Prof. Dr. Rainer Schnell
Publications by type
Conference Papers
Chen, Y., Schnell, R., Armknecht, F., & Heng, Y. (2022*). Salting as a Countermeasure Against Attacks on Privacy Preserving Record Linkage Techniques. Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies, 353–360. Setúbal: SciTePress. DOI: 10.5220/0010787200003123
Christen, P., & Schnell, R. (2022). Avoiding the Peak of Inflated Expectations: Common Misconceptions in Population Data Research. International Journal of Population Data Science, 7, 27. DOI: 10.23889/ijpds.v7i3.1797
Schnell, R., & Weiand, S. V. (2022). Microsimulation of an Educational Attainment Register to Study Record Linkage Quality (Abstract). International Journal of Population Data Science, 7, 075. DOI: 10.23889/ijpds.v7i3.1848
Klingwort, J., & Schnell, R. (2020). Transport Survey Estimate Adjustment by Permanently Installed Highway-sensors Using Capture-recapture Techniques. In Statistics Canada (ed.), Proceedings of Statistics Canada Symposium 2018 - Combine to Conquer: Innovations in the Use of Multiple Sources of Data. Ottawa. URL: https://www.statcan.gc.ca/en/media/2294
Ranbaduge, T., Christen, P., & Schnell, R. (2020*). Secure and Accurate Two-Step Hash Encoding for Privacy-Preserving Record Linkage. In H. W. Lauw, R. C.-W. Wong, A. Ntoulas, E.-P. Lim, S.-K. Ng, & S. J. Pan (eds.), Advances in Knowledge Discovery and Data Mining (pp. 139–151). Cham: Springer International Publishing. DOI: 10.1007/978-3-030-47436-2_11
Ranbaduge, T., & Schnell, R. (2020*). Securing Bloom Filters for Privacy-preserving Record Linkage. CIKM ’20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 2185–2188. New York: Association for Computing Machinery. DOI: 10.1145/3340531.3412105
Schnell, R., & Borgs, C. (2020a*). Encoding Hierarchical Classification Codes for Privacy-Preserving Record Linkage Using Bloom Filters. In P. Cellier & K. Driessens (eds.), Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019 Workshops, CCIS 1168 (pp. 1–15). Würzburg: Springer. DOI: 10.1007/978-3-030-43887-6_12
Schnell, R., & Borgs, C. (2020b). Implementing Privacy-preserving National Health Registries. In Statistics Canada (ed.), Proceedings of Statistics Canada Symposium 2018 - Combine to Conquer: Innovations in the Use of Multiple Sources of Data. Ottawa. URL: https://www.statcan.gc.ca/en/media/2321
Vidanage, A., Christen, P., Ranbaduge, T., & Schnell, R. (2020*). A Graph Matching Attack on Privacy-Preserving Record Linkage. CIKM ’20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 1485–1494. New York: Association for Computing Machinery. DOI: 10.1145/3340531.3411931
Klingwort, J., Buelens, B., Burger, J., & Schnell, R. (2019*). Graph-based Inference from Non-Probability Road Sensor Data (H. Cherifi, J. F. Mendes, L. M. Rocha, S. Gaito, E. Moro, J. Gonçalves-Sá, & F. Santos, eds.). In (pp. 599–601). Lisbon. URL: https://shirshendu.ccny.cuny.edu/PDF%20Files/CPD_BookOfAbs.pdf
Schnell, R., & Redlich, S. (2019*). Web Scraping Online Newspaper Death Notices for the Estimation of the Local Number of Deaths. Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies HEALTHINF, 5, 319–325. SciTePress. DOI: 10.5220/0007382603190325
Vidanage, A., Ranbaduge, T., Christen, P., & Schnell, R. (2019*). Efficient Pattern Mining based Cryptanalysis for Privacy-Preserving Record Linkage. 2019 IEEE 35th International Conference on Data Engineering (ICDE), 1698–1701. DOI: 10.1109/ICDE.2019.00176
Christen, P., Vidanage, A., Ranbaduge, T., & Schnell, R. (2018*). Pattern-Mining Based Cryptanalysis of Bloom Filters for Privacy-Preserving Record Linkage. In D. Phung, V. Tseng, G. Webb, B. Ho, M. Ganji, & L. Rashidi (eds.), Advances in Knowledge Discovery and Data Mining. PAKDD 2018 (pp. 530–542). Cham: Springer. DOI: 10.1007/978-3-319-93040-4_42
