Year: 2026
Type: article
Abstract: Privacy risk assessment is difficult due to uncertainty, incomplete information, and the evolving nature of modern information systems. Existing methods often rely on precise probabilities or stochastic models that do not adequately capture epistemic uncertainty or conflicting evidence. This paper presents a structured Privacy Risk Assessment framework based on the Evidential Reasoning Model and Dempster-Shafer belief theory. The framework decomposes a risk object into hierarchical components, assertions, and evidence, enabling extensible and fine-grained risk computation. Dempster–Shafer theory aggregates heterogeneous evidence while explicitly representing belief, disbelief, and uncertainty, and the model supports incremental updates without full recomputation. A case study using a smart grid environment implementing the Green Button Initiative demonstrates that the approach provides systematic, transparent, and computationally efficient privacy risk evaluation in complex data-sharing systems.
Source: Pragmatic Cybersecurity
Authors: Raisa Islam, Dongwan Shin
Institution: New Mexico Institute of Mining and Technology
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Funder: National Science Foundation
OpenAlex ID: W7204924224
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