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Systems that use passwords for authentication must have some way to check any password entered to gain access. If the valid passwords are simply stored in a system file or database, an attacker who gains sufficient access to the system will obtain all user passwords, giving the attacker access to all accounts on the attacked system and possibly other systems where users employ the same or ...
Accelerated bootstrap – The bias-corrected and accelerated (BCa) bootstrap, by Efron (1987), [12] adjusts for both bias and skewness in the bootstrap distribution. This approach is accurate in a wide variety of settings, has reasonable computation requirements, and produces reasonably narrow intervals.
Cross-validation is employed repeatedly in building decision trees. One form of cross-validation leaves out a single observation at a time; this is similar to the jackknife. Another, K-fold cross-validation, splits the data into K subsets; each is held out in turn as the validation set. This avoids "self-influence".
The easier a password is for the owner to remember generally means it will be easier for an attacker to guess. [12] However, passwords that are difficult to remember may also reduce the security of a system because (a) users might need to write down or electronically store the password, (b) users will need frequent password resets and (c) users are more likely to re-use the same password ...
In statistics, the jackknife (jackknife cross-validation) is a cross-validation technique and, therefore, a form of resampling. It is especially useful for bias and variance estimation. The jackknife pre-dates other common resampling methods such as the bootstrap.
A server implements an HSTS policy by supplying a header over an HTTPS connection (HSTS headers over HTTP are ignored). [1] For example, a server could send a header such that future requests to the domain for the next year (max-age is specified in seconds; 31,536,000 is equal to one non-leap year) use only HTTPS: Strict-Transport-Security: max-age=31536000.
In statistics, the bootstrap error-adjusted single-sample technique (BEST or the BEAST) is a non-parametric method that is intended to allow an assessment to be made of the validity of a single sample.
The simplest example of a challenge-response protocol is password authentication, where the challenge is asking for the password and the valid response is the correct password. An adversary who can eavesdrop on a password authentication can authenticate themselves by reusing the intercepted password. One solution is to issue multiple passwords ...