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Results: 14
Number of items: 14
  • Open Access
    Peltonen, E., Bayhan, S., Bermbach, D., Buschjager, S., Degeler, V., Ding, A. Y., Incel, Ö. D., Katare, D., Kjargaard, M. B., Leroux, S., Mahmoodi, T., Mann, Z. Á., Meratnia, N., Pimentel, A. D., Rellermeyer, J. S., Rivière, E., Sapra, D., Solmaz, G., & van der Waaij, B. (2025). Rethinking Computing Systems in the Era of Climate Crisis: A Call for a Sustainable Computing Continuum. IEEE Internet Computing, 29(2), 8-18. https://doi.org/10.1109/MIC.2025.3566642
  • Open Access
    Chabal, D., Muller, T., Zhang, E., Sapra, D., de Laat, C., & Mann, Z. Á. (2025). COLIBRI: Optimizing Multi-party Secure Neural Network Inference Time for Transformers. In L. Nemec Zlatolas, K. Rannenberg, T. Welzer, & J. Garcia-Alfaro (Eds.), ICT Systems Security and Privacy Protection: 40th IFIP International Conference, SEC 2025, Maribor, Slovenia, May 21–23, 2025 : proceedings (Vol. I, pp. 17-31). (IFIP Advances in Information and Communication Technology; Vol. 745). Springer. https://doi.org/10.1007/978-3-031-92882-6_2
  • Open Access
    van Dijk, R., van de Wetering, J., Argentini, R., Gorka, L., van Luenen, A. F., Minnema, S., Rijgersberg, E., Ugen, M., Mann, Z. Á., & Geradts, Z. (2025). PaSSw0rdVib3s! AI-assisted password recognition for digital forensic investigations. Forensic Science International: Digital Investigation, 52(supplement), Article 301870. https://doi.org/10.1016/j.fsidi.2025.301870
  • Prins, J., & Mann, Z. Á. (2024). Secure Neural Network Inference for Edge Intelligence: Implications of Bandwidth and Energy Constraints. In S. Pal, C. Savaglio, R. Minerva, & F. C. Delicato (Eds.), IoT Edge Intelligence (pp. 265–288). (Internet of Things). Springer. https://doi.org/10.1007/978-3-031-58388-9_9
  • Zhang, E., & Mann, Z. Á. (2024). Predicting the Execution Time of Secure Neural Network Inference. In N. Pitropakis, S. Katsikas, S. Furnell, & K. Markantonakis (Eds.), ICT Systems Security and Privacy Protection: 39th IFIP International Conference, SEC 2024, Edinburgh, UK, June 12–14, 2024, Proceedings (Vol. Cham, pp. 481–494). (IFIP Advances in Information and Communication Technology; Vol. 710). Springer. https://doi.org/10.1007/978-3-031-65175-5_34
  • Open Access
    Islam, T., Oprescu, A., Mann, Z. Á., & Klous, S. (2024). A Framework to Optimize the Energy Cost of Securing Neural Network Inference. In IEEE Congress on Cybermatics: 2024 IEEE International Conferences on Internet of Things (iThings), IEEE Green Computing and Communications (GreenCom), IEEE Cyber, Physical and Social Computing (CPSCom), IEEE Smart Data (SmartData): Cybermatics 2024: iThings 2024 GreenCom 2024 CPSCom 2024 SmartData 2024 : 19-22 August 2024, Copenhagen, Denmark : proceedings (pp. 339–346). IEEE Computer Society. https://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics62450.2024.00073
  • Open Access
    Mann, Z. Á. (2024). Urgency in Cybersecurity Risk Management: Toward a Solid Theory. In 2024 IEEE 37th Computer Security Foundations Symposium: proceedings : 8-12 July 2024, Enschede, The Netherlands (pp. 651-664). (CSF). IEEE Computer Society. https://doi.org/10.1109/CSF61375.2024.00051
  • Open Access
    Regazzoni, F., Acs, G., Aszalos, A. Z., Avgerinos, C., Bakalos, N., Berral, J. L., Bos, J. W., Brohet, M., Castillo Sanz, A. G., Davies, G. T., Florescu, S., Flory, P.-E., Gutierrez-Torre, A., Haleplidis, E., Héliou, A., Ioannidis, S., El-Kady, A. I., Kapusta, K., Karagianni, K., ... Fournaris, A. P. (2024). SECURED for Health: Scaling Up Privacy to Enable the Integration of the European Health Data Space. In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE): proceedings : Valencia, Spain, 25-27 March 2024 (pp. 1552-1555). IEEE. https://doi.org/10.23919/DATE58400.2024.10546514
  • Open Access
    Mann, Z. A., Weinert, C., Chabal, D., & Bos, J. W. (2024). Towards Practical Secure Neural Network Inference: The Journey So Far and the Road Ahead. ACM Computing Surveys, 56(5), Article 117. https://doi.org/10.1145/3628446
  • Open Access
    Batool, K., Anwar, S., & Mann, Z. Á. (2024). SecFePAS: Secure Facial-Expression-Based Pain Assessment with Deep Learning at the Edge. In 2024 IEEE/ACM Symposium on Edge Computing: SEC 2024 : 4-7 December 2024, Rome, Italy : proceedings (pp. 417-424). IEEE Computer Society. https://doi.org/10.1109/SEC62691.2024.00046
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