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Integrity refers to whether data is valid or invalid. Invalid data may result from a number of different sources, both human and computer in origin. For example, many (flawed) business processes require multiple entry of the same data multiple times, potentially by multiple users. This can lead to integrity breaches if errors are made. More commonly, though, communication errors can occur when data is transmitted over a network, or when data is being transferred in memory. Most network protocols use parity to ensure data integrity an extra bit is added to every 8 bits of data, which is used with a checksum algorithm to determine whether an error has been detected. Parity mechanisms can detect errors in data but are not capable of fixing errors typically, a retransmission is required, but this is better than losing data altogether. Memory corruption can occur when a program reads memory that is allocated to a different application or, more seriously, attempts to overwrite data of another application. Fortunately, most modern memory hardware contains error-correction coding (ECC) that ensures that data errors can be easily identified and fixed before they cause any problems. Since network protocols and hardware protocols generally handle invalid data caused by system hardware and software, the Application layer is generally where there is great concern over data integrity, especially where that data has been transmitted over a network, because data can potentially be intercepted, modified, and then relayed by a malicious third party (for pleasure or profit). For example, a share-trading application might require traders to authenticate themselves over a Secure Sockets Layer (SSL) connection, but then revert to plaintext mode for processing all buy and sell requests, because SSL is too slow to encrypt all traffic to and from the broker s Web site, particularly when thousands of users are trading concurrently. A malicious third party might take control of a downstream router and write a filter that changes all co-occurrences of BUY and 1000 shares to 10000 shares. Such an attack would be difficult to thwart, unless SSL was used for all transmissions. One way to determine data integrity is to use a one-way hash function, like a message digest. These functions can be computed from a string of arbitrary length and return an almost unique identifier, such as b6d624gaf995c9e7c7da2a816b7deb33. Even a small change in the source string changes the computed function, so the message digests can be used to detect data tampering. There are several algorithms available to compute such hash functions, including MD5 and SHA-1, which all generate a different bit length digest the longest digests provide a relatively stronger guarantee of collision resistance; that is, when the same digest is computed from the same piece of data. Fortunately, the probability of doing this is very low. The bit lengths of MD5 and SHA-1 are 128 and 160 bits, respectively. Accurate data has all the properties of data integrity, plus an assurance that what a piece of data claims to be is what it actually is. Thus, a username of nine characters cannot be an accurate login if the maximum length is eight characters. Indeed, the many buffer-overflow attacks of recent years have exploited excess data length as a key mechanism for bringing down applications that don t explicitly check for data accuracy.
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An issue related to integrity is authenticity that is, given a piece of data that has demonstrated integrity, how do you know that it is authentic If multiple copies of data exist, and they all pass integrity checks, how do you know whether they are consistent with each other If multiple copies of a piece of data exist, and one or more copies are inconsistent, how do you establish which one (or more) copies is authentic The issues of authenticity and consistency are closely related in distributed systems.
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