Title Towards a Threat Model and Security Analysis for Data Cooperatives
Publication Type Conference Paper
Year of Publication 2022
Authors Salau, A, Dantu, R, Morozov, K, Upadhyay, K, Badruddoja, S
Conference Name 19th International Conference on Security and Cryptography (SECRYPT 2022)
Keywords Cybersecurity, Data Cooperatives, Secure Data Management, Security and Privacy., Threat Model
Abstract

Data cooperative (called “data coop” for short) is an emerging approach in the area of secure data management. It promises its users a better protection and control of their data, as compared to the traditional way of their handling by the data collectors (such as governments, big data companies, and others). However, for the success of data coops, existing challenges with respect to data management systems need to be adequately addressed. Especially, they concern terms of security and privacy, as well as the power imbalance between providers/owners and collectors of data. Designing a security and privacy model for a data coop requires a systematic threat modeling approach that identifies the security landscape, attack vectors, threats, and vulnerabilities, as well as the respective mitigation strategies. In this paper, we analyze the security of data cooperatives, identify potential security risks and threats, and suggest adequate countermeasures. We also discuss existing challenges that hinder the widespread adoption of data coops. 

DOI 10.5220/0011328700003283

Publication Status:

UNT Department:

UNT Center:

UNT Lab: