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Research Article
Optimized Differential Private Online Transaction Scheme for Online Shopping
Jayasree V1
Dr. F. Ramesh Dhanaseelan2
1PG MCA Student, Department of MCA, ST.Xavier’s Catholic College of Engineering, Nagercoil, India. 2Professor, Department of MCA, ST.Xavier’s Catholic College of Engineering, Nagercoil, India.
Published Online: July-August 2022
Pages: 241-243
Cite this article
No DOIReferences
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[3] R. Ganesan et al., “A secured hybrid architecture model for internet banking (e-banking),” The J. Internet Banking Commerce, vol. 14,
no. 1, pp. 1–17, 1970.
[4] M. Tebaa, K. Zkik, and S. El Hajji, “Hybrid homomorphic encryption method for protecting the privacy of banking data in the cloud,”
Int. J. Secur.Appl., vol. 9, no. 6, pp. 61–70, 2015.
[5] Z. Zhang, Z. Qin, L. Zhu, J. Weng, and K. Ren, “Cost-friendly differential privacy for smart meters: Exploiting the dual roles of the
noise,” IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 619–626,Mar. 2017.
[6] M. Hardt and K. Talwar, “On the geometry of differential privacy,” in Proc. 42ndACMSymp. Theory Comput., 2010, pp. 705–714.
[7] S. Meiser and E. Mohammadi, “Tight on budget?Tight bounds for r-fold approximate differential privacy,” in Proc. ACM SIGSAC
Conf. Comput.Commun.Secur., 2018, pp. 247–264.
[8] F. Farokhi and H. Sandberg, “Ensuring privacy with constrained additive noise by minimizing fisher information,” Automatica, vol.
99, pp. 275–288, 2019.
[9] J. Soria-Comas, J. Domingo-Ferrer, D. S_anchez, and D. Meg_ıas, “Individual differential privacy: A utility-preserving formulation of
differential privacy guarantees,” IEEE Trans. Inf. Forensics Security, vol. 12, no. 6, pp. 1418–1429, Jun. 2017.
[10] T. Zhu, P. Xiong, G. Li, and W. Zhou, “Correlated differential privacy: Hiding information in non-IID data set,” IEEE Trans. Inf.
Forensics Security, vol. 10, no. 2, pp. 229–242, Feb. 2015.
[11] M. Fanaeepour and B. I. P. Rubinstein, “Histogramming privately ever after: Differentially-private data-dependent error bound
optimisation,” in Proc. IEEE 34th Int. Conf.Data Eng., 2018, pp. 1204–1207.
[12] K. Chaudhuri, J. Imola, and A. Machanavajjhala, “Capacity bounded differential privacy,” in Proc. Int. Conf. Neural Inf. Process.
Syst., 2019, pp. 3469–3478.
[13] Z. Zhang, W. Cao, Z. Qin, L. Zhu, Z. Yu, and K. Ren, “When privacy meets economics: Enabling differentially-private
batterysupported meter reporting in smart grid,” in Proc. IEEE/ACM 25th Int. Symp. Quality Service, 2017, pp. 1–9.
[14] D. Cynthia and L. Jing, “Differential privacy and robust statistics,” in Proc. 41st ACM Symp. Theory Comput., 2009, pp. 371–380.
[15] D. Cynthia, “Differential privacy,” in Proc. Automata Lang. Program., 2006, pp. 1–10.
[16] M. Chiang and T. Zhang, “Fog and IoT: An overview of research opportunities,” IEEE Internet Things J., vol. 3, no. 6, pp. 854–864,
Dec. 2016.
[17] C. Dwork, “Differential privacy: A survey of results,” in Proc. Int. Conf. Theory Appl. Models Comput., 2008, pp. 1–19.
[18] T. Zhu, G. Li, W. Zhou, and P. S. Yu, “Differentially private data publishing and analysis: A survey,” IEEE Trans. Knowl. Data
Eng.,vol. 29, no. 8, pp. 1619–1638, Aug. 2017.
