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When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking — arXiv:2608.03902

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.03902
License (as archived): CC0-1.0
Archived: 2026-10-31T12:16:43.857Z
SHA-256 of the archived text: f3b29d0993641fbefc0f58599ad714d996d1222a497b7f6b78fa64d008913e99
Stable URL of this page: https://metraipolis.com/documento/dc_ce3fd2249072

How to cite

When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking — arXiv:2608.03902 — arXiv (en), https://arxiv.org/abs/2608.03902 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_ce3fd2249072 (Metraipolis archive dc_ce3fd2249072, sha256 f3b29d0993641fbefc0f58599ad714d996d1222a497b7f6b78fa64d008913e99)

BibTeX

@misc{dcce3fd2249072,
  title = {When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking — arXiv:2608.03902},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.03902},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_ce3fd2249072; sha256 f3b29d0993641fbefc0f58599ad714d996d1222a497b7f6b78fa64d008913e99},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.03902. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Resource constraints on UAV platforms have driven a paradigm shift in aerial tracking, from pursuing performance toward balancing accuracy with efficiency. Adaptive Transformer Trackers, which leverage an input-dependent dynamic routing architecture, have emerged as a representative solution to this challenge. However, we reveal that behind this computation-on-demand flexibility hides a critical structural flaw: the Lipschitz singularity of computational path decisions, which has an unbounded local Lipschitz constant at discrete layer-skipping decision boundaries. This mathematical discontinuity renders adaptive tracking networks inherently unstable: tiny input perturbations can be amplified at the gating modules, causing dramatic changes in the inference topology. We formally characterize this singularity in the context of adaptive tracking architectures and, for the first time, identify it as a directly exploitable new attack surface. This insight reveals a previously overlooked and highly vulnerable topological path space attack surface. Based on this, we propose the Adversarial Path-Inversion (API) framework. API generates imperceptible perturbations to precisely manipulate the gating decisions, forcing the inference onto altered computational paths. The severe inconsistency between the original and the inverted paths dismantles the representation capability of the model. Extensive experiments on state-of-the-art adaptive trackers demonstrate that API achieves superior perturbation stealthiness, more effective attack, and faster inference speeds. This work opens a new dimension for the security analysis of dynamic tracking networks and provides a theoretical warning for constructing robust adaptive tracking architectures in the future.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-05 in cs.AI).
Categorie arXiv: Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2608.03902 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-31T12:05:52.863Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-08-05?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).