Sunday, August 26, 2012


Data compression
In computer science and information theorydata compressionsource coding or bit-rate reduction is the process of encoding information using fewer bits than the original representation would use.
Compression is useful because it helps reduce the consumption of expensive resources, such as hard disk space or transmission bandwidth. On the downside, compressed data must be decompressed to be used, and this extra processing may be detrimental to some applications. For instance, a compression scheme for video may require expensive hardware for the video to be decompressed fast enough to be viewed as it is being decompressed (the option of decompressing the video in full before watching it may be inconvenient, and requires storage space for the decompressed video). The design of data compression schemes therefore involves trade-offs among various factors, including the degree of compression, the amount of distortion introduced (if using alossy compression scheme), and the computational resources required to compress and uncompress the data. Compression was one of the main drivers for the growth of information during the past two decades[1].

Lossless versus lossy compression
Lossless compression algorithms usually exploit statistical redundancy in such a way as to represent the sender's data more concisely without error. Lossless compression is possible because most real-world data has statistical redundancy. For example, in English text, the letter 'e' is much more common than the letter 'z', and the probability that the letter 'q' will be followed by the letter 'z' is very small. Another kind of compression, called lossy data compression or perceptual coding, is possible if some loss of fidelity is acceptable. Generally, a lossy data compression will be guided by research on how people perceive the data in question. For example, the human eye is more sensitive to subtle variations in luminance than it is to variations in color. JPEG image compression works in part by "rounding off" some of this less-important information. Lossy data compression provides a way to obtain the best fidelity for a given amount of compression.

Lossy image compression is used in digital cameras, to increase storage capacities with minimal degradation of picture quality. Similarly, DVDs use the lossy MPEG-2 Video codec for video compression.
In lossy audio compression, methods of psychoacoustics are used to remove non-audible (or less audible) components of the signal. Compression of human speech is often performed with even more specialized techniques, so that "speech compression" or "voice coding" is sometimes distinguished as a separate discipline from "audio compression". Different audio and speech compression standards are listed under audio codecs. Voice compression is used in Internet telephony for example, while audio compression is used for CD ripping and is decoded by audio players.

The Lempel–Ziv (LZ) compression methods are among the most popular algorithms for lossless storage. DEFLATE is a variation on LZ which is optimized for decompression speed and compression ratio, but compression can be slow. DEFLATE is used in PKZIPgzip and PNGLZW (Lempel–Ziv–Welch) is used in GIF images. Also noteworthy are the LZR (LZ–Renau) methods, which serve as the basis of the Zip method. LZ methods utilize a table-based compression model where table entries are substituted for repeated strings of data. For most LZ methods, this table is generated dynamically from earlier data in the input. The table itself is often Huffman encoded (e.g. SHRI, LZX). A current LZ-based coding scheme that performs well is LZX, used in Microsoft's CAB format.
The very best modern lossless compressors use probabilistic models, such as prediction by partial matching. The Burrows–Wheeler transform can also be viewed as an indirect form of statistical modelling.
In a further refinement of these techniques, statistical predictions can be coupled to an algorithm called arithmetic coding. Arithmetic coding, invented by Jorma Rissanen, and turned into a practical method by Witten, Neal, and Cleary, achieves superior compression to the better-known Huffman algorithm, and lends itself especially well to adaptive data compression tasks where the predictions are strongly context-dependent. Arithmetic coding is used in the bilevel image-compression standard JBIG, and the document-compression standard DjVu. The text entry system, Dasher, is an inverse-arithmetic-coder.
Lossless data compression
Lossless data compression is a class of data compression algorithms that allows the exact original data to be reconstructed from the compressed data. The term lossless is in contrast to lossy data compression, which only allows an approximation of the original data to be reconstructed, in exchange for better compression rates.
Lossless data compression is used in many applications. For example, it is used in the ZIP file format and in the Unix tool gzip. It is also often used as a component within lossy data compression technologies (e.g. lossless mid/side joint stereo preprocessing by the LAME MP3 encoder and other lossy audio encoders).
Lossless compression is used in cases where it is important that the original and the decompressed data be identical, or where deviations from the original data could be deleterious. Typical examples are executable programs, text documents and source code. Some image file formats, like PNG or GIF, use only lossless compression, while others like TIFF and MNG may use either lossless or lossy methods. Lossless audio formats are most often used for archiving or production purposes, with smaller lossy audio files being typically used on portable players and in other cases where storage space is limited and/or exact replication of the audio is unnecessary.

