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The digitalization of our society is only possible in the presence of secure and reliable software systems governing ongoing critical processes, so-called critical information infrastructures. The understanding of mutual interdependencies of events and processes is crucial for cybersecurity and software reliability. One of the promising ways to tackle these challenges is process mining, which is a set of techniques that aims to mine essential knowledge from processes, thus providing more perspectives and temporal context to data interpretation and process understanding. However, it is unclear how process mining can help and can be practically used in the context of cybersecurity and reliability.Therefore, in this work, we investigate the potential of process mining to aid in cybersecurity and software reliability to analyze and support research efforts in these areas. Concretely, we collect existing process mining applications, discuss current trends and promising research directions that can be used to tackle the current cybersecurity and software reliability challenges. To this end, we conduct a systematic literature review covering 35 relevant research approaches to examine how the process mining is currently used for these tasks and what are the research gaps and promising research directions in the area. This work is an extension of our previous work, which focused solely on the cybersecurity area, based on the observation of relative closeness and similar goals of those two fields, in which some approaches tend to overlap.

A key challenge in System of Systems (SoS) engineering is the analysis and maintenance of global properties under SoS evolution, and the integration of new constituent elements. There is a need to model the constituent systems composing a SoS in order to allow the analysis of emergent behaviours at the SoS boundary. The Contract pattern allows the engineer to specify constrained behaviours to which constituent systems are required to conform in order to be a part of the SoS. However, the Contract pattern faces some limitations in terms of its accessibility and suitability for verifying contract compatibility. To address these deficiencies, we propose the enrichment of the Contract pattern, which hitherto has been defined using SysML and the COMPASS Modelling Language (CML), by utilising SysML and Object Constraint Language (OCL). In addition, we examine the potential of interface automata, a notation for improving loose coupling between interfaces of constituent systems defined according to the contract, as a means of enabling the verification of contract compatibility. The approach is demonstrated using a case study in audio/video content streaming.

Smart cities aim at integrating various IoT (Internet of Things) technologies by providing many opportunities for the development, governance, and management of user services. One of the ways to support this idea is to use cloud and edge computing techniques to reduce costs, manage resource consumption, enhance performance, and connect the IoT devices more effectively. However, the selection of services remains a significant research question since there are currently different strategies towards cloud computing, including services for central remote computing (traditional cloud model) as well as distributed local computing (edge computing). In this paper, we offer an integrated view of these two directions and the selection among the edge technologies based on MCDA (Multiple Criteria Decision Analysis) algorithms. To this end, we propose a foglet as a middleware that aims at achieving satisfactory levels of customer services by using fuzzy similarity and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to facilitate the rating and selection of services in the fog-to-cloud environment. Then, we describe the selection process with a numerical example, and conclude our work with an outline of future perspectives.

Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers’ computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process.