated with that symbol to see that it is being used correctly and to guide the generation of the bytecodes Typically the database comprises a collection of key-and-value pairs. Information is retrieved from the database by searching for a given key. In the case of the driver's license database, the key is the driver's license number and in the case of the symbol table, the key is the name of the symbol. In general, an application may perform a large number of insertion and/or look-up operations. Occasionally it is also necessary to remove items from the database. Because a large number of operations will be done we want to do them as quickly as possible.

9. Hashing
   A filing cabinet is a reallife example of hashing. hashing is the algorithmic equivalent of the old saying, “A place for everything, and everything in its  
   http://www.tidbits.com/matt/rbd/hash.html
   
   Extractions: ByMatt Neuburg Matt Neuburg is the author of REALbasic: The Definitive Guide , and a member of the editorial board of REALbasic Developer . This article was originally published in REALbasic Developer Issue 1.4 (Feb/March 2003). Figure 1: Hash pigeonholes consisting of linked lists Here, then, is our hash function, which transforms a string into a number by multiplying its first and last character values: SimpleHashValue: Function simpleHashValue(word as string) As integer dim startasc, endasc as integer startasc = asc(mid(word,1,1)) endasc = asc(mid(word,len(word),1)) return (startasc*endasc) End Function Store: Figure 2: A depressingly bad distribution of data into pigeonholes We can achieve much better hashing performance by turning to the pros for help. Here is a highly sophisticated hash function by the computer scientist Peter J. Weinberger: SmartHashValue Using the same test case, this distributes the 4000 distinct words into nearly 3500 pigeonholes in an extremely even fashion, with just one or two words in most pigeonholes, and no pigeonhole containing more than 4 words. Store (the Dictionary version): Sub store(word as string) dim ct as integer if dict.hasKey(word) then ct = dict.value(word) ct = ct + 1 dict.value(word) = ct else dict.value(word) = 1 end End Sub

10. PHP Security Consortium: Password Hashing
    In this article I m going to cover password hashing, a subject which is often poorly understood by newer developers. Recently I ve been asked to look at  
    http://phpsec.org/articles/2005/password-hashing.html
    
    Extractions: Home About Articles Contact ... Projects Articles Article List In this article I'm going to cover password hashing, a subject which is often poorly understood by newer developers. Recently I've been asked to look at several web applications which all had the same security issue - user profiles stored in a database with plain text passwords. Password hashing is a way of encrypting a password before it's stored so that if your database gets into the wrong hands, the damage is limited. Hashing is nothing new - it's been in use in Unix system password files since long before my time, and quite probably in other systems long before that. In this article I'll explain what a hash is, why you want to use them instead of storing real passwords in your applications, and give you some examples of how to implement password hashing in PHP and MySQL. As you read on you'll see that I advocate the use of a hashing algorithm called Secure Hashing Algorithm 1 (or SHA-1). Since I wrote this article, a team of researchers - Xiaoyun Wang, Yiqun Lisa Yin, and Hongbo Yu - have shown SHA-1 to be weaker than was previously thought. This means that for certain purposes such as digital signatures, stronger algorithms like SHA-256 and SHA-512 are now being recommended. For generating password hashes, SHA-1 still provides a more than adequate level of security for most applications today. You should be aware of this issue however and begin to think about using stronger algorithms in your code as they become more readily available.

11. Hashing
    Basically hashing is a form of noncompetitive cross-country running with the main objective of working up a decent thirst. Great emphasis is placed on the  
    http://www.cix.co.uk/~bicesterh3/uk/hashing.htm
    
    Extractions: How It All Started... A brief look at the origins of this world-wide organisation. A Guide for New Feet If you would like to try hashing you might find this useful. Or not! Hash Hints A few words of advice before you begin... A Guide for Hares Some hints for the not quite so new hasher in the UK. More about Hashing Other sources of information on hashing: magazines, on-line mailing lists, etc Wikipedia on Hashing