Lossless compression techniques
Most lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that "probable" (e.g. frequently encountered) data will produce shorter output than "improbable" data.
The primary encoding algorithms used to produce bit sequences are Huffman coding (also used by DEFLATE) and arithmetic coding. Arithmetic coding achieves compression rates close to the best possible for a particular statistical model, which is given by the information entropy, whereas Huffman compression is simpler and faster but produces poor results for models that deal with symbol probabilities close to 1.
There are two primary ways of constructing statistical models: in a static model, the data is analyzed and a model is constructed, then this model is stored with the compressed data. This approach is simple and modular, but has the disadvantage that the model itself can be expensive to store, and also that it forces a single model to be used for all data being compressed, and so performs poorly on files containing heterogeneous data. Adaptive models dynamically update the model as the data is compressed. Both the encoder and decoder begin with a trivial model, yielding poor compression of initial data, but as they learn more about the data, performance improves. Most popular types of compression used in practice now use adaptive coders.
Lossless compression methods may be categorized according to the type of data they are designed to compress. While, in principle, any general-purpose lossless compression algorithm (general-purpose meaning that they can compress any bitstring) can be used on any type of data, many are unable to achieve significant compression on data that are not of the form for which they were designed to compress. Many of the lossless compression techniques used for text also work reasonably well for indexed images.

Lossy compression

In information technology"lossy" compression is a data encoding method that compresses data by discarding (losing) some of it. The procedure aims to minimize the amount of data that need to be held, handled, and/or transmitted by a computer. The different versions of the photo of the dog at the right demonstrate how much data can be dispensed with, and how the images become progressively coarser as the data that made up the original one is discarded (lost). Typically, a substantial amount of data can be discarded before the result is sufficiently degraded to be noticed by the user.
Lossy compression is most commonly used to compress multimedia data (audiovideo, and still images), especially in applications such as streaming mediaand internet telephony. By contrast, lossless compression is required for text and data files, such as bank records and text articles. In many cases it is advantageous to make a master lossless file that can then be used to produce compressed files for different purposes; for example, a multi-megabyte file can be used at full size to produce a full-page advertisement in a glossy magazine, and a 10 kilobyte lossy copy can be made for a small image on a web page.

Run-length encoding
Run-length encoding (RLE) is a very simple form of data compression in which runs of data (that is, sequences in which the same data value occurs in many consecutive data elements) are stored as a single data value and count, rather than as the original run. This is most useful on data that contains many such runs: for example, simple graphic images such as icons, line drawings, and animations. It is not useful with files that don't have many runs as it could greatly increase the file size.
RLE also refers to a little-used image format in Windows 3.x, with the extension .rle, which is a Run Length Encoded Bitmap, used to compress the Windows 3.x startup screen.

In computingJPEG (Description: Description: play /ˈdʒeɪpɛɡ/ [pronounced as jay - peg] is a commonly used method of lossy compression for digital photography (image). The degree of compression can be adjusted, allowing a selectable tradeoff between storage size and image quality. JPEG typically achieves 10:1 compression with little perceptible loss in image quality.
JPEG compression is used in a number of image file formats. JPEG/Exif is the most common image format used by digital cameras and other photographic image capture devices; along with JPEG/JFIF, it is the most common format for storing and transmitting photographic images on the World Wide Web.[citation needed] These format variations are often not distinguished, and are simply called JPEG.
The term "JPEG" is an acronym for the Joint Photographic Experts Group which created the standard. The MIME media type for JPEG is image/jpeg(defined in RFC 1341), except in Internet Explorer, which provides a MIME type of image/pjpeg when uploading JPEG images.[1]
It supports a maximum image size of 65535×65535.[2]

Moving Picture Experts Group
The Moving Picture Experts Group (MPEG) is a working group of experts that was formed by ISO and IEC to set standards for audio and video compression and transmission.[1] It was established in 1988 by the initiative of Hiroshi Yasuda (Nippon Telegraph and Telephone) and Leonardo Chiariglione[2], who has been from the beginning the Chairman of the group. The first MPEG meeting was in May 1988 in Ottawa, Canada.[3][4][5] As of late 2005, MPEG has grown to include approximately 350 members per meeting from various industries, universities, and research institutions. MPEG's official designation is ISO/IEC JTC1/SC29 WG11 - Coding of moving pictures and audio (ISO/IEC Joint Technical Committee 1, Subcommittee 29, Working Group 11).

