This paper presents a new implementation of personal data protection methods based on specific encryption and generalization algorithms implemented in Logstash plugins. Our encryption algorithm is adapted to personal data by considering the different categories: identifiers, quasi-identifiers, and sensitive attributes. In addition, our anonymization solution offers several generalization methods, which can be configured according to the data type. To validate the results of these methods, we also propose a step of verifying privacy protection models such as k-anonymity and l-diversity.