12. Hash Search Function - The GNU C Library
    The hcreate function creates a hashing table which can contain at least nel elements. There is no possibility to grow this table so it is necessary to  
    http://www.gnu.org/software/libc/manual/html_node/Hash-Search-Function.html
    
    Extractions: : Tree Search Function , Previous: Search/Sort Example , Up: Searching and Sorting The functions mentioned so far in this chapter are for searching in a sorted or unsorted array. There are other methods to organize information which later should be searched. The costs of insert, delete and search differ. One possible implementation is using hashing tables. The following functions are declared in the header file search.h hcreate size_t nel The hcreate function creates a hashing table which can contain at least nel elements. There is no possibility to grow this table so it is necessary to choose the value for nel The weakest aspect of this function is that there can be at most one hashing table used through the whole program. The table is allocated in local memory out of control of the programmer. As an extension the GNU C library provides an additional set of functions with an reentrant interface which provide a similar interface but which allow to keep arbitrarily many hashing tables. It is possible to use more than one hashing table in the program run if the former table is first destroyed by a call to hdestroy The function returns a non-zero value if successful. If it return zero something went wrong. This could either mean there is already a hashing table in use or the program runs out of memory.

13. AustinH3
    Provides pictures, hashing statistics, a calendar of events, news items, meeting minutes, and related links.  
    http://www.austinh3.org/
    
    Extractions: - To persuade older members that they are not as old as they feel Upcoming Events February 2008 NOH3 Mardi Gras Madness XVIII Snow Down Hash 2008 Mardi Gras Hill Country H3 7th Aanl Red Dress Run ICBINMH3 2nd Analversary March 2008 Interhash 2008 - Perth ... Colorado Invihash 2008 Subscribe to AustinH3

14. MySQL AB :: MySQL 5.0 Reference Manual :: 5.4.9 Password Hashing As Of MySQL 4.1
    When a client attempts to connect to the server, there is an initial authentication step in which the client must present a password that has a hash value  
    http://dev.mysql.com/doc/mysql/en/Password_hashing.html
    
    Extractions: Additional languages MySQL 5.0 Reference Manual 5 MySQL Server Administration ... 5.4 The MySQL Access Privilege System :: 5.4.9 Password Hashing as of MySQL 4.1 Section Navigation Toggle MySQL user accounts are listed in the user table of the mysql database. Each MySQL account is assigned a password, although what is stored in the Password column of the user table is not the plaintext version of the password, but a hash value computed from it. Password hash values are computed by the function.

15. Hashing Animation Tool
    Trouble viewing the applet? Click for Operating Requirements.  
    http://www.engin.umd.umich.edu/CIS/course.des/cis350/hashing/WEB/HashApplet.htm

16. Hashing Lecture 21
    The basics of hashing is to apply a function to the search key so we can determine where the item is without looking at the other items.  
    http://www.cs.sunysb.edu/~skiena/214/lectures/lect21/lect21.html
    
    Extractions: Lecture 21 Steven S. Skiena Hashing One way to convert form names to integers is to use the letters to form a base ``alphabet-size'' number system: To convert ``STEVE'' to a number, observe that e is the 5th letter of the alphabet, s is the 19th letter, t is the 20th letter, and v is the 22nd letter. Thus ``Steve'' Thus one way we could represent a table of names would be to set aside an array big enough to contain one element for each possible string of letters, then store data in the elements corresponding to real people. By computing this function, it tells us where the person's phone number is immediately!! What's the Problem? Because we must leave room for every possible string, this method will use an incredible amount of memory. We need a data structure to represent a sparse table , one where almost all entries will be empty. We can reduce the number of boxes we need if we are willing to put more than one thing in the same box! Example: suppose we use the base alphabet number system, then take the remainder Now the table is much smaller, but we need a way to deal with the fact that more than one, (but hopefully every few) keys can get mapped to the same array element.

