Safe Social Internet of Thing for Urban Mobility Services

Smart cities are characterized by smart heterogeneous devices that can interact and cooperate with each other by exchanging regularly big amounts of data with the big issue to treat sensitive data in a properly respectful manner, avoiding exposure to the risks that new technologies inevitably bring to the fore. This objective can only be pursued with adequate knowledge of the risks and methods of protection, for this reason in addition to producing materially functional results, it has been studied in depth the techniques of protection of personal data including the anonymization and pseud-anonymization of sensitive data. We provide the analysis of the state of the art that starts from the concepts of security and privacy and comes to an analysis of anonymization algorithms. This analysis tries to give an overview of the two fundamental issues in the field of data security: privacy, according to the European Regulation 2016 (GDPR) and the practical techniques with which it is preserved, with particular attention to anonymization algorithms: we analyze the advantages and disadvantages of the latter. The performance of the proposed solution is compared against that of a TraffictYpe-based DifferEntiated Reputation (TYDER) algorithm. This performance was evaluated in terms of QoS parameters such as delay, latency, packet loss and prediction error. The results show how MISSION outperforms TYDER in urban mobility scenario.