2026-05-28T07:39:56Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/325222026-02-03T12:27:30Zcom_10630_2254col_10630_37959

Luo Chen, Hao Qiang Segura, David Baena, Carlos Khatib, Emil Jatib Fortes-Rodríguez, Sergio Barco-Moreno, Raquel 2024-09-11T10:03:31Z 2024-09-11T10:03:31Z 2024 https://hdl.handle.net/10630/32522 The evolution of mobile networks is currently going through a stage of opening up the infrastructure, known as O-RAN, a paradigm that also proposes providing more intelligence to the Radio Access Network (RAN). The key element that allows this change is the RAN Intelligent Control (RIC). Possible service improvements to customers are affected by new security breaches that may occur on the network. This paper analyses the impact of poisoning and evasion attacks, where training and testing data, respectively, are altered on Machine Learning (ML) algorithms. To this end, an E2E scenario has been analysed, in which the direct effects on users’ perception are studied. spa http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Sistemas de comunicaciones inalámbricos Aprendizaje automático Proceso de datos Alteración de datos E2E: impacto de un ataque de envenenamiento y evasión en una red celular. conference output