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Authentication is the process of verifying a user’s identity for them to access a system’s resources. An authentication factor is a piece of information used for this authentication. Three well-known groups of authentication factors exist: knowledge-based (what you know), possession-based (what you have) and inherence-based (what you are). Authentication schemes belonging to distinct authentication factors can be combined in a multi-factor manner to increase security. Although multiple multi-factor proposals are seen in literature, the absence of a method that allows a proper comparison and selection of these authentication methods, based on an application’s security requirements, can be observed. Existing frameworks for the analysis of authentication methods have been identified through the realization of a systematic literature review, but most of these focus on specific contexts and do not provide a generic enough solution. Due to the above, this research focuses on the creation of a recommendation framework that guides in the comparison and selection of single and multi-factor authentication schemes, considering both the application’s requirements and its context. This has been attained not only through the knowledge found in literature, but the experience from industry experts has been compiled as well through the collaboration with a multinational software development company. Consequently, the knowledge found in literature has been obtained from a systematic literature review, whereas the experience from industry experts was obtained through a survey and interviews. The framework proposal has been generated based on the above and has been validated through an expert panel and a case study methodology in collaboration with the partnered software development company. A tool prototype has been constructed as well. The result is a recommendation framework for the comparison and selection of authentication methods that can support this decision process in multiple contexts.

Process mining allows the discovery, monitoring, and improvement of processes through records of their executions. When used for discovery, models depicting the process behavior can be obtained and then analyzed through a performance perspective, focusing on performance indicators for the dimension of interest. In process mining, there has been scarce research on the analysis of some dimensions, such as the cost dimension. A systematic literature review has been conducted to identify the methods used for analyzing the cost dimension in process mining and other process-oriented disciplines, the dimensions considered jointly with costs, and how such a joint analysis is carried out. The review identified 68 publications. The results indicate ample research within distinct disciplines, like business process management and cost management, regarding the costs of performing processes, their reporting and forecasting. However, there is a need to further enrich their visualization and analysis, and to provide cost-aware operational support. Moreover, the utility of further researching cost analysis jointly with other dimensions, like time, flexibility, and quality, is also observed. These results provide a structured focal point of research that can be considered when analyzing costs from a process perspective and the identification of research gaps within this domain.