Christen, P., Schnell, R., Vatsalan, D., & Ranbaduge, T. (2017*). Efficient Cryptanalysis of Bloom Filters for Privacy-Preserving Record Linkage. In J. Kim, K. Shim, L. Cao, J.-G. Lee, X. Lin, & Y.-S. Moon (eds.), Advances in Knowledge Discovery and Data Mining: 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I (pp. 628–640). Berlin: Springer. DOI: 10.1007/978-3-319-57454-7_49
Schnell, R., Richter, A., & Borgs, C. (2017*). A Comparison of Statistical Linkage Keys with Bloom Filter-based Encryptions for Privacy-preserving Record Linkage Using Real-world Mammography Data. Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) – Volume 5: HEALTHINF, 276–283. SCITEPRESS. DOI: 10.5220/0006140302760283
Stausberg, J., Waldenburger, A., Borgs, C., & Schnell, R. (2017*). Combining Different Privacy-Preserving Record Linkage Methods for Hospital Admission Data. Informatics for Health 2017, April 24-26, 2017, Manchester Central, UK, 161–165. EFMI/Farr. DOI: 10.3233/978-1-61499-753-5-161
Schnell, R., & Borgs, C. (2016*). Randomized Response and Balanced Bloom Filters for Privacy Preserving Record Linkage. IEEE International Conference on Data Mining (ICDM); Barcelona, 218–224. IEEE. URL: https://ieeexplore.ieee.org/document/7836669
Schnell, R., & Borgs, C. (2015*). Building a National Perinatal Database Without the Use of Unique Personal Identifiers. Proceedings of the 2015 IEEE 15th International Conference on Data Mining Workshop; Atlantic City, NJ, USA, 232–239. URL: https://ieeexplore.ieee.org/document/7395676
Sehili, Z., Kolb, L., Borgs, C., Schnell, R., & Rahm, E. (2015*). Privacy Preserving Record Linkage with PPJoin. Proceedings 16. GI-Konferenz für Datenbanksysteme in Business, Technologie und Web (BTW), LNI, 85–104. URL: https://dbs.uni-leipzig.de/files/research/publications/2015-3/pdf/P4Join-BTW2015.pdf
Schnell, R. (2013a*). Efficient Private Record Linkage of Very Large Datasets. Proceedings of the International Statistical Institute, 59th World Statistics Congress; Hong Kong, 1862–1867. URL: https://openaccess.city.ac.uk/id/eprint/14652/
Schnell, R. (2013b*). Privacy-Preserving Record Linkage and Privacy-Preserving Blocking for Large Files with Cryptographic Keys Using Multibit Trees. Proceedings of the Joint Statistical Meetings, 187–194. Alexandria: American Statistical Association. URL: https://openaccess.city.ac.uk/id/eprint/14431/
Bachteler, T., Schnell, R., & Reiher, J. (2010). An Empirical Comparison of Approaches to Approximate String Matching in Private Record Linkage. In Statistics Canada (ed.), Proceedings of Statistics Canada Symposium 2010. Social Statistics: the Interplay among Censuses, Surveys and Administrative Data (pp. 290–295). Ottawa: Statistics Canada.
Schnell, R., Bachteler, T., & Reiher, J. (2010). Private Record Linkage with Bloom Filters. In Statistics Canada (ed.), Proceedings of Statistics Canada Symposium 2010. Social Statistics: the Interplay among Censuses, Surveys and Administrative Data (pp. 304–309). Ottawa: Statistics Canada. URL: https://publications.gc.ca/collections/collection_2014/statcan/CS11-522-2010-eng.pdf
Schnell, R., Gramlich, T., Mosthaf, A., & Bender, S. (2010). Using Complete Administration Data for Nonresponse Analysis: the PASS Survey of Low-income Households in Germany. In Statistics Canada (ed.), Proceedings of Statistics Canada Symposium 2010. Social Statistics: the Interplay among Censuses, Surveys and Administrative Data (pp. 104–109). Ottawa: Statistics Canada. URL: https://publications.gc.ca/site/eng/9.569968/publication.html
Schnell, R., Bachteler, T., & Bender, S. (2003*). Record Linkage Using Error-prone Strings. Proceedings of the Section on Survey Research Methods, American Statistical Association, 3713–3717. URL: http://www.asasrms.org/Proceedings/y2003f.html
Schnell, R., & Kreuter, F. (2002*). Separating Interviewer and Sampling-point Effects. Proceedings of the Section on Survey Research Methods, American Statistical Association, 3132–3133. URL: http://www.asasrms.org/Proceedings/y2002f.html