Cloud-based machine learning for the detection of anonymous web proxies
Shane Miller, Kevin J Curran, Tom Lunney · 2016
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 cost-efficient 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.