 Graphics Interchange Format
The Graphics Interchange Format (GIF) is a bitmap image format that was introduced by CompuServe in 1987 and has since come into widespread usage on the World Wide Web due to its wide support and portability.
The format supports up to 8 bits per pixel thus allowing a single image to reference a palette of up to 256 distinct colors. The colors are chosen from the 24-bit RGB color space. It also supports animations and allows a separate palette of 256 colors for each frame. The color limitation makes the GIF format unsuitable for reproducing color photographs and other images with continuous color, but it is well-suited for simpler images such as graphics or logos with solid areas of color.
GIF images are compressed using the Lempel-Ziv-Welch (LZW) lossless data compression technique to reduce the file size without degrading the visual quality. This compression technique was patented in 1985. Controversy over the licensing agreement between the patent holder, Unisys, and CompuServe in 1994 spurred the development of the Portable Network Graphics (PNG) standard; since then all the relevant patents have expired.

MPEG-1 or MPEG-2 Audio Layer III,[4] more commonly referred to as MP3, is a patented digital audio encoding format using a form of lossy data compression. It is a common audio format for consumer audio storage, as well as a de facto standard of digital audio compression for the transfer and playback of music on digital audio players.
MP3 is an audio-specific format that was designed by the Moving Picture Experts Group (MPEG) as part of its MPEG-1 standard and later extended inMPEG-2 standard. The first MPEG subgroup – Audio group was formed by several teams of engineers at Fraunhofer IISUniversity of HannoverAT&T-Bell LabsThomson-BrandtCCETT, and others.[7] MPEG-1 Audio (MPEG-1 Part 3), which included MPEG-1 Audio Layer I, II and III was approved as a committee draft of ISO/IEC standard in 1991,[8][9] finalised in 1992[10] and published in 1993 (ISO/IEC 11172-3:1993[5]). Backwards compatible MPEG-2 Audio (MPEG-2 Part 3) with additional bit rates and sample rates was published in 1995 (ISO/IEC 13818-3:1995).[6][11]
The use in MP3 of a lossy compression algorithm is designed to greatly reduce the amount of data required to represent the audio recording and still sound like a faithful reproduction of the original uncompressed audio for most listeners. An MP3 file that is created using the setting of 128 kbit/s will result in a file that is about 1/11 the size[note 1] than the CD file created from the original audio source. An MP3 file can also be constructed at higher or lower bit rates, with higher or lower resulting quality.
The compression works by reducing accuracy of certain parts of sound that are considered to be beyond the auditory resolution ability of most people. This method is commonly referred to as perceptual coding.[13] It uses psychoacoustic models to discard or reduce precision of components less audible to human hearing, and then records the remaining information in an efficient manner.

Free Lossless Audio Codec

Free Lossless Audio Codec (FLAC) is an audio compression codec that employs a lossless data compression algorithm. A digital audio recording compressed by FLAC can be decompressed into an identical copy of the original audio data. Audio sources encoded to FLAC are typically reduced to 50–60% of their original size.[2]
FLAC is an open and royalty-free format with a free software implementation made available. FLAC has support for taggingcover art, and fast seeking. Though FLAC playback support in portable audio devices and dedicated audio systems is limited compared to formats like MP3[3] or uncompressed PCM, FLAC is supported by more hardware devices than competing lossless compressed formats like WavPack.

Windows Media Audio
Windows Media Audio (WMA) is an audio data compression technology developed by Microsoft. The name can be used to refer to its audio file format or its audio codecs. It is a proprietary technology that forms part of the Windows Media framework. WMA consists of four distinct codecs. The original WMA codec, known simply as WMA, was conceived as a competitor to the popular MP3 and RealAudio codecs.[1][2] WMA Pro, a newer and more advanced codec, supports multichannel and high resolution audio.[3] A lossless codec, WMA Lossless, compresses audio data without loss of audio fidelity (the regular WMA format is lossy).[3] And WMA Voice, targeted at voice content, applies compression using a range of low bit rates.

