The Carnegie Mellon College Software program Engineering Institute, AI Engineering: A Nationwide Initiative. https://www.sei.cmu.edu/our-work/initiatives/show.cfm?customel_datapageid_4050=311883. Accessed: 2023-08-29.

A. Alshamrani, S. Myneni, A. Chowdhary, and D. Huang, A survey on superior persistent threats: Strategies, options, challenges, and analysis alternatives, IEEE Communications Surveys & Tutorials, 21 (2019), pp. 1851–1877.

H. Barmer, R. Dzombak, M. Gaston, J. Palat, F. Redner, C. Smith, and T. Smith, Human-Centered AI. https://assets.sei.cmu.edu/asset_files/WhitePaper/2021_019_001_735364.pdf. Accessed: 2023-08-29.

D. Bertsimas and J. Dunn, Optimum classification bushes, Machine Studying, 106 (2017), pp. 1039–1082.

A. L. Buczak and E. Guven, A survey of information mining and machine studying strategies for cyber safety intrusion detection, IEEE Communications Surveys & Tutorials, 18 (2015), pp. 1153–1176.

D. Dasgupta, Z. Akhtar, and S. Sen, Machine studying in cybersecurity: a complete survey, The Journal of Protection Modeling and Simulation, 19 (2022), pp. 57–106.

European Parliament and Council of the European Union, Regulation (EU) 2016/679 of the European Parliament and of the Council.

D. Gibert, C. Mateu, and J. Planes, The rise of machine studying for detection and classification of malware: Analysis developments, traits and challenges, Journal of Community and Pc Functions, 153 (2020), p. 102526.

B. Goodman and S. Flaxman, EU rules on algorithmic decision-making and a “proper to rationalization”, in ICML Workshop on Human Interpretability in Machine Studying (WHI 2016), New York, NY. http://arxiv.org/abs/1606.08813v1, 2016.

Z. Hao, S. Liu, Y. Zhang, C. Ying, Y. Feng, H. Su, and J. Zhu, Physics-informed machine studying: A survey on issues, strategies and functions, arXiv preprint, arXiv:2211.08064, (2022).

Okay. Highnam, Okay. Arulkumaran, Z. Hanif, and N. R. Jennings, BETH dataset: Actual cybersecurity information for anomaly detection analysis, Coaching, 763 (2021), p. 8.

G. E. Karniadakis, I. G. Kevrekidis, L. Lu, P. Perdikaris, S. Wang, and L. Yang, Physics-informed machine studying, Nature Evaluations Physics, 3 (2021), pp. 422–440.

C. Rudin, Cease explaining black field machine studying fashions for top stakes selections and use interpretable fashions as a substitute, Nature Machine Intelligence, 1 (2019), pp. 206–215.

Okay. Shaukat, S. Luo, V. Varadharajan, I. A. Hameed, and M. Xu, A survey on machine studying strategies for cyber safety within the final decade, IEEE Entry, 8 (2020), pp. 222310–222354.

D. Ucci, L. Aniello, and R. Baldoni, Survey of machine studying strategies for malware evaluation, Computer systems & Safety, 81 (2019), pp. 123–147.

Y. Xin, L. Kong, Z. Liu, Y. Chen, Y. Li, H. Zhu, M. Gao, H. Hou, and C. Wang, Machine studying and deep studying strategies for cybersecurity, IEEE Entry, 6 (2018), pp. 35365–35381.