Machine Learning Techniques as Mechanisms for Data Protection and Privacy

Author:

Viloria Amelec,Alberto Nelson,Turriago John Rhenals

Publisher

Springer Singapore

Reference21 articles.

1. Gupta, R., Anand, P., Chaudhury, S., Lall, B., Singh, S.: Compressive Sensing-Based Privacy for Fall Detection (2020). arXiv preprint arXiv:2001.03463

2. Bhave, D.P., Teo, L.H., Dalal, R.S.: Privacy at work: a review and a research agenda for a contested terrain. J. Manag. 46(1), 127–164 (2020)

3. Shateri, M., Messina, F., Piantanida, P., Labeau, F.: Privacy-Cost Management in Smart Meters Using Deep Reinforcement Learning (2020). arXiv preprint arXiv:2003.04946

4. Bernabe, J.B., David, M., Moreno, R.T., Cordero, J.P., Bahloul, S., Skarmeta, A.: Aries: evaluation of a reliable and privacy-preserving European identity management framework. Futur. Gener. Comput. Syst. 102, 409–425 (2020)

5. Silva, J., Solano, D., Fernandez, C., Romero, L., Villa, J.V.: Privacy preserving, protection of personal data, and big data: a review of the Colombia case. Procedia Comput. Sci. 151, 1213–1218 (2019). https://doi.org/10.1016/j.procs.2019.04.174

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