Huffman coding
In computer science and information theoryHuffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol. It was developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".
Huffman coding uses a specific method for choosing the representation for each symbol, resulting in a prefix code (sometimes called "prefix-free codes", that is, the bit string representing some particular symbol is never a prefix of the bit string representing any other symbol) that expresses the most common source symbols using shorter strings of bits than are used for less common source symbols. Huffman was able to design the most efficient compression method of this type: no other mapping of individual source symbols to unique strings of bits will produce a smaller average output size when the actual symbol frequencies agree with those used to create the code. A method was later found to design a Huffman code in linear time if input probabilities (also known as weights) are sorted.[citation needed]
For a set of symbols with a uniform probability distribution and a number of members which is a power of two, Huffman coding is equivalent to simple binary block encoding, e.g., ASCII coding. Huffman coding is such a widespread method for creating prefix codes that the term "Huffman code" is widely used as a synonym for "prefix code" even when such a code is not produced by Huffman's algorithm.
Although Huffman's original algorithm is optimal for a symbol-by-symbol coding (i.e. a stream of unrelated symbols) with a known input probability distribution, it is not optimal when the symbol-by-symbol restriction is dropped, or when the probability mass functions are unknown, not identically distributed, or not independent (e.g., "cat" is more common than "cta"). Other methods such as arithmetic coding and LZW coding often have better compression capability: both of these methods can combine an arbitrary number of symbols for more efficient coding, and generally adapt to the actual input statistics, the latter of which is useful when input probabilities are not precisely known or vary significantly within the stream. However, the limitations of Huffman coding should not be overstated; it can be used adaptively, accommodating unknown, changing, or context-dependent probabilities. In the case of known independent and identically-distributed random variables, combining symbols together reduces inefficiency in a way that approaches optimality as the number of symbols combined increases.

Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham LempelJacob Ziv, and Terry Welch. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. The algorithm is simple to implement, and has the potential for very high throughput in hardware implementations.[1

Parity bit
parity bit is a bit that is added to ensure that the number of bits with the value one in a set of bits is even or odd. Parity bits are used as the simplest form of error detecting code.
There are two variants of parity bits: even parity bit and odd parity bit. When using even parity, the parity bit is set to 1 if the number of ones in a given set of bits (not including the parity bit) is odd, making the number of ones in the entire set of bits (including the parity bit) even. If the number of on-bits is already even, it is set to a 0. When using odd parity, the parity bit is set to 1 if the number of ones in a given set of bits (not including the parity bit) is even, keeping the number of ones in the entire set of bits (including the parity bit) odd. And when the number of set bits is already odd, the odd parity bit is set to 0. In other words, an even parity bit will be set to "1" if the number of 1's + 1 is even, and an odd parity bit will be set to "1" if the number of 1's +1 is odd.
Even parity is a special case of a cyclic redundancy check (CRC), where the 1-bit CRC is generated by the polynomial x+1.
If the parity bit is present but not used, it may be referred to as mark parity (when the parity bit is always 1) or space parity (the bit is always 0)

Cyclic redundancy check
cyclic redundancy check (CRC) is an error-detecting code designed to detect accidental changes to raw computer data, and is commonly used in digital networks and storage devices such as hard disk drives. Blocks of data entering these systems get a short check value attached, derived from the remainder of a polynomial division of their contents; on retrieval the calculation is repeated, and corrective action can be taken against presumed data corruption if the check values do not match.
CRCs are so called because the check (data verification) value is a redundancy (it adds zero information to the message) and the algorithm is based on cyclic codes. CRCs are popular because they are simple to implement in binary hardware, are easy to analyze mathematically, and are particularly good at detecting common errors caused by noise in transmission channels. Because the check value has a fixed length, the function that generates it is occasionally used as a hash function. The CRC was invented by W. Wesley Peterson in 1961; the 32-bit polynomial used in the CRC function of Ethernet and many other standards is the work of several researchers and was published in 1975.
In cryptographyRC4 (also known as ARC4 or ARCFOUR meaning Alleged RC4, see below) is the most widely used software stream cipher and is used in popular protocols such as Secure Sockets Layer (SSL) (to protect Internet traffic) and WEP (to secure wireless networks). While remarkable for its simplicity and speed in software, RC4 has weaknesses that argue against its use in new systems.[2] It is especially vulnerable when the beginning of the output keystream is not discarded, or nonrandom or related keys are used; some ways of using RC4 can lead to very insecure cryptosystems such asWEP.

