# Collecting, Processing and Secondary Using Personal and (Pseudo)Anonymized Data in Smart Cities
## 3 Background Concepts
### Key Terminology  
De-Identification, anonymization and pseudonymization are techniques used to reduce the likelihood of identifying individuals in a dataset with personal data. Its worth to mention there is no standard definition of these terms, and they are highly nuanced and context-dependent. Likewise, the terms De-Anonymization and Re-Identification are interchangeably misused. Therefore, this section provides clear definitions to establish the differences and correct use of these terms that are the basis of the terminology used throughout the paper, answering the RQ1. **De-Identification** consists of removing or obfuscating all personal information from a dataset to prevent the identification of individuals. De-identification is not necessarily an irreversible process and it is possible to foresee the existence of a mapping table that allows reversing the process (linking the original records to the de-identified records). In addition to the suppression of all identifying attributes, de-identification usually implies the modification of \"quasi-identifier\" via the generalization processes (e.g., modifying the scale of an attribute) or by introducing uncertainty factors based on the original values. **Anonymization** is usually considered a \"strong\" case of de-identification, as it aims to make it impractical or even impossible (using all reasonable means) to re-identify (including by the technician who performed the initial operation). In other words, in principle, it should be an irreversible process analogous to destruction. It should be noted that the scope of this definition is adaptable depending on the technological context of the moment: \"all means considered reasonable\", thus allowing the necessary resources, cost and knowledge necessary to carry out a re-identification to be considered. **Pseudonymization** is a process that aims to replace all personal identifiers (e.g., names, addresses and account number) with pseudonyms: artificially generated words or codes, which may function as masked representations of the original data. A \"strong\" pseudonymization is additionally concerned with focusing on the \"quasi-identifier\" attributes (e.g., date of birth) and that the attribution of codes is carried out randomly and independently of the original values (although they may eventually continue to be related to each other). Pseudonymization is an approach that provides a form of traceable anonymity \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Issue** & **None** & **Partially** & **Fully** \\  & & **Addressed** & **Addressed** \\ \hline \hline \begin{tabular}{c} Clarify the terms de-identification, \\ anonymization and \\ pseudonymization \\ \end{tabular} & — & [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 30] & Our Work \\ \hline \begin{tabular}{c} Clarify the terms de-anonymization \\ and re-identification \\ \end{tabular} & [13; 14; 15; 16; 17; 18; 19; 20; 22; 23; 24; 25; 26; 27; 30] & [21; 28; 29] & Our Work \\ \hline \
\begin{tabular}{c} Link the surveyed \\ privacy-preserving techniques to \\ practical privacy problems faced in \\ smart cities \\ \end{tabular} & [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27] & [28; 29; 30] & Our Work \\ \hline
\begin{tabular}{c} Covers smart city privacy concerns \\ \end{tabular} & [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27] & — & Our Work \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Issues addressed by the related work and our work. and requires legal, organizational or technical procedures. Consequently, the association can only be carried out under specific and controlled circumstances [31,32]. It should be noted that pseudonymization is not, as a rule, sufficient to guarantee, in light of the GDPR, that the final results of the operation no longer constitute personal data [33]. Additionally, it cannot be neglected that the combination of pseudonymized data with other datasets may allow the total or partial re-identification of individuals.