@article{article_923267, title={Mondrian Based Real Time Anonymization Model}, journal={Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi}, volume={8}, pages={472–483}, year={2021}, DOI={10.35193/bseufbd.923267}, author={Civelek, İrem and Aydın, Muhammed Ali}, keywords={Kimliksizleştirme, Mahremiyet Koruma Modeli, Spark}, abstract={The presence of private information belonging to individuals in data heaps called "Big Data" causes the privacy of the person to be endangered against disclosure attacks. To protect personal privacy in big data, it is ensured that anonymous data is created, stored, and shared in systems with anonymization methods. However, de-identified data cannot be reinstatement. The aim of this study is to create a new method that provides instant disidentification and does not disrupt the data structure in the system. In the study, the Hadoop ecosystem was used to process large data heaps. With the proposed model, it has been ensured that the requests from the user are processed in the Hadoop ecosystem with the services in the middle layer, thus obtaining anonymous data. The algorithm used for disidentification is optimized and results are compared according to algorithms in the literature. With the proposed model, it has been observed that the user is user-friendly in terms of querying and obtaining an anonymous data set. According to the analysis results, an algorithm that works with 40% efficiency compared to other algorithms in terms of processing speed was created with the disidentification algorithm used in the model.}, number={1}, publisher={Bilecik Şeyh Edebali Üniversitesi}