The correct functioning of interactive computer systems depends on both the faultless operation of the device and correct human actions. In this paper, we focus on system malfunctions due to human actions. We present abstract principles that generate cognitively plausible human behaviour. These principles are then formalised in a higher-order logic as a
generic
, and so retargetable, cognitive architecture, based on results from cognitive psychology. We instantiate the generic cognitive architecture to obtain specific user models. These are then used in a series of case studies on the formal verification of simple interactive systems. By doing this, we demonstrate that our verification methodology can detect a variety of realistic, potentially erroneous actions, which emerge from the combination of a poorly designed device and cognitively plausible human behaviour.
A demonstration is presented of how automated reasoning tools can be used to check the predictability of a user interface. Predictability concerns the ability of a user to determine the outcomes of their actions reliably. It is especially important in situations such as a hospital ward where medical devices are assumed to be reliable devices by their expert users (clinicians) who are frequently interrupted and need to quickly and accurately continue a task. There are several forms of predictability. A definition is considered where information is only inferred from the current perceptible output of the system. In this definition, the user is not required to
In this paper we are concerned with security issues that arise in the interaction between user and system. We focus on cognitive processes that affect security of information flow from the user to the computer system and the resilience of the whole system to intruder attacks. For this, we extend our framework developed for the verification of usability properties by introducing two kinds of intruder models, an observer and an active intruder, with the associated security properties. Finally, we consider small examples to illustrate the ideas and approach. These examples demonstrate how our framework can be used (a) to detect confidentiality leaks, caused by a combination of an inappropriate design and certain aspects of human cognition, and (b) to identify designs more susceptible to cognitively based intruder attacks.
Abstract. We formally specify the interpretation stage in a dual state space human-computer interaction cycle. This is done by extending / reorganising our previous cognitive architecture. In particular, we focus on shape related aspects of the interpretation process associated with device input prompts. A cash-point example illustrates our approach. Using the SAL model checking environment, we show how the extended cognitive architecture facilitates detection of prompt-shape induced human error.
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