Threat-Oriented Digital Twinning for Security Evaluation of Autonomous Platforms

Computer Science > Cryptography and Security [Submitted on 28 Apr 2026] Threat-Oriented Digital Twinning for Security Evaluation of Autonomous Platforms Thomas J. Neubert, Laxima Niure Kandel, Berker Peköz Open, unclassified research on secure autonomy is constrained by limited access to operational platforms, contested communications infrastructure, and representative adversarial test conditions. This paper presents a threat-oriented digital twinning methodology for cybersecurity evaluation of learning-enabled autonomous platforms. The approach is instantiated as an open-source, modular twin of a representative autonomy stack with separated sensing, autonomy, and supervisory-control functions; confidence-gated multi-modal perception; explicit command and telemetry trust boundaries; and runtime hold-safe behavior. The contribution is methodological: a reproducible design pattern that translates threat analysis into observable, controllable tests for spoofing, replay, malformed-input injection, degraded sensing, and adversarial ML stress. Although the implemented proxy is ground based, the architecture is intentionally framed around stack elements shared with UAV and space systems, including constrained onboard compute, intermittent or high-latency links, probabilistic perception, and mission-critical recovery behavior. The result is an implementable research scaffold for dependable and secure autonomy studies across UAV and space domains. Comments: Camera ready accepted for presentation at and publication in the proceedings of 2026 56st Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W): Dependable and Secure Autonomous Systems (DSAS) Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI); Robotics (cs.RO); Systems and Control (eess.SY) MSC classes: 68M25, 68T40, 93C85, 68M15, 68M14 ACM classes: D.4.6; I.2.9; I.2.8; E.3 Cite as: arXiv:2604.25757 [cs.CR]   (or arXiv:2604.25757v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.25757 Focus to learn more Submission history From: Berker Peköz [view email] [v1] Tue, 28 Apr 2026 15:21:02 UTC (581 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.AI cs.RO cs.SY eess eess.SY References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)