Tokens of Interaction: Psychophysiological Signals, a Potential Source of Evidence of Digital Incidents

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Abstract

The human factor is a key component of any computing network just as are other tools and devices within it. At the same time, human emotion is highly responsive to the environment and this manifests in psychophysiological changes even when no physical reaction is observable. Therefore, a digital record of the state of body and mind can to one degree or another reflect the state of other components in a given network while the person is a part of it. Meanwhile, as the digital and physical worlds continue to converge cybersecurity is increasingly a day-to-day concern. Many crimes are now committed, mediated or witnessed through a digital device, and many operational artifacts of computing systems have later proved useful as evidence in digital investigations. Psychophysiological signals though unharnessed in this regard, could be a rich resource—in detecting occurrence, timing and duration of adverse incidents—owing to high human emotional responsiveness to the environment. Further, psychophysiological signals are hard to manipulate and so they are likely to provide a truer reflection of events. This is not only promising for investigations but as a potential feedback channel for monitoring safety and security in digital spaces, independent of human decision-making. This paper proceeds a dissertation study investigating psychophysiological signals for markers of digital incidents. Understanding and harnessing psychophysiological markers of digital incidents can enable designing of safer computing spaces through triggering appropriate controls to adaptively manage threats—such as cyberbullying and insiders threats.

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APA

Mogire, N., Minas, R. K., & Crosby, M. E. (2019). Tokens of Interaction: Psychophysiological Signals, a Potential Source of Evidence of Digital Incidents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11580 LNAI, pp. 93–110). Springer Verlag. https://doi.org/10.1007/978-3-030-22419-6_8

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