Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a minute:

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

I think people here could guide me in solving a problem related to anomaly detection in Computer Science. The term anomaly here refers to some undesired event occuring in the system like a virus infection.

I could get to know about it from more than one source. For example, after having extracted a value from two different data structures, if there is a difference it is certain that virus infection is there.

In order to remove the false positive cases, information is gathered from different data structures or mechanisms. Hence, certain information are less trusted and certain information are more trusted.

I am looking for a mathematical method, that could easily handle this type of situations. Whether Fuzzy/Genetic Algorithm/Neural Net fits here? Found in some places they are using normality-based approach (using z-score). Please help.

share|improve this question
up vote 3 down vote accepted

Read this: Anomaly Detection : A Survey (2009)

share|improve this answer

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.