Stop-and-wait ARQ
Stop-and-wait ARQ is a method used in telecommunications to send information between two connected devices. It ensures that information is not lost due to dropped packets and that packets are received in the correct order. It is the simplest kind of automatic repeat-request (ARQ) method. A stop-and-wait ARQ sender sends one frame at a time; it is a special case of the general sliding window protocol with both transmit and receive window sizes equal to 1. After sending each frame, the sender doesn't send any further frames until it receives an acknowledgement (ACK) signal. After receiving a good frame, the receiver sends an ACK. If the ACK does not reach the sender before a certain time, known as the timeout, the sender sends the same frame again.
The above behavior is the simplest Stop-and-Wait implementation. However, in a real life implementation there are problems to be addressed.
Typically the transmitter adds a redundancy check number to the end of each frame. The receiver uses the redundancy check number to check for possible damage. If the receiver sees that the frame is good, it sends an ACK. If the receiver sees that the frame is damaged, the receiver discards it and does not send an ACK -- pretending that the frame was completely lost, not merely damaged.
One problem is where the ACK sent by the receiver is damaged or lost. In this case, the sender doesn't receive the ACK, times out, and sends the frame again. Now the receiver has two copies of the same frame, and doesn't know if the second one is a duplicate frame or the next frame of the sequence carrying identical data.
Another problem is when the transmission medium has such a long latency that the sender's timeout runs out before the frame reaches the receiver. In this case the sender resends the same packet. Eventually the receiver gets two copies of the same frame, and sends an ACK for each one. The sender, waiting for a single ACK, receives two ACKs, which may cause problems if it assumes that the second ACK is for the next frame in the sequence.
To avoid these problems, the most common solution is to define a 1 bit sequence number in the header of the frame. This sequence number alternates (from 0 to 1) in subsequent frames. When the receiver sends an ACK, it includes the sequence number of the next packet it expects. This way, the receiver can detect duplicated frames by checking if the frame sequence numbers alternate. If two subsequent frames have the same sequence number, they are duplicates, and the second frame is discarded. Similarly, if two subsequent ACKs reference the same sequence number, they are acknowledging the same frame.
Stop-and-wait ARQ is inefficient compared to other ARQs, because the time between packets, if the ACK and the data are received successfully, is twice the transit time (assuming the turnaround time can be zero). The throughput on the channel is a fraction of what it could be. To solve this problem, one can send more than one packet at a time with a larger sequence number and use one ACK for a set. This is what is done in Go-Back-N ARQ and the Selective Repeat ARQ.

Burst error
In telecommunication, a burst error or error burst is a contiguous sequence of symbols, received over a data transmission channel, such that the first and last symbols are in error and there exists no contiguous subsequence of m correctly received symbols within the error burst.[1]
The integer parameter m is referred to as the guard band of the error burst. The last symbol in a burst and the first symbol in the following burst are accordingly separated by m correct bits or more. The parameter m should be specified when describing an error burst.
The length of a burst of bit errors in a frame is defined as the number of bits from the first error to the last, inclusive.

Digital signature

digital signature or digital signature scheme is a mathematical scheme for demonstrating the authenticity of a digital message or document. A valid digital signature gives a recipient reason to believe that the message was created by a known sender, and that it was not altered in transit. Digital signatures are commonly used for software distribution, financial transactions, and in other cases where it is important to detect forgery or tampering.
Triple DES
In cryptographyTriple DES is the common name for the Triple Data Encryption Algorithm (TDEA or Triple DEAblock cipher, which applies the Data Encryption Standard (DES) cipher algorithm three times to each data block.
The original DES cipher's key size of 56 bits was generally sufficient when that algorithm was designed, but the availability of increasing computational power made brute-force attacks feasible. Triple DES provides a relatively simple method of increasing the key size of DES to protect against such attacks, without the need to design a completely new block cipher algorithm.

Spam (electronic)
Spam is the use of electronic messaging systems (including most broadcast media, digital delivery systems) to send unsolicited bulk messages indiscriminately. While the most widely recognized form of spam is e-mail spam, the term is applied to similar abuses in other media: instant messaging spamUsenet newsgroup spamWeb search engine spamspam in blogswiki spamonline classified ads spam,mobile phone messaging spamInternet forum spamjunk fax transmissionssocial networking spam, television advertising and file sharing network spam.
Spamming remains economically viable because advertisers have no operating costs beyond the management of their mailing lists, and it is difficult to hold senders accountable for their mass mailings. Because the barrier to entry is so low, spammers are numerous, and the volume of unsolicited mail has become very high. In the year 2011, the estimated figure for spam messages is around seven trillion. The costs, such as lost productivity and fraud, are borne by the public and by Internet service providers, which have been forced to add extra capacity to cope with the deluge. Spamming has been the subject of legislation in many jurisdictions.[1]
A person who creates electronic spam is called a spammer.[2]

