| On the role of data anonymization in machine learning privacy N Senavirathne, V Torra 2020 IEEE 19th International conference on trust, security and privacy in …, 2020 | 21 | 2020 |
| Integrally private model selection for decision trees N Senavirathne, V Torra computers & security 83, 167-181, 2019 | 13 | 2019 |
| Approximating robust linear regression with an integral privacy guarantee N Senavirathne, V Torra 2018 16th Annual Conference on Privacy, Security and Trust (PST), 1-10, 2018 | 9 | 2018 |
| Rounding based continuous data discretization for statistical disclosure control N Senavirathne, V Torra Journal of Ambient Intelligence and Humanized Computing 14 (11), 15139-15157, 2023 | 8 | 2023 |
| Integral privacy compliant statistics computation N Senavirathne, V Torra Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS …, 2019 | 4 | 2019 |
| Dissecting membership inference risk in machine learning N Senavirathne, V Torra Cyberspace Safety and Security: 13th International Symposium, CSS 2021 …, 2022 | 3 | 2022 |
| Towards Privacy Preserving Micro-data Analysis: A machine learning based perspective under prevailing privacy regulations N Senavirathne University of Skövde, 2021 | 3 | 2021 |
| Maximal c consensus meets V Torra, N Senavirathne Information Fusion 51, 58-66, 2019 | 2 | 2019 |
| Systematic evaluation of probabilistic K-anonymity for privacy preserving micro-data publishing and analysis N Senavirathne, V Torra 18th International Conference on Security and Cryptography, SECRYPT 2021 …, 2021 | | 2021 |
| Addressing the challenges of privacy preserving machine learning in the context of data anonymization N Senavirathne University of Skövde, 2019 | | 2019 |
