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.
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