Comput.Secur., vol. 21, no. 3, pp. 253–265, 2002.
[2] S. Kiljan, H. P. E. Vranken, and M. C. J. D. van Eekelen, “Evaluation of transaction authentication methods for online banking,”
Future Gener.Comput.Syst., vol. 80, pp. 430–447, 2018.
[3] R. Ganesan et al., “A secured hybrid architecture model for internet banking (e-banking),” The J. Internet Banking Commerce, vol. 14,
no. 1, pp. 1–17, 1970.
[4] M. Tebaa, K. Zkik, and S. El Hajji, “Hybrid homomorphic encryption method for protecting the privacy of banking data in the cloud,”
Int. J. Secur.Appl., vol. 9, no. 6, pp. 61–70, 2015.
[5] Z. Zhang, Z. Qin, L. Zhu, J. Weng, and K. Ren, “Cost-friendly differential privacy for smart meters: Exploiting the dual roles of the
noise,” IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 619–626,Mar. 2017.
[6] M. Hardt and K. Talwar, “On the geometry of differential privacy,” in Proc. 42ndACMSymp. Theory Comput., 2010, pp. 705–714.
[7] S. Meiser and E. Mohammadi, “Tight on budget?Tight bounds for r-fold approximate differential privacy,” in Proc. ACM SIGSAC
Conf. Comput.Commun.Secur., 2018, pp. 247–264.
[8] F. Farokhi and H. Sandberg, “Ensuring privacy with constrained additive noise by minimizing fisher information,” Automatica, vol.
99, pp. 275–288, 2019.
[9] J. Soria-Comas, J. Domingo-Ferrer, D. S_anchez, and D. Meg_ıas, “Individual differential privacy: A utility-preserving formulation of
differential privacy guarantees,” IEEE Trans. Inf. Forensics Security, vol. 12, no. 6, pp. 1418–1429, Jun. 2017.
[10] T. Zhu, P. Xiong, G. Li, and W. Zhou, “Correlated differential privacy: Hiding information in non-IID data set,” IEEE Trans. Inf.
Forensics Security, vol. 10, no. 2, pp. 229–242, Feb. 2015.
[11] M. Fanaeepour and B. I. P. Rubinstein, “Histogramming privately ever after: Differentially-private data-dependent error bound
optimisation,” in Proc. IEEE 34th Int. Conf.Data Eng., 2018, pp. 1204–1207.
[12] K. Chaudhuri, J. Imola, and A. Machanavajjhala, “Capacity bounded differential privacy,” in Proc. Int. Conf. Neural Inf. Process.
Syst., 2019, pp. 3469–3478.
[13] Z. Zhang, W. Cao, Z. Qin, L. Zhu, Z. Yu, and K. Ren, “When privacy meets economics: Enabling differentially-private
batterysupported meter reporting in smart grid,” in Proc. IEEE/ACM 25th Int. Symp. Quality Service, 2017, pp. 1–9.
[14] D. Cynthia and L. Jing, “Differential privacy and robust statistics,” in Proc. 41st ACM Symp. Theory Comput., 2009, pp. 371–380.
[15] D. Cynthia, “Differential privacy,” in Proc. Automata Lang. Program., 2006, pp. 1–10.
[16] M. Chiang and T. Zhang, “Fog and IoT: An overview of research opportunities,” IEEE Internet Things J., vol. 3, no. 6, pp. 854–864,
Dec. 2016.
[17] C. Dwork, “Differential privacy: A survey of results,” in Proc. Int. Conf. Theory Appl. Models Comput., 2008, pp. 1–19.
[18] T. Zhu, G. Li, W. Zhou, and P. S. Yu, “Differentially private data publishing and analysis: A survey,” IEEE Trans. Knowl. Data
Eng.,vol. 29, no. 8, pp. 1619–1638, Aug. 2017.
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