{'fraction_non_alphanumeric': 0.008325624421831638, 'fraction_numerical': 0.0, 'mean_word_length': 5.720496894409938, '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}}
Research on Risk Assessment Method of Internet of Things Architecture Based on Parameter Joint Optimization

In order to solve the problems of low accuracy and poor stability of traditional Internet of Things network risk assessment, a risk assessment method of Internet of Things framework based on parameter joint optimization is proposed. By standardizing and optimizing the operating parameters of Internet of Things network structure, the evaluation parameters of the Internet of Things are effectively detected, and the node structure of the Internet of Things neural network is optimally set according to the standardized parameters, thus effectively detecting and correcting the risk parameters and achieving the requirement of accurate assessment of the risks of the Internet of Things framework. Finally, The experiment proves that the risk assessment method of Internet of Things architecture based on parameter joint optimization has higher stability and accuracy than the risk assessment method of predictive mapping network, and fully meets the research requirements.