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Here the MySQL database called www is on localhost and can be accessed by a user called httpd using no1secret as the password The www database has a table called users You can change these parameters as desired to connect to the appropriate database on the local host or a remote MySQL database server This include file opens a connection to the named database on the appropriate host and returns a connection handle called $dbh, which is available to authphp In the authphp script, notice this line:

$sth = mysql_query( SELECT 1 from $table WHERE username = $PHP_AUTH_USER and passwd = $PHP_AUTH_PW , $dbh);

Attribute creator cRLObject cRLPartitionedRevocationList crossCertificatePair currentLocation currentParentCA currentValue currentMachineId dBCSPwd dc defaultClassStore defaultGroup defaultHidingValue defaultLocalPolicyObject defaultObjectCategory defaultPriority defaultSecurityDescriptor deltaRevocationList department description desktopProfile destinationIndicator dhcpClasses dhcpFlags dhcpIdentification dhcpMask dhcpMaxKey dhcpObjDescription dhcpObjName dhcpOptions dhcpProperties

This line performs an SQL query that returns 1 if user-supplied credentials (stored in $PHP_AUTH_USER and $PHP_AUTH_PW automatically by PHP) matches a username and passwd field, respectively, in the (users) table

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QuickReduct. The original algorithm, augmented by using DVD-based calculation. QuickReduct II, also known as ReverseReduct. A backward-eliminating version of QuickReduct. QuickReduct III. Unlike the original QuickReduct, this version of the algorithm introduces a minor optimization: the reduction stops immediately as soon as the rst reduct is found. QuickReduct IV. Augmented version of QuickReduct III. In adding further features to the attribute subset, dataset samples are not examined if they are known to be discernible given the current attribute subset. Only heretofore indiscernible samples are used in the calculation of . This reduces the effective size of the dataset as QuickReduct IV approaches a solution. For example, assume a dataset of 150 samples is being processed, and the rst evaluation of dependency yields 120 discernible samples. In adding further attributes to the attribute subset, will only be evaluated for the remaining 30 samples. This depends on the monotonicity of : if samples d and d are discernible given the attribute set A, then they will also be discernible given the attribute set A , where A A QuickReduct V. In selecting an attribute to be added to the candidate reduct, the attribute whose addition leads to the highest is used. This version of

If your users table has a different field name for username or passwd, make sure you change the query statement to reflect those names

The $success = mysql_fetch_row($sth) statement returns an array called $success, which should have returned the value 1 as the first element in $success[0] if the query is successful Or else the element is undefined By using the first element $success[0], the decision to display (or not to display) the authentication challenge by using show_challenge() is made After a user is authenticated, this simple authphp script does not do anything other than print a message stating that the user was successfully authenticated You can, of course, have the script do much more than that For example, you can redirect the user to a protected subdirectory by using the Header( Location: /path/to/subdirectory );

Syntax Unicode String Distinguished Name Octet String Octet String Octet String DistinguishedName Octet String Octet String Octet String Unicode String Distinguished Name Distinguished Name Boolean Distinguished Name Distinguished Name Integer Unicode String Octet String Unicode String Unicode String Unicode String Print Case String Octet String Large Integer Unicode String Print Case String Large Integer Unicode String Unicode String Octet String Octet String

the algorithm immediately stops calculating if the result is guaranteed to be below the highest result so far. This is tested incrementally by summing the frequencies of indiscernible pairs in the DVD. This optimization saves considerable time, especially where datasets have a signi cant degree of redundancy and/or noise.

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