Ecological Objectives Need Cybersecurity Assumptions

How should planners expose security dependencies inside ecological benefit claims? This review answers by treating cross-domain assurance as a property of a sociotechnical workflow rather than a feature that can be read from average accuracy. The focal setting is automated green-space operations, where an optimized service can create privacy, security, and distributional harms that are invisible in its technical objective. Evidence from the assigned publications is synthesized with foundational studies of calibration, distribution shift, causal structure, and responsible deployment. Four requirements follow: preserve the lineage of environmental sensing, mobility and service records, infrastructure graphs, threat reports, and planning constraints; measure stability across relevant perturbations; connect confidence to a specific action; and maintain a route for human challenge and correction. The framework distinguishes descriptive performance from decision utility and separates uncertainty about the world from uncertainty created by the model and its evaluator. It also shows why faster inference or richer reasoning is valuable only when it improves a defined decision under a transparent resource budget. The article is a literature review and research agenda, not a report of a newly completed trial.

1. Wang, Zijun, et al. "Trident: Dual-Stream APT Attribution over Heterogeneous Threat Knowledge Graphs." *Computers & Security* 171 (2026): 105094.
2. Li, Yuanhao, et al. "BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models." *arXiv preprint arXiv:2605.09134* (2026).
3. Liu, Kun, and Yong Ying. "Green Infrastructure Integration in Smart City Planning and Development." *Proceedings of the 2025 5th International Conference on Smart Transportation and City Engineering (STCE 2025)* (2026).
4. Batty, Michael, et al. "Smart Cities of the Future." *European Physical Journal Special Topics*, vol. 214, 2012, pp. 481-518.
5. Kitchin, Rob. "The Real-Time City? Big Data and Smart Urbanism." *GeoJournal*, vol. 79, 2014, pp. 1-14.
6. Bibri, Simon Elias, and John Krogstie. "Smart Sustainable Cities of the Future: An Extensive Interdisciplinary Literature Review." *Sustainable Cities and Society*, vol. 31, 2017, pp. 183-212.
7. Tzoulas, Konstantinos, et al. "Promoting Ecosystem and Human Health in Urban Areas Using Green Infrastructure: A Literature Review." *Landscape and Urban Planning*, vol. 81, no. 3, 2007, pp. 167-178.
8. Benedict, Mark A., and Edward T. McMahon. *Green Infrastructure: Linking Landscapes and Communities*. Island Press, 2006.
9. Dwork, Cynthia. "Differential Privacy." *Automata, Languages and Programming*, Springer, 2006, pp. 1-12.
10. McMahan, Brendan, et al. "Communication-Efficient Learning of Deep Networks from Decentralized Data." *Proceedings of the 20th International Conference on Artificial Intelligence and Statistics*, 2017, pp. 1273-1282.
11. Shokri, Reza, and Vitaly Shmatikov. "Privacy-Preserving Deep Learning." *Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security*, 2015, pp. 1310-1321.
12. Kairouz, Peter, et al. "Advances and Open Problems in Federated Learning." *Foundations and Trends in Machine Learning*, vol. 14, nos. 1-2, 2021, pp. 1-210.
13. Selbst, Andrew D., et al. "Fairness and Abstraction in Sociotechnical Systems." *Proceedings of the Conference on Fairness, Accountability, and Transparency*, 2019, pp. 59-68.