Simple Mail Transfer Protocol
Simple Mail Transfer Protocol (SMTP) is an Internet standard for electronic mail (e-mail) transmission across Internet Protocol (IP) networks. SMTP was first defined by RFC 821 (1982, eventually declared STD 10),[1] and last updated by RFC 5321 (2008)[2] which includes the extended SMTP (ESMTP) additions, and is the protocol in widespread use today. SMTP is specified for outgoing mail transport and uses TCP port 25. The protocol for new submissions is effectively the same as SMTP, but it uses port 587 instead. SMTP connections secured by SSL are known by the shorthand SMTPS, though SMTPS is not a protocol in its own right.
While electronic mail servers and other mail transfer agents use SMTP to send and receive mail messages, user-level client mail applications typically only use SMTP for sending messages to a mail server for relaying. For receiving messages, client applications usually use either the Post Office Protocol (POP) or the Internet Message Access Protocol (IMAP) or a proprietary system (such as Microsoft Exchange or Lotus Notes/Domino) to access their mail box accounts on a mail server.

In cryptographyX.509 is an ITU-T standard for a public key infrastructure (PKI) and Privilege Management Infrastructure (PMI). X.509 specifies, amongst other things, standard formats for public key certificatescertificate revocation listsattribute certificates, and a certification path validation algorithm.

Data Encryption Standard

The Data Encryption Standard (DES) is a block cipher that uses shared secret encryption. It was selected by the National Bureau of Standards as an official Federal Information Processing Standard (FIPS) for the United States in 1976 and which has subsequently enjoyed widespread use internationally. It is based on a symmetric-key algorithm that uses a 56-bit key. The algorithm was initially controversial because of classified design elements, a relatively short key length, and suspicions about a National Security Agency (NSA) backdoor. DES consequently came under intense academic scrutiny which motivated the modern understanding of block ciphers and their cryptanalysis.
DES is now considered to be insecure for many applications. This is chiefly due to the 56-bit key size being too small; in January, 1999, and the Electronic Frontier Foundation collaborated to publicly break a DES key in 22 hours and 15 minutes (see chronology). There are also some analytical results which demonstrate theoretical weaknesses in the cipher, although they are infeasible to mount in practice. The algorithm is believed to be practically secure in the form of Triple DES, although there are theoretical attacks. In recent years, the cipher has been superseded by the Advanced Encryption Standard (AES). Furthermore, DES has been withdrawn as a standard by theNational Institute of Standards and Technology (formerly the National Bureau of Standards).
In some documentation, a distinction is made between DES as a standard and DES the algorithm which is referred to as the DEA (the Data Encryption Algorithm). When spoken, "DES" is either spelled out as an abbreviation (/ˌdiːˌiːˈɛs/), or pronounced as a one-syllable acronym (/ˈdɛz/).

Advanced Encryption Standard

Advanced Encryption Standard (AES) is a specification for the encryption of electronic data. It has been adopted by the U.S. government and is now used worldwide. It supersedes DES.[3]
In the United States of America, AES was announced by National Institute of Standards and Technology (NIST) as U.S. FIPS PUB 197 (FIPS 197) on November 26, 2001 after a five-year standardization process in which fifteen competing designs were presented and evaluated before it was selected as the most suitable (see Advanced Encryption Standard process for more details). It became effective as a Federal government standard on May 26, 2002 after approval by the Secretary of Commerce. It is available in many different encryption packages. AES is the first publicly accessible and open cipher approved by the National Security Agency (NSA) for top secret information (see Security of AES, below).
Originally called Rijndael, the cipher was developed by two Belgian cryptographers, Joan Daemen and Vincent Rijmen, and submitted by them to the AES selection process.[4] The name Rijndael (Dutch pronunciation: [ˈrɛindaːl][5]) is a play on the names of the two inventors.

Pretty Good Privacy
Pretty Good Privacy (PGP) is a data encryption and decryption computer program that provides cryptographic privacy and authentication for data communication. PGP is often used for signing, encrypting and decrypting texts, E-mails, files, directories and whole disk partitions to increase the security of e-mail communications. It was created by Phil Zimmermann in 1991.
PGP and similar products follow the OpenPGP standard (RFC 4880) for encrypting and decrypting data.

