As the computational capabilities of IoT devices increase, decentralisation approaches of IoT-aware business processes (BPs) take advantage of them by transferring the execution of BP parts to IoT devices. These approaches aim at mainly decreasing the use of batteries and the communication cost. However, the use of IoT-aware BPs in critical systems makes it crucial to consider the reliability in decentralisation. This paper proposes an IoT-aware BP decentralisation approach, maximising the overall BP reliability. We use an adaptation of the Simulated Annealing algorithm, which approximates the globally optimal solution.

In recent years, we have witnessed the growing use of the Internet of Things (IoT) to automate and improve activities of Business Processes (BPs), especially in critical systems. Within these contexts, uncertainties and their impacts cannot be ignored, justifying the interest for risk assessment. Risk assessment in BPs should rely on a meaningful computation of the risk level considering the individual risk of BP elements. Moreover, decision makers need to have risk information at different granularity levels so they can focus on some specific parts of BPs and identify which process fragments contribute most to the BP risk level. Current proposals only analyse risk at the process level, without taking into account different BP granularity levels, and the way they calculate the risk level can prevent the analysis of worst case scenarios. This paper proposes an algorithm to calculate the process risk level that reveals the BP elements that contribute most to risk, thus supporting risk analysis at different BP granularity levels. In addition, our proposal enriches BP models with information about risk likelihood, business value of BP elements, and risk acceptance criteria. These contributions are as relevant as the increasing use of IoT aware BPs in critical systems, promoting the improvement of BPs with a risk perspective and well informed decision making.

The concept of device fingerprinting is based in the assumption that each electronic device holds a unique set of physical and/or logical features that others can capture and use to differentiate it from the whole. Web-based fingerprinting, a particular case of device fingerprinting, allows website owners to differentiate devices based on the set of information that browsers transmit. Depending on the techniques being used, a website can track a device based on its browser features (browser fingerprinting) or based on system settings (cross-browser fingerprinting). The latter allows identification of the device even when more than one browser is used. Several different works have introduced new techniques over the last years proving that fingerprinting can be done in multiple ways, but there is not a consolidated work gathering all of them. The current work identifies known web-based fingerprinting techniques, categorizing them as which ones are browser and which are cross-browser and showing real examples of the data that can be captured with each technique. The study is synthesized in a taxonomy, which provides a clear separation between techniques, making it easier to identify the threats to security and privacy inherent to each one.

Organizations that include several organizational units with similar business processes often suffer, with time, from the proliferation of processes variant models that significantly deviate from the original (to be followed) one. Take, for instance, student enrolment processes on distinct faculties of the same university, or healthcare processes of a National Health Service across distinct health centers. This can lead to poor global (process) management, since measuring and improving processes can be difficult with too many variants of the same business process. Related works analyse the generalisation and flexibility aspects of process models and related variants, but do not deal with the overall process model lifecycle, especially for this kind of organizations. This paper introduces a novel approach for the Governance and continuous improvement of process models for this kind of organizations. The approach is based on the general Business Process Management (BPM) cycle for process models, proposing concrete techniques for the phases of evaluation, classification and analysis between real and concrete variant models from each organizational unit. It includes the use of similarity metrics and flexibility in business processes, and the main output is a continuously improved template process model. This template foresees a common process part (best practice-based) including process elements collected from the process model variants verified in organizational units, and a flexible part, referring to possible (controlled) deviations that can be tolerated by the organization's headquarters. This approach enhances overall business process management and associated resources by enforcing uniform (good) behavior across similar organizational units. We present the results of our approach applied to a real-world case study of home-healthcare related business process models.

In this paper, we present a two-step approach for modelling controlled flexibility in software processes: (1) senior process engineers express which, where and how changes can be applied onto process elements, (2) other process participants can easily identify which changes they are allowed to perform, and act accordingly. To support this, we propose a flexibility meta-model and modelling language, and a software process modelling tool called FlexEPFC. Finally, we compare FlexEPFC with three other prominent process-aware tools: SPADE, JIL/Juliette and Jazz.