Inicio  /  Future Internet  /  Vol: 14 Par: 6 (2022)  /  Artículo
ARTÍCULO
TITULO

Data Anonymization: An Experimental Evaluation Using Open-Source Tools

Joana Tomás    
Deolinda Rasteiro and Jorge Bernardino    

Resumen

In recent years, the use of personal data in marketing, scientific and medical investigation, and forecasting future trends has really increased. This information is used by the government, companies, and individuals, and should not contain any sensitive information that allows the identification of an individual. Therefore, data anonymization is essential nowadays. Data anonymization changes the original data to make it difficult to identify an individual. ARX Data Anonymization and Amnesia are two popular open-source tools that simplify this process. In this paper, we evaluate these tools in two ways: with the OSSpal methodology, and using a public dataset with the most recent tweets about the Pfizer and BioNTech vaccine. The assessment with the OSSpal methodology determines that ARX Data Anonymization has better results than Amnesia. In the experimental evaluation using the public dataset, it is possible to verify that Amnesia has some errors and limitations, but the anonymization process is simpler. Using ARX Data Anonymization, it is possible to upload big datasets and the tool does not show any error in the anonymization process. We concluded that ARX Data Anonymization is the one recommended to use in data anonymization.

 Artículos similares

       
 
Valerie Hernley, Aleksandar Jemcov, Jeongseek Kang, Matthew Montgomery and Scott C. Morris    
The relationship between aerodynamic forcing and non-synchronous vibration (NSV) in axial compressors remains difficult to ascertain from experimental measurements. In this work, the relationship between casing pressure and blade vibration was investigat... ver más

 
Oscar Bermejo, Juan Manuel Gallardo, Adrian Sotillo, Arnau Altuna, Roberto Alonso and Andoni Puente    
Labyrinth seals are commonly used in turbomachinery in order to control leakage flows. Flutter is one of the most dangerous potential issues for them, leading to High Cycle Fatigue (HCF) life considerations or even mechanical failure. This phenomenon dep... ver más

 
Marwa Salah Farhan, Amira Youssef and Laila Abdelhamid    
Traditional data warehouses (DWs) have played a key role in business intelligence and decision support systems. However, the rapid growth of the data generated by the current applications requires new data warehousing systems. In big data, it is importan... ver más

 
Aristeidis Karras, Anastasios Giannaros, Christos Karras, Leonidas Theodorakopoulos, Constantinos S. Mammassis, George A. Krimpas and Spyros Sioutas    
In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data, enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive data produced by numerous connected devices. Our study introduces ... ver más
Revista: Future Internet

 
Khaqan Baluch, Heon-Joon Park, Kyuchan Ji and Sher Q. Baluch    
Whilst numerical modelling is commonly used for simulation to check the design of water conveyance, sluicing and spillway structure design, the numerical modelling has rarely been compared with the physical model tests. The objective of this research pre... ver más
Revista: Water