David Keatley

IP theft insiders continue to pose threats to organizations, which can lead to large financial losses and reputational harm. This paper examines IP insider threat in a novel way by combining the methods of Grounded Theory and Behavior Sequence Analysis. Novel socio-technical variables identified in our study included IP theft via photographs rather than simply downloading data, travelling overseas, approaching other organizations, and delivering presentations. Contrary to previous assumptions about IP theft, the BSA revealed multiple, complex pathways that were not linear. The analysis showed the work behind seeking out potential organizations to sell the stolen IP. This occurred in some cases on multiple occasions (until the insider was successful at selling or continued, gaining multiple transactions). Uniquely, the paper proposes a new way forward in considering insider threats. We argue that insider threat takes place via non-linear and multiple pathways. Understanding insider threat by applying this framework opens up new, improved methods to prevent and detect Drawing from Situational Crime Prevention Theory, we provide guidelines for policymakers to make it harder for insiders to commit these acts (e.g., policies around personal devices and travel).

Studying behaviour outside of the laboratory is often difficult as information may be incomplete, idiosyncratic, fragmented, partly qualitative, and rapidly changing. Developing methods to detect and analyse the non-random, syntactic structure of behaviour allows researchers to understand and predict future behaviours. This symposium will provide a series of talks centred around Sequence Analysis methods, which allow the progression of real-world, complex behaviours (both animal and human) to be mapped and understood. The symposium will begin with a brief outline of the basic approach of Lag-Sequence Analysis (LSA), aimed at those with no prior experience or knowledge of Sequence Analysis research. This talk will also focus on Indicator Waves, a novel method of sequencing multiple, concurrent behaviours across time. The second talk will explain the use of proximity coefficients to analyse the interrelationships among sequences of behaviours within and between cases. Using examples from law enforcement interactions, the talk will show how this approach opens up conventional inference testing across variables that distinguish different sequences. The final talks will outline the T-System Approach in Sequence Analysis. The T-System is a formally defined set of probabilistic patterns of relations between behaviours or events on a discrete time scale. This may seem quite similar to LSA; however, the T-System approach allows for much more sophisticated, hierarchical analyses of sequential and concurrent behaviour over time. These complex T-System analyses will be clearly explained to show how hidden behavioural relationships can be detected, which would be impossible with traditional LSA methods. The T-Systems talks will include novel, extended analysis of T-Pattern sets for the new T-prediction and T-retrodiction. In addition, the newly updated THEME software, with increased speed of large dataset analysis, will be outlined, with applications to big data. Finally, drawing from the literature, examples will be provided on how the T-System approach can be applied to research in human and non-human samples. The symposium will end with a discussion and evaluation of which method is best for particular research questions or approaches, and the future of all these methods will be discussed.