The Coordination of Artificial Intelligence and Human Security Experts in the Field of Cybersecurity

Engel, Joel, 2020

Art der Arbeit Master Thesis
Auftraggebende
Betreuende Dozierende Hinkelmann, Knut
Keywords
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As the literature review and expert interviews conducted as part of this master's thesis revealed, it is becoming increasingly difficult for companies to protect their digital assets. There are a wide variety of challenges they are currently facing. As it could be shown, AI can significantly support companies in tackling many of these challenges. AI alone, however, is not capable of alleviating all the concerns companies have about cybersecurity issues as both interviewed experts and literature sources agree. The most significant added value can be achieved as a team of employees and AI, where they compensate for each other's weaknesses. This Master Thesis's goal was to develop a framework to help organizations implement AI in the cybersecurity domain in a way that it is optimally aligned with their employees. The framework is composed of different parts. The core of the framework is the methodical procedure for the conception, introduction, and operation of a coordination-optimized AI. From this procedure, references are made to the other parts of the Thesis, which all represent central components in the framework. Thus, acute challenges were identified in the context of this thesis and examined in terms of how strongly AI can support in overcoming them. Also, relevant characteristics of AI systems that foster a partnership with cybersecurity experts were determined. Besides, the framework addresses preconditions and key success factors for the successful use of AI in cybersecurity. To design the framework, interviews with experts in the field were conducted in parallel to an in-depth literature review. When selecting the experts, care was taken to ensure that they had as many different perspectives as possible to achieve a broad-based framework.
Studiengang: Business Information Systems (Master)
Vertraulichkeit: öffentlich
Art der Arbeit
Master Thesis
Autorinnen und Autoren
Engel, Joel
Betreuende Dozierende
Hinkelmann, Knut
Publikationsjahr
2020
Sprache der Arbeit
Englisch
Vertraulichkeit
öffentlich
Studiengang
Business Information Systems (Master)
Standort Studiengang
Olten