How PGP encryption works
PGP encryption uses a serial combination of hashingdata compressionsymmetric-key cryptography, and, finally, public-key cryptography; each step uses one of several supported algorithms. Each public key is bound to a user name and/or an e-mail address. The first version of this system was generally known as a web of trust to contrast with the X.509 system which uses a hierarchical approach based on certificate authority and which was added to PGP implementations later. Current versions of PGP encryption include both options through an automated key management server.
Multipurpose Internet Mail Extensions (MIME) is an Internet standard that extends the format of email to support:
§  Text in character sets other than ASCII
§  Non-text attachments
§  Message bodies with multiple parts
§  Header information in non-ASCII character sets
MIME's use, however, has grown beyond describing the content of email to describe content type in general, including for the web (see Internet media type) and as a storage for rich content in some commercial products (e.g., IBM Lotus Domino and IBM Lotus Quickr).
Virtually all human-written Internet email and a fairly large proportion of automated email is transmitted via SMTP in MIME format. Internet email is so closely associated with the SMTP and MIME standards that it is sometimes called SMTP/MIME email.[1]
The content types defined by MIME standards are also of importance outside of email, such as in communication protocols like HTTP for the World Wide Web. HTTP requires that data be transmitted in the context of email-like messages, although the data most often is not actually email.
MIME is specified in six linked RFC memorandaRFC 2045RFC 2046RFC 2047RFC 4288RFC 4289 and RFC 2049, which together define the specifications.

 Kerberos (protocol)
Kerberos (Description: Description: play /ˈkɛərbərəs/) is a computer network authentication protocol which works on the basis of "tickets" to allow nodes communicating over a non-secure network to prove their identity to one another in a secure manner. Its designers aimed primarily at a client–server model, and it provides mutual authentication — both the user and the server verify each other's identity. Kerberos protocol messages are protected against eavesdropping and replay attacks. Kerberos builds on symmetric key cryptography and requires a trusted third party, and optionally may use public-key cryptography by utilizingasymmetric key cryptography during certain phases of authentication.[1] Kerberos uses port 88 by default.
"Kerberos" also refers to a suite of free software published by Massachusetts Institute of Technology (MIT) that implements the Kerberos protocol.

The Evolution of the Kerberos Authentication System" is a very good description of the limitations of Kerberos 4 and what changes were made in Kerberos 5
However, here is a quick list of the more important changes:
  • The key salt algorithm has been changed to use the entire principal name.
  • The network protocol has been completely redone and now uses ASN.1 encoding everywhere.
  • There is now support for forwardablerenewable, and postdatable tickets.
  • Kerberos tickets can now contain multiple IP addresses and addresses for different types of networking protocols.
  • A generic crypto interface module is now used, so other encryption algorithms beside DES can be used.
  • There is now support for replay caches, so authenticators are not vulnerable to replay.
  • There is support for transitive cross-realm authentication.

Internet Protocol Security (IPsec) is a protocol suite for securing Internet Protocol (IP) communications by authenticating and encrypting each IP packet of a communication session. IPsec also includes protocols for establishing mutual authentication between agents at the beginning of the session and negotiation of cryptographic keys to be used during the session.
IPsec is an end-to-end security scheme operating in the Internet Layer of the Internet Protocol Suite. It can be used in protecting data flows between a pair of hosts (host-to-host), between a pair of security gateways (network-to-network), or between a security gateway and a host (network-to-host).[1]
Some other Internet security systems in widespread use, such as Secure Sockets Layer (SSL), Transport Layer Security (TLS) and Secure Shell (SSH), operate in the upper layers of the TCP/IP model. Hence, IPsec protects any application traffic across an IP network. Applications do not need to be specifically designed to use IPsec. The use of TLS/SSL, on the other hand, must be designed into an application to protect the application protocols.
IPsec is a successor of the ISO standard Network Layer Security Protocol (NLSP). NLSP was based on the SP3 protocol that was published by NIST, but designed by the Secure Data Network System project of the National Security Agency (NSA).
IPsec is officially specified by the Internet Engineering Task Force (IETF) in a series of Request for Comment documents addressing various components and extensions. It specifies the spelling of the protocol name to be IPsec.[2

Layer 2 Tunneling Protocol
In computer networkingLayer 2 Tunneling Protocol (L2TP) is a tunneling protocol used to support virtual private networks (VPNs). It does not provide any encryption or confidentiality by itself; it relies on an encryption protocol that it passes within the tunnel to provide privacy.[1]
Although L2TP acts like a Data Link Layer protocol in the OSI model, L2TP is in fact a Session Layer protocol,[2] and uses the registered UDP port 1701. (see List of TCP and UDP port numbers).

