Selected Publicatoins

Below is a selection of publications. For an almost complete list, see here: DBLP, PubMed.

• FJ Sarmin, AR Sarkar, Y Wang, and N Mohammed.
  Synthetic data: revisiting the privacy-utility trade-off.
  International Journal of Information Security, 24(4), 2025. Springer.


• AR Sarkar, YS Chuang, N Mohammed, and X Jiang.
  De-identification is not enough: a comparison between de-identified and synthetic clinical notes.
  Scientific Reports, 14:29669, 2024. Nature.


• MMA Aziz, P. Thulasiraman, and N Mohammed.
  Parallel and private generalized suffix tree construction and query on genomic data.
  BMC Genomic Data, 23(1):45, 2022.


• MMA Aziz, T Ahmed, T Faequa, X Jiang, Y Yao, and N Mohammed.
  Differentially private medical texts generation using generative neural networks.
  ACM Transactions on Computing for Healthcare (HEALTH), 3(1): 27 pages, 2021.


• MMA Aziz, S Kamali, N Mohammed, and X Jiang.
  Online algorithm for differentially private genome-wide association studies.
  ACM Transactions on Computing for Healthcare (HEALTH), 2(2): 27 pages, 2021.


• T Ahmed, MMA Aziz, and N Mohammed.
  De-identification of electronic health record using neural network.
  Scientific Reports, 10(1):18600, 2020. NATURE.


• MSR Mahdi, MMA Aziz, D Alhadidi, and N Mohammed.
  Secure similar patients query on encrypted genomic data.
  IEEE Journal of Biomedical and Health Informatics, 23(6):2611-2618, 2019.


• MN Sadat, MMA Aziz, N Mohammed, F Chen, X Jiang, and S Wang.
  SAFETY: Secure gwAs in Federated Environment Through a hYbrid solution.
  IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 16(1):93-102, 2019.


• M. Rahman, T. Rahman, R. Laganiere, N. Mohammed, and Y. Wang.
  Membership inference attack against differentially private deep learning model.
  Transactions on Data Privacy (TDP), 11(1):61-79, 2018.


• MMA Aziz, D Alhadidi, and N Mohammed.
  Secure approximation of edit distance on genomic data.
  BMC Medical Genomics, 10(2):55-67, 2017.


• R Ghasemi, MMA Aziz, N Mohammed, M Dehkordi, and X Jiang.
  Private and efficient query processing on outsourced genomic databases.
  IEEE Journal of Biomedical and Health Informatics, 21(5): 1466-1472, 2017.


• N Mohammed, D Alhadidi, BCM Fung, and M Debbabi.
  Secure two-party differentially private data release for vertically-partitioned data.
  IEEE Transactions on Dependable and Secure Computing (TDSC), 11(1): 59-71, 2014.


• N Mohammed, X Jiang, R Chen, BCM Fung, and L Ohno-Machado.
  Privacy-preserving heterogeneous health data sharing.
  Journal of the American Medical Informatics Association (JAMIA), 20(3):462-469, 2013.


• R Chen, BCM Fung, N Mohammed, BC Desai, and K Wang.
  Privacy-preserving trajectory data publishing by local suppression.
  Information Sciences (INS), 231:83-97, 2013. Elsevier.


• D Alhadidi, N Mohammed, BCM Fung, and M Debbabi.
  Secure distributed framework for achieving ε-differential privacy.
  In Proceedings of the 12th Privacy Enhancing Technologies Symposium (PETS), LNCS 7834, pages 120-139, Vigo, Spain, July 2012.


• N Mohammed, BCM Fung, and M Debbabi.
  Anonymity meets game theory: secure data integration with malicious participants.
  Very Large Data Bases Journal (VLDBJ), 20(4):567-588, 2011.


• N Mohammed, R Chen, BCM Fung, and PS Yu.
  Differentially private data release for data mining.
  In Proceedings of the 17th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 493-501, San Diego, CA, August 2011.
  [ Source code - DiffGen | acceptance ratio (with oral presentation): 7.8% ]


• R Chen, N Mohammed, BCM Fung, BC Desai, and L Xiong.
  Publishing set-valued data via differential privacy.
  The Proceedings of the VLDB Endowment (PVLDB), 4(11):1087-1098, August 2011.


• N Mohammed, BCM Fung, PCK Hung, and C Lee.
  Centralized and distributed anonymization for high-dimensional healthcare data.
  ACM Transactions on Knowledge Discovery from Data (TKDD), 4(4):18:1-18:33, 2010.


• N Mohammed, BCM Fung, PCK Hung, and C Lee.
  Anonymizing healthcare data: a case study on the blood transfusion service.
  In Proceedings of the 15th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 1285-1294, Paris, France, June 2009.
  [ Source code - PAIS | acceptance ratio: 10% | Best student paper award ]