@Article{cmes.2025.072603,
AUTHOR = {Borja Bordel Sánchez, Ramón Alcarria, Tomás Robles},
TITLE = {Information Diffusion Models and Fuzzing Algorithms for a Privacy-Aware Data Transmission Scheduling in 6G Heterogeneous <i>ad hoc</i> Networks},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {146},
YEAR = {2026},
NUMBER = {2},
PAGES = {--},
URL = {http://www.techscience.com/CMES/v146n2/66295},
ISSN = {1526-1506},
ABSTRACT = {In this paper, we propose a new privacy-aware transmission scheduling algorithm for 6G <i>ad hoc</i> networks. This system enables end nodes to select the optimum time and scheme to transmit private data safely. In 6G dynamic heterogeneous infrastructures, unstable links and non-uniform hardware capabilities create critical issues regarding security and privacy. Traditional protocols are often too computationally heavy to allow 6G services to achieve their expected Quality-of-Service (QoS). As the transport network is built of <i>ad hoc</i> nodes, there is no guarantee about their trustworthiness or behavior, and transversal functionalities are delegated to the extreme nodes. However, while security can be guaranteed in extreme-to-extreme solutions, privacy cannot, as all intermediate nodes still have to handle the data packets they are transporting. Besides, traditional schemes for private anonymous <i>ad hoc</i> communications are vulnerable against modern intelligent attacks based on learning models. The proposed scheme fulfills this gap. Findings show the probability of a successful intelligent attack reduces by up to 65% compared to <i>ad hoc</i> networks with no privacy protection strategy when used the proposed technology. While congestion probability can remain below 0.001%, as required in 6G services.},
DOI = {10.32604/cmes.2025.072603}
}