Set (abstract data type)
set is an abstract data structure that can store certain values, without any particular order, and no repeated values. It is a computer implementation of the mathematical concept of a finite set. Unlike most other collection types, rather than retrieving a specific element from a set, one typically tests a value for membership in a set.
Some set data structures are designed for static sets that do not change with time, and allow only query operations — such as checking whether a given value is in the set, or enumerating the values in some arbitrary order. Other variants, called dynamic or mutable sets, allow also the insertion and/or deletion of elements from the set.
A set can be implemented in many ways. For example, one can use a list, ignoring the order of the elements and taking care to avoid repeated values. Sets are often implemented using various flavors of treestries, or hash tables.
A set can be seen, and implemented, as a (partial) associative array, in which the value of each key-value pair has the unit type.

Transport Layer Security (TLS)and its predecessor, Secure Sockets Layer (SSL), are cryptographic protocols that provide communication security over the Internet.[1] TLS and SSL encrypt the segments of network connections above the Transport Layer, using asymmetric cryptography for key exchange,symmetric encryption for privacy, and message authentication codes for message integrity.
Several versions of the protocols are in widespread use in applications such as web browsingelectronic mailInternet faxinginstant messaging and voice-over-IP (VoIP).
TLS is an IETF standards track protocol, last updated in RFC 5246, and is based on the earlier SSL specifications developed by NetscapeCommunications

Modes of operation
IPsec can be implemented in a host-to-host transport mode, as well as in a network tunnel mode.
[edit]Transport mode
In transport mode, only the payload (the data you transfer) of the IP packet is usually encrypted and/or authenticated. The routing is intact, since the IP header is neither modified nor encrypted; however, when the authentication header is used, the IP addresses cannot be translated, as this will invalidate the hash value. The transport and application layers are always secured by hash, so they cannot be modified in any way (for example by translating the port numbers). Transport mode is used for host-to-host communications.
A means to encapsulate IPsec messages for NAT traversal has been defined by RFC documents describing the NAT-T mechanism.
[edit]Tunnel mode
In tunnel mode, the entire IP packet is encrypted and/or authenticated. It is then encapsulated into a new IP packet with a new IP header. Tunnel mode is used to create virtual private networks for network-to-network communications (e.g. between routers to link sites), host-to-network communications (e.g. remote user access), and host-to-host communications (e.g. private chat).
Tunnel mode supports NAT traversal.

Point-to-Point Tunneling Protocol

The Point-to-Point Tunneling Protocol (PPTP) is a method for implementing virtual private networks. PPTP uses a control channel over TCP and a GRE tunnel operating to encapsulate PPPpackets.
The PPTP specification does not describe encryption or authentication features and relies on the PPP protocol being tunneled to implement security functionality. However the most common PPTP implementation, shipping with the Microsoft Windows product families, implements various levels of authentication and encryption natively as standard features of the Windows PPTP stack. The intended use of this protocol is to provide similar levels of security and remote access as typical VPN products.

Cycle of payment authentication

A card is presented for payment.
·Authentication. The merchant verifies the validity of the card and the cardholder. In a card-present setting, the merchant physically inspects the card for signs of alteration and can request a government-issued ID if in doubt about the cardholder’s authenticity. In a card-absent setting, there are many services that can assist merchants in the authentication process and we have reviewed them in multiple articles before.
·Authorization. In this stage the card issuer approves or rejects the transaction, based on the information provided by the merchant. The possible authorization responses are:
·         Approval – the merchant can proceed with the transaction.
·         Decline – the merchant should not complete the transaction and ask for an alternative payment method instead.
·         Refer to card issuer – the merchant should contact the issuer before completing the transaction.
·         Capture card – the merchant should retain the card.
·         Valid – used for inquiries (balance inquiries, address verification requests, etc.), this response indicates that the authorization request is not declined. In effect, it is an approval, however there is no actual transaction taking place.
·         Clearing and settlement. Although separate processes, the clearing and settlement occur simultaneously. Clearing is the process of exchanging transaction data between an acquirer and an issuer, while settlement is the process of exchanging funds between the two parties. In a typical card transaction, the issuer pays the acquirer the transaction amount, minus the applicable interchange fee. The acquirer then debits the merchant’s account with the amount of the settled funds, minus its own processing fees, which are stated in the merchant agreement.
·         Cardholder payment. The issuer, credits its cardholder’s account with the transaction amount. At the end of the month the cardholder makes a payment to the issuer to complete the transaction cycle.

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