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In computer programming, DLL injection is a technique used for running code within the address space of another process by forcing it to load a dynamic-link library. [1] DLL injection is often used by external programs to influence the behavior of another program in a way its authors did not anticipate or intend.
Code injection is the malicious injection or introduction of code into an application. Some web servers have a guestbook script, which accepts small messages from users and typically receives messages such as: Very nice site! However, a malicious person may know of a code injection vulnerability in the guestbook and enter a message such as:
In software engineering, dependency injection is a programming technique in which an object or function receives other objects or functions that it requires, as opposed to creating them internally. Dependency injection aims to separate the concerns of constructing objects and using them, leading to loosely coupled programs.
A classification of SQL injection attacking vector as of 2010. In computing, SQL injection is a code injection technique used to attack data-driven applications, in which malicious SQL statements are inserted into an entry field for execution (e.g. to dump the database contents to the attacker).
Leroy "Lee" Edward Hood (born October 10, 1938) is an American biologist who has served on the faculties at the California Institute of Technology (Caltech) and the University of Washington. [2] Hood has developed ground-breaking scientific instruments which made possible major advances in the biological sciences and the medical sciences.
Reality testing is the psychotherapeutic function by which the objective or real world and one's relationship to it are reflected on and evaluated by the observer. This process of distinguishing the internal world of thoughts and feelings from the external world is a technique commonly used in psychoanalysis and behavior therapy, and was originally devised by Sigmund Freud.
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data.This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable.