• Mo F, Tarkhani Z and Haddadi H. (2024). Machine Learning with Confidential Computing: A Systematization of Knowledge. ACM Computing Surveys. 56:11. (1-40). Online publication date: 30-Nov-2024.

    https://doi.org/10.1145/3670007

  • Xue J, Zheng M, Sheng Y, Yang L, Lou Q and Jiang L. TrojFair: Trojan Fairness Attacks. Proceedings of the 1st ACM Workshop on Large AI Systems and Models with Privacy and Safety Analysis. (47-56).

    https://doi.org/10.1145/3689217.3690620

  • Yadav C, Chowdhury A, Boneh D and Chaudhuri K. FairProof. Proceedings of the 41st International Conference on Machine Learning. (55682-55705).

    /doi/10.5555/3692070.3694365

  • Laine J, Minkkinen M and Mäntymäki M. (2024). Ethics-based AI auditing. Information and Management. 61:5. Online publication date: 1-Jul-2024.

    https://doi.org/10.1016/j.im.2024.103969

  • Toreini E, Mehrnezhad M and van Moorsel A. (2023). Fairness as a Service (FaaS): verifiable and privacy-preserving fairness auditing of machine learning systems. International Journal of Information Security. 23:2. (981-997). Online publication date: 1-Apr-2024.

    https://doi.org/10.1007/s10207-023-00774-z

  • Duddu V, Das A, Khayata N, Yalame H, Schneider T and Asokan N. (2024). Attesting Distributional Properties of Training Data for Machine Learning. Computer Security – ESORICS 2024. 10.1007/978-3-031-70879-4_1. (3-23).

    https://link.springer.com/10.1007/978-3-031-70879-4_1

  • Freiberger V and Buchmann E. (2024). Fairness Certification for Natural Language Processing and Large Language Models. Intelligent Systems and Applications. 10.1007/978-3-031-66329-1_39. (606-624).

    https://link.springer.com/10.1007/978-3-031-66329-1_39

  • Will N and Maziero C. (2023). Intel Software Guard Extensions Applications: A Survey. ACM Computing Surveys. 55:14s. (1-38). Online publication date: 31-Dec-2024.

    https://doi.org/10.1145/3593021

  • Toreini E, Mehrnezhad M and van Moorsel A. Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems. Computer Security. ESORICS 2023 International Workshops. (569-584).

    https://doi.org/10.1007/978-3-031-54129-2_34

  • Karan A, Balepur N and Sundaram H. Your Browsing History May Cost You: A Framework for Discovering Differential Pricing in Non-Transparent Markets. Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. (717-735).

    https://doi.org/10.1145/3593013.3594038

  • Lo D. (2023). Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmaps 2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE). 10.1109/ICSE-FoSE59343.2023.00010. 979-8-3503-2496-9. (69-85).

    https://ieeexplore.ieee.org/document/10449668/

  • Kolberg J. (2023). Fairness von Biometrischen Systemen. Datenschutz und Datensicherheit - DuD. 10.1007/s11623-022-1709-1. 47:1. (15-21). Online publication date: 1-Jan-2023.

    https://link.springer.com/10.1007/s11623-022-1709-1

  • Searle R, Gururaj P, Gupta A and Kannur K. (2022). Secure Implementation of Artificial Intelligence Applications for Anti-Money Laundering using Confidential Computing 2022 IEEE International Conference on Big Data (Big Data). 10.1109/BigData55660.2022.10021108. 978-1-6654-8045-1. (3092-3098).

    https://ieeexplore.ieee.org/document/10021108/

  • Kolberg J, Rathgeb C and Busch C. The Influence of Gender and Skin Colour on the Watchlist Imbalance Effect in Facial Identification Scenarios. Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. (465-478).

    https://doi.org/10.1007/978-3-031-37660-3_33