Cloud-based machine learning for the detection of anonymous web proxies

The emergence and growth of cloud computing has made a serious impact on the IT industry in recent years with large companies starting to offer powerful, reliable and costefficient platforms for businesses to build and reshape... [ view full abstract ]

The emergence and growth of cloud computing
has made a serious impact on the IT industry in recent years with
large companies starting to offer powerful, reliable and costefficient
platforms for businesses to build and reshape their
business models. Showing no sign of slowing down, cloud
computing capabilities now include machine learning, with
facilities for both designing and deploying models. With this
capability of machine learning using cloud computing comes the
increasing need to be able to classify whether an incoming
connection is from a legitimate originating IP address or if it is
being sent through an intermediary like a web proxy. Taking
inspiration from Intrusion Detection Systems that make use of
machine learning capabilities to improve anomaly detection
accuracy, this paper proposes that cloud based machine learning
can be used in order to detect and classify web proxy usage by
capturing packet data and feeding it into a cloud based machine
learning web service.