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Authors
# Name
1 THIAGO NOBREGA(thiago.pereira@copin.ufcg.edu.br)
2 Dimas Nascimento(dimas.cassimiro@ufape.edu.br)
3 Carlos Eduardo Pires(cesp@dsc.ufcg.edu.br)

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Reference
# Reference
1 Mohammad Al-Rubaie and J. Morris Chang. Privacy-Preserving Machine Learning: Threats and Solutions. IEEE Security & Privacy, 17(2):49–58, 3 2019
2 Carlo Batini and Monica Scannapieco. Data and Information Quality. Data-Centric Systems and Applications. Springer International Publishing, 1 edition, 2016
3 James H Boyd, Anna M Ferrante, Christine M O’Keefe, Alfred J Bass, Sean M Randall, and James B Semmens. Data linkage infrastructure for cross-jurisdictional health-related research in Australia. BMC health services research, 12(1):1–8, 2012.
4 Justin Brickell and Vitaly Shmatikov. Privacy-preserving classifier learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5628 LNCS:128–147, 2009
5 LA Bygrave. Data protection pursuant to the right to privacy in human rights treaties. International Journal of Law and Information Technology, 6(3):247–284, 01 1998.
6 Kamalika Chaudhuri and Claire Monteleoni. Privacy-preserving logistic regression. Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference, pages 289–296, 2009.
7 Peter Christen. Automatic record linkage using seeded nearest neighbour and support vector machine classification. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 151–159, 2008.
8 Peter Christen. Data Matching. Springer Berlin Heidelberg, Berlin, Heidelberg, 2012
9 Peter Christen, Thilina Ranbaduge, and Rainer Schnell. Linking Sensitive Data. Springer International Publishing, Cham, 2020
10 Peter Christen, Thilina Ranbaduge, Dinusha Vatsalan, and Rainer Schnell. Precise and Fast Cryptanal- ysis for Bloom Filter Based Privacy-Preserving Record Linkage. IEEE Trans. Knowl. Data Eng., 31(11):2164–2177, 2019.
11 Peter Christen, Rainer Schnell, Dinusha Vatsalan, and Thilina Ranbaduge. Efficient Cryptanalysis of Bloom Filters for Privacy-Preserving Record Linkage Peter, volume 10235 of Lecture Notes in Computer Science. Springer International Publishing, Cham, 2017
12 Peter Christen and Dinusha Vatsalan. A flexible data generator for privacy-preserving data mining and record linkage. 2012
13 Mary Cryan. Probability and Computing Randomized Algorithms and Probabilistic Analysis. JSTOR, 2006.
14 Xin Luna Dong and Theodoros Rekatsinas. Data Integration and Machine Learning. In Proceedings of the 2018 International Conference on Management of Data, pages 1645–1650, New York, NY, USA, 5 2018. ACM.
15 Cynthia Dwork. Theory and Applications of Models of Computation. 4978:1–19, 2008
16 Ashutosh Dhar Dwivedi, Gautam Srivastava, Shalini Dhar, and Rajani Singh. A decentralized privacy- preserving healthcare blockchain for iot. Sensors, 19(2):326, 2019
17 Cynthia Dwork and Aaron Roth. The algorithmic foundations of differential privacy. Foundations and Trends® in Theoretical Computer Science, 9(3–4):211–407, 2014.
18 Xi He, Ashwin Machanavajjhala, Cheryl Flynn, and Divesh Srivastava. Composing Differential Privacy and Secure Computation. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security - CCS ’17, number 1, pages 1389–1406, New York, New York, USA, 2017. ACM Press.
19 Ali Inan, Murat Kantarcioglu, Gabriel Ghinita, and Elisa Bertino. Private record matching using differential privacy. In Proceedings of the 13th International Conference on Extending Database Technology - EDBT ’10, page 123, New York, New York, USA, 2010. ACM Press
20 Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. An Introduction to Statistical Learn- ing. Springer Texts in Statistics. Springer New York, New York, NY, 2021.
21 Matthias Jarke and Christoph Quix. Federated Data Integration in Data Spaces, pages 181–194. Springer International Publishing, Cham, 2022.
22 Nishadi Kirielle, Peter Christen, and Thilina Ranbaduge. Transer: Homogeneous transfer learning for entity resolution. In Julia Stoyanovich, Jens Teubner, Paolo Guagliardo, Milos Nikolic, Andreas Pieris, Jan M¨uhlig, Fatma ¨Ozcan, Sebastian Schelter, H. V. Jagadish, and Meihui Zhang, editors, Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022, Edinburgh, UK, March 29 - April 1, 2022, pages 2:118–2:130. OpenProceedings.org, 2022
23 Nick Koudas, Sunita Sarawagi, and Divesh Srivastava. Record linkage: similarity measures and algorithms. In Proceedings of the 2006 ACM SIGMOD international conference on Management of data, pages 802–803, 2006
24 M. Kuzu, M. Kantarcioglu, E. a. Durham, C. Toth, and B. Malin. A practical approach to achieve private medical record linkage in light of public resources. Journal of the American Medical Informatics Association, pages 285–292, 2012
25 Mehmet Kuzu, Murat Kantarcioglu, Elizabeth Durham, and Bradley Malin. A Constraint Satisfac- tion Cryptanalysis of Bloom Filters in Private Record Linkage. Privacy Enhancing Technologies, 6794:226–245, 2011
26 Yehuda Lindell. Tutorials on the Foundations of Cryptography. Springer, 2017
27 Michael Loster, Ioannis Koumarelas, and Felix Naumann. Knowledge transfer for entity resolution with siamese neural networks. Journal of Data and Information Quality (JDIQ), 13(1):1–25, 2021.
