A computer-implemented method of identifying human interaction with a computer, comprising: receiving interaction data indicative of interaction with the computer, wherein the interaction data comprises event data indicative of interaction events with a user-interface, UI, provided by the computer and wherein the event data is indicative of one or more of movement of a pointing device, movement of a cursor responsive to touch applied to a touch sensitive device, activation of a control of the UI and operation of a keyboard associated with the computer; determining one or more UI cues from the interaction data; determining, at a first classifier, whether the interaction data is indicative of directed or random interaction with the computer in dependence on a plurality of the UI cues; providing an output of the first classifier to a second classifier; determining, at the second classifier, whether the interaction data is indicative of human or software-controlled interaction with the computer, in dependence on the plurality of the UI cues and the output of the first classifier; wherein the second classifier is a machine-learning based classifier trained based upon a first set of training data indicative of human interaction and a second set of training data indicative of software-controlled interaction, and the first classifier is a machine-learning based classifier trained based upon a third set of training data indicative of random interaction and a combined set of training data comprising the first and second sets of training data; determining whether the interaction data is indicative of human interaction with the computer based on both the output of the first classifier and an output of the second classifier; and performing an action in dependence on the determination of whether the interaction data is indicative of human interaction with the computer. receiving interaction data indicative of interaction with the computer, wherein the interaction data comprises event data indicative of interaction events with a user-interface, UI, provided by the computer and wherein the event data is indicative of one or more of movement of a pointing device, movement of a cursor responsive to touch applied to a touch sensitive device, activation of a control of the UI and operation of a keyboard associated with the computer; determining one or more UI cues from the interaction data; determining, at a first classifier, whether the interaction data is indicative of directed or random interaction with the computer in dependence on a plurality of the UI cues; providing an output of the first classifier to a second classifier; determining, at the second classifier, whether the interaction data is indicative of human or software-controlled interaction with the computer, in dependence on the plurality of the UI cues and the output of the first classifier; wherein the second classifier is a machine-learning based classifier trained based upon a first set of training data indicative of human interaction and a second set of training data indicative of software-controlled interaction, and the first classifier is a machine-learning based classifier trained based upon a third set of training data indicative of random interaction and a combined set of training data comprising the first and second sets of training data; determining whether the interaction data is indicative of human interaction with the computer based on both the output of the first classifier and an output of the second classifier; and performing an action in dependence on the determination of whether the interaction data is indicative of human interaction with the computer. <EOS>