Home // CLOUD COMPUTING 2024, The Fifteenth International Conference on Cloud Computing, GRIDs, and Virtualization // View article

MANTRA: Towards a Conceptual Framework for Elevating Cybersecurity Applications Through Privacy-Preserving Cyber Threat Intelligence Sharing

Authors:
Philipp Fuxen
Murad Hachani
Rudolf Hackenberg
Mirko Ross

Keywords: Cyber Threat Intelligence; Federated Learning; Privacy-Preserving Data Sharing; Cybersecurity

Abstract:
In light of the escalating cyber threat landscape, this paper highlights the critical importance of Cyber Threat Intelligence while acknowledging the challenges that impede its effective dissemination, including reputational risks, technical barriers, and the existence of data silos. To address these issues, we propose the conceptual framework of the MANTRA network—a theoretical privacy-preserving Cyber Threat Intelligence sharing model intended to enhance cybersecurity measures across organizations of varying sizes and resource capacities. The MANTRA concept endeavors to overcome these dissemination challenges through the adoption of federated learning for dismantling data silos, the enhancement of data analytics for managing information overload, the application of secure protocols and peer-to-peer communication for safeguarding the confidentiality, integrity, and availability of Cyber Threat Intelligence data, and the promotion of inter-organizational collaboration via socio-economic governance models. This holistic strategy aims not only to facilitate the exchange of information on cyber threats, but also to strengthen the collective defense against the ever-evolving cyber threats. Central to this theoretical exploration are pivotal research questions: identifying the most effective data sources for the envisioned MANTRA network, discerning the methodologies and technologies critical for secure and efficient data exchange within MANTRA, and comprehending how specific application scenarios of MANTRA might impact the efficiency of cybersecurity tactics across diverse organizational contexts. In conclusion, MANTRA presents a concept that combines a hybrid peer-to-peer architecture with federated learning and offers a promising framework for privacy-preserving Cyber Threat Intelligence sharing that should be further explored and validated in future research.

Pages: 34 to 41

Copyright: Copyright (c) IARIA, 2024

Publication date: April 14, 2024

Published in: conference

ISSN: 2308-4294

ISBN: 978-1-68558-156-5

Location: Venice, Italy

Dates: from April 14, 2024 to April 18, 2024