17. Hawaii Hashing Gateway
    also includes Hawaii Full Moon Hash House Harriers, Oahu Pick Up Hash House Harriers, Kukini Nui Hash House Harriers, Burnt Rubber Hash House Harriers,  
    http://alohah3.org/

18. Ha.ckers.org Web Application Security Lab - Archive » Detecting Hashing Algorith
    All that we do is take the plaintext password, apply the various hashing Eventually, we may add optional salts, and many more hashing algorithms and  
    http://ha.ckers.org/blog/20070929/detecting-hashing-algorithms/
    
    Extractions: De-anonymizing Tor and Detecting Proxies Webappsec Crisis Management After reading the thread on sla.ckers If you have the password and the hash, you can input it into hashmaster digg_title = "Detecting Hashing Algorithms"; digg_bgcolor = '#FFFFFF'; digg_skin = 'compact'; This entry was posted on Saturday, September 29th, 2007 at 11:08 am and is filed under Webappsec . You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response , or trackback from your own site. thornmaker Says: September 29th, 2007 at 1:36 pm Interesting idea, this could be expanded a lot more. How about adding simple decryption schemes (so if a hash is, lets say hex encrypted you still can match it) and you should add (even) more hashing algorithms. Does the 0.2 indicate this tool will get some updates in the future?

19. Hashing Files - Encryption, Hashing, File Shredding Utility. Program To Hide Any
    hashing Files Encryption, hashing, file shredding utility. Program to hide any number of files/folders.  
    http://hashing-files.qarchive.org/
    
    Extractions: Smart program! Easy to use, simple and works like expected. If folders are needed to be hid other than the "obvious" windows way, then this is the program to be... Hide Files allows you to select any folders (and sub folders with all files) of your choice to protect them as hidden. You can drag-and-drop the desired files/folders from Explorer into the Hide Files window. In one mouse click they become invisible. Once files or folders are hidden, it is impossible to find them, or access and remove any file. Unhiding files or folders is as easy as hiding them - just one mouse click and they are visible again. var template = "728x90"; var adblockBorderStyle = "border:#FFFFFF 1px solid"; var adblockTitleColor = "#FF0000"; var adblockBackgroundColor = "#FFFFFF"; var adblockTextColor = "#333333"; var adblockURLColor = "#FF0000"; var userKeyword = ""; var aid = "12028"; var said = "";

20. RFC 2104 (rfc2104) - HMAC: Keyed-Hashing For Message Authentication
    RFC 2104 HMAC Keyed-hashing for Message Authentication.  
    http://www.faqs.org/rfcs/rfc2104.html
    
    Extractions: RFC 2104 (RFC2104) Internet RFC/STD/FYI/BCP Archives RFC Index RFC Search Usenet FAQs Web FAQs ... Cities Alternate Formats: rfc2104.txt rfc2104.txt.pdf RFC 2104 - HMAC: Keyed-Hashing for Message Authentication RFC 1826 , August 1995. [BCK1] M. Bellare, R. Canetti, and H. Krawczyk, "Keyed Hash Functions and Message Authentication", Proceedings of Crypto'96, LNCS 1109, pp. 1-15. ( http://www.research.ibm.com/security/keyed-md5.html ) [BCK2] M. Bellare, R. Canetti, and H. Krawczyk, "Pseudorandom Functions Revisited: The Cascade Construction", Proceedings of FOCS'96. [Dobb] H. Dobbertin, "The Status of MD5 After a Recent Attack", RSA Labs' CryptoBytes, Vol. 2 No. 2, Summer 1996. http://www.rsa.com/rsalabs/pubs/cryptobytes.html [PV] B. Preneel and P. van Oorschot, "Building fast MACs from hash functions", Advances in Cryptology CRYPTO'95 Proceedings, Lecture Notes in Computer Science, Springer-Verlag Vol.963, 1995, pp. 1-14. [MD5] Rivest, R., "The MD5 Message-Digest Algorithm", RFC 1321 , April 1992. [MM] Meyer, S. and Matyas, S.M., Cryptography, New York Wiley, 1982. [RIPEMD] H. Dobbertin, A. Bosselaers, and B. Preneel, "RIPEMD-160: A strengthened version of RIPEMD", Fast Software Encryption, LNCS Vol 1039, pp. 71-82.

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