Zero-Trust Security Models for Cloud Data Analytics: Enhancing Privacy in Distributed Systems
DOI:
https://doi.org/10.47363/JAICC/2025(4)415Keywords:
Abstract, Academic Literature, Scientific Literature, Reader Interaction, Contributions, Contextual Importance, Current Problems, Future Lines, Implementation, Evaluations, Privacy, Distributed Computing, Googlization of Information, Random Graph, Distributed Data, Privacy Compromise, Zero Trust Security, Robust Systems, Cloud ArchitecturesAbstract
The abstract is typically the first item that interacts deeply with a reader of academic and scientific literature to point out the contributions and contextualize the importance of the subject, indicating current problems and future lines that might be addressed by the implementation and evaluations. Therefore, the abstract is a compelling component of a paper or a report, besides being one of the first parts of the text that a reader uses to assess the relevance of reading the full text. In this research report, we provide a survey on the importance of privacy for distributed computing, while demonstrating the relevance of the data evaluation behind personal data sensitivity. We provide a detailed study on the Googlization of information, random graphs, and related distributed data, showing the dangers of privacy compromise. We present an independent survey on zero trust-based security models for the secure implementation of robust distributed systems and show that the systems can be efficiently implemented in cloud architectures.
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