Robert Lagerström

Simon Hacks, Robert Lagerström, Daniel Ritter

Process digitization and integration is an increasing need for enterprises, while cyber-attacks denote a growing threat. Using the Business Process Management Notation (BPMN) is common to handle the digital and integration focus within and across organizations. In other parts of the same companies, threat modeling and attack graphs are used for analyzing the security posture and resilience. In this paper, we propose a novel approach to use attack graph simulations on processes represented in BPMN. Our contributions are the identification of BPMN's attack surface, a mapping of BPMN elements to concepts in a Meta Attack Language (MAL)-based Domain-Specific Language (DSL), called coreLang, and a prototype to demonstrate our approach in a case study using a real-world invoice integration process. The study shows that non-invasively enriching BPMN instances with cybersecurity analysis through attack graphs is possible without much human expert input. The resulting insights into potential vulnerabilities could be beneficial for the process modelers.

Sotirios Katsikeas, Pontus Johnson, Mathias Ekstedt et al.

In order to provide a coherent overview of cyber security research, the Scopus academic abstract and citation database was mined to create a citation graph of 98,373 authors active in the field between 1949 and early 2020. The Louvain community detection algorithm was applied to the graph in order to identify existing research communities. The analysis discovered twelve top-level communities: access control, authentication, biometrics, cryptography (I & II), cyber-physical systems, information hiding, intrusion detection, malwares, quantum cryptography, sensor networks, and usable security. These top-level communities were in turn composed of a total of 80 sub-communities. The analysis results are presented for each community in descriptive text, sub-community graphs, and tables with, for example, the most-cited papers and authors. A comparison between the detected communities and topical areas defined by other related work, is also presented, demonstrating a greater researcher emphasis on cryptography, quantum cryptography, information hiding and biometrics, at the expense of laws and regulation, risk management and governance, and security software lifecycle.

Wenjun Xiong, Robert Lagerström

Modern vehicles contain more than a hundred Electronic Control Units (ECUs) that communicate over different in-vehicle networks, and they are often connected to the Internet, which makes them vulnerable to various cyber-attacks. Besides, data collected by the connected vehicles is directly connected to the vehicular network. Thus, big vehicular data are collected, which are valuable and generate insights into driver behavior. Previously, a probabilistic modeling and simulation language named vehicleLang is presented to analyze the security of connected vehicles. However, the privacy issues of vehicular data have not been addressed. To fill in the gap, this work present a privacy specification for vehicles based on vehicleLang, which uses the Meta Attack Language (MAL) to assess the security of connected vehicles in a formal way, with a special focus on the privacy aspect. To evaluate this work, test cases are also presented.