28 Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean. Distributed Representations of Words and Phrases and their Compositionality. 10 2013.
29 Kato Mivule, Claude Turner, and Soo Yeon Ji. Towards a differential privacy and utility preserving machine learning classifier. Procedia Computer Science, 12:176–181, 2012
30 Hirofumi Miyajima, Noritaka Shigei, Syunki Makino, Hiromi Miyajima, Yohtaro Miyanishi, Shinji Kitagami, and Norio Shiratori. A proposal of privacy preserving reinforcement learning for secure multiparty computation. Artificial Intelligence Research, 6(2):57, 2017.
31 Thiago Nobrega, Carlos Eduardo S Pires, Dimas Cassimiro Nascimento, and Leandro Balby Marinho. Towards automatic privacy-preserving record linkage: A transfer learning based classification step. Data & Knowledge Engineering, 145:102180, 2023
32 Thiago Pereira da N´obrega, Carlos Eduardo Santos Pires, and Tiago Brasileiro Araujo. Avaliacao Empiricade Tecnicas de Comparacao Privada Aplicadas na Resolucao de Entidades. In Proceedings of the 31 st of the Brazilian Symposium on Databases (SBBD16), pages 121–126, 2016.
33 Thiago Nobrega. Towards Auditable and Intelligent Privacy-Preserving Record Linkage. PhD thesis, PPGCC/UFCG, 2022.
34 Thiago Nobrega, Carlos Eduardo S. Pires, and Dimas Cassimiro Nascimento. Blockchain-based privacy- preserving record linkage: enhancing data privacy in an untrusted environment. Information Systems, 102:101826, 2021
35 Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. Deep contextualized word representations. 2 2018
36 Robespierre Pita, Clicia Pinto, Pedro Melo, Malu Silva, Marcos Barreto, and Davide Rasella. A Spark- based workflow for probabilistic record linkage of healthcare data. CEUR Workshop Proceedings, 1330:17–26, 2015.
37 Hans-Ulrich Prokosch, Thomas Bahls, Martin Bialke, J¨urgen Eils, Christian Fegeler, Julian Gruendner, Birger Haarbrandt, Christopher Hampf, Wolfgang Hoffmann, Hauke Hund, et al. The covid-19 data exchange platform of the german university medicine. In Challenges of Trustable AI and Added-Value on Health, pages 674–678. IOS Press, 2022
38 Arun Rajkumar and Shivani Agarwal. A differentially private stochastic gradient descent algorithm for multiparty classification. Journal of Machine Learning Research, 22:933–941, 2012.
39 Fang Yu Rao, Jianneng Cao, Elisa Bertino, and Murat Kantarcioglu. Hybrid private record linkage: Sep- arating differentially private synopses from matching records. ACM Transactions on Privacy and Security, 22(3), 2019.
40 Mark Russinovich, Manuel Costa, C´edric Fournet, David Chisnall, Antoine Delignat-Lavaud, Sylvan Cleb- sch, Kapil Vaswani, and Vikas Bhatia. Toward confidential cloud computing. Communications of the ACM, 64(6):54–61, 2021.
41 Fengyi Tang, Wei Wu, Jian Liu, Huimei Wang, and Ming Xian. Privacy-preserving distributed deep learning via homomorphic re-encryption. Electronics (Switzerland), 8(4), 2019.
42 Saravanan Thirumuruganathan, Shameem A Puthiya Parambath, Mourad Ouzzani, Nan Tang, and Shafiq Joty. Reuse and Adaptation for Entity Resolution through Transfer Learning. 2018.
43 Dinusha Vatsalan, Dimitrios Karapiperis B, and Aris Gkoulalas-divanis. An Overview of Big Data Issues in Privacy-Preserving Record Linkage, volume 2. Springer International Publishing, 2019.
44 Dinusha Vatsalan and Peter Christen. Multi-Party Privacy-Preserving Record Linkage using Bloom Filters. 12 2016.
45 Dinusha Vatsalan, Peter Christen, and Vassilios S. Verykios. A taxonomy of privacy-preserving record linkage techniques. Information Systems, 38(6):946–969, 2013
46 Dinusha Vatsalan, Peter Christen, and Vassilios S Verykios. Ef fi cient Two-Party Private Blocking based on Sorted Nearest Neighborhood Clustering. pages 1949–1958, 2013.
47 Dinusha Vatsalan, Dimitrios Karapiperis, and Vassilios S Verykios. Privacy-Preserving Record Linkage. (January), 2018
48 Dinusha Vatsalan, Ziad Sehili, Peter Christen, and Erhard Rahm. Privacy-Preserving Record Linkage for Big Data : Current Approaches and Research Challenges. In Big Data Handbook. Springer, 2016.
49 Anushka Vidanage, Peter Christen, Thilina Ranbaduge, and Rainer Schnell. A Graph Matching Attack on Privacy-Preserving Record Linkage. Int. Conf. Inf. Knowl. Manag. Proc., pages 1485–1494, 2020
50 Anushka Vidanage, Thilina Ranbaduge, Peter Christen, and Rainer Schnell. Efficient Pattern Mining based Cryptanalysis for Privacy-Preserving Record Linkage. Proceedings - International Conference on Data Engineering, pages 1698–1701, 2019
51 Anushka Vidanage, Thilina Ranbaduge, Peter Christen, and Rainer Schnell. A taxonomy of attacks on privacy-preserving record linkage. Journal of Privacy and Confidentiality, 12(1), 2022
52 Jiasi Weng, Jian Weng, Jilian Zhang, Ming Li, Yue Zhang, and Weiqi Luo. Deepchain: Auditable and privacy-preserving deep learning with blockchain-based incentive. IEEE Transactions on Dependable and Secure Computing, 18(5):2438–2455, 2019.