We propose a novel deception detection system based on Rapid Serial Visual Presentation (RSVP). One motivation for the new method is to present stimuli on the fringe of awareness, such that it is more difficult for deceivers to confound the deception test using countermeasures. The proposed system is able to detect identity deception (by using the first names of participants) with a 100% hit rate (at an alpha level of 0.05). To achieve this, we extended the classic Event-Related Potential (ERP) techniques (such as peak-to-peak) by applying Randomisation, a form of Monte Carlo resampling, which we used to detect deception at an individual level. In order to make the deployment of the system simple and rapid, we utilised data from three electrodes only: Fz, Cz and Pz. We then combined data from the three electrodes using Fisher's method so that each participant was assigned a single p-value, which represents the combined probability that a specific participant was being deceptive. We also present subliminal salience search as a general method to determine what participants find salient by detecting breakthrough into conscious awareness using EEG.
One major drawback of deception detection is its vulnerability to countermeasures, whereby participants wilfully modulate their physiological or neurophysiological response to critical guilt-determining stimuli. One reason for this vulnerability is that stimuli are usually presented slowly. This allows enough time to consciously apply countermeasures, once the role of stimuli is determined. However, by increasing presentation speed, stimuli can be placed on the fringe of awareness, rendering it hard to perceive those that have not been previously identified, hindering the possibility to employ countermeasures. We tested an identity deception detector by presenting first names in Rapid Serial Visual Presentation and instructing participants to lie about their own identity. We also instructed participants to apply a series of countermeasures. The method proved resilient, remaining effective at detecting deception under all countermeasures.
MULTIFILE
Decisions and business rules are essential Components of an organization. Combined, these components form a basis for securing the implementation of new laws, regulations and internal policies into processes, work instructions and information systems. To ensure proper implementation, business rule types must be taken into account, as the functions per type may be different. The current body of knowledge on decision and business rule management offers some insights into different types of business rules, however, these types are often presented as a secondary focus of a contribution or set in stone without proper evidence supporting these claims. This study therefore aims to explore the different business rule types utilized in the body of knowledge as well as practice. This will form a basis to determine possible overlap and inconsistencies and aid in establishing the functional differences between the defined business rule types. By applying a literature review, semi-structured interviews and secondary data analysis, we observed that the current body of knowledge shows serious diffusion with regards to business rule types, the same holds for practice. Therefore, future research should focus to research these differences in detail with the aim to harmonize the proliferation of business rule types.
