{'fraction_non_alphanumeric': 0.014010507880910683, 'fraction_numerical': 0.0, 'mean_word_length': 4.836734693877551, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
OCPP security - Neural network for detecting malicious traffic

Because the electric mobility has its focus on eco-friendly means of transport, a distributed platform designed for a smart city environment that can manage the electrical charging stations is vital. One of the major problems of distributed systems and cloud is security. The purpose of this article is to determine the malicious traffic using a backpropagation neural network. The main focus of the paper is to present a composite network that is able to detect faulted, random and normal types of traffic.