As the world becomes increasingly dependent on data, questions continuously arise as to how to protect our global information systems. It has become imperative to find ways to protect your data from outsiders who may want to steal that data. Machine learning is a field in Computer Science that can help examine what is happening on a computer network and identify when something abnormal happens. Machine learning algorithms are becoming increasingly popular in the computer security world. Once an algorithm has been tested and deployed, it can be left alone as it learns from the network data it collects, making an administrator's life much easier. This research examines how the Naive Bayes Classification Model can be used to identify

stemswedishΤεχνίτη Νοημοσύνη και Ρομποτική

15 Οκτ 2013 (πριν από 3 χρόνια και 8 μήνες)

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As the world becomes increasingly dependent on data, questions continuously arise as to how
to protect our global information systems. It has become imperative to find ways to protect your
data from outsiders who may want to steal that data. Machine
learning is a field in Computer
Science that can help examine what is happening on a computer network and identify when
something abnormal happens. Machine learning algorithms are becoming increasingly popular
in the computer security world. Once an algori
thm has been tested and deployed, it can be left
alone as it learns from the network data it collects, making an administrator's life much easier.
This research examines how the Naive Bayes Classification Model can be used to identify
normal and abnormal I
nternet activity. The goal of this work is to create a program that correctly
distinguishes between what is deemed acceptable internet traffic from nefarious or questionable
traffic. This work will describe the algorithm and demonstrate its effectiveness f
or a variety of
traffic types.