pith. sign in

arxiv: 2606.23073 · v1 · pith:CYCYF6JVnew · submitted 2026-06-22 · 📡 eess.SP

Integrating Sensing into Covert Communications: Opportunities and Challenges

Jun Wu , Xiaoqi Zhang , Haoyuan Pan , Gaosheng Zhao , Dong In Kim , Tse-Tin Chan This is my paper

Pith reviewed 2026-06-26 07:15 UTC · model grok-4.3

classification 📡 eess.SP
keywords covert communicationssensingwireless securitybeamformingstate-aware controlexposure riskslow-altitude networksresource consumption
0
0 comments X

The pith

Sensing shifts covert communications from passive concealment to state-aware control using adversary and environmental data.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines how adding sensing to covert wireless systems lets transmissions and jamming adapt based on real-time information about adversaries and the propagation environment. This moves away from relying on blind interference or uncertainty toward informed decisions that can improve performance in changing conditions. The approach also creates fresh risks around the sensing process exposing the system and consuming extra resources. The authors outline intelligent sensing methods that gather only task-relevant details with minimal probing and include a case study on low-altitude networks where sensing-assisted beamforming raises both spatial efficiency and covert delivery reliability.

Core claim

Sensing-empowered covert communications use adversary and environmental information to guide transmission and jamming control, changing system design from passive concealment to state-aware decision-making while creating challenges in exposure and resource use. Several intelligent sensing paradigms are discussed that extract relevant information through limited active probing. A case study demonstrates that sensing-assisted beamforming enhances spatial resource utilization and covert data delivery reliability in time-varying channels.

What carries the argument

Sensing-assisted beamforming that extracts task-relevant adversary and environmental information to enable state-aware transmission and jamming decisions.

If this is right

  • Sensing improves spatial resource utilization and reliability of covert data delivery in time-varying channels.
  • Intelligent sensing paradigms can extract task-relevant information using only limited active probing.
  • Covert system design must now account for exposure and resource consumption introduced by the sensing process.
  • Open issues remain in building more adaptive covert wireless systems that balance sensing benefits against its risks.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same sensing data could potentially be reused across multiple covert links in a shared network to reduce overall probing overhead.
  • In multi-user settings the exposure risks from sensing might compound if one user's probes reveal information usable against others.
  • Testing whether sensing-assisted control maintains covertness under mobility models not covered in the low-altitude case study would clarify general applicability.

Load-bearing premise

Information gathered by sensing about adversaries and the environment can direct transmission and jamming without the sensing activity itself revealing the system or creating excessive exposure risks.

What would settle it

A measurement in which active sensing transmissions are detected by the target adversary at a rate that raises the overall exposure probability above the level achieved by conventional blind covert methods.

Figures

Figures reproduced from arXiv: 2606.23073 by Dong In Kim, Gaosheng Zhao, Haoyuan Pan, Jun Wu, Tse-Tin Chan, Xiaoqi Zhang.

Figure 2
Figure 2. Figure 2: Intelligent sensing paradigms for covert communications. Predictive sensing anticipates adversary mobility to support proactive [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Intelligent sensing for covert communications in urban [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
read the original abstract

Covert communications aim to hide the existence of wireless transmissions from unauthorized adversaries. However, conventional designs based on blind interference or passive uncertainty can be ineffective in dynamic propagation environments. This article investigates sensing-empowered covert communications, where adversary and environmental information are used to guide transmission and jamming control. We show how sensing changes covert system design from passive concealment to state-aware decision-making, while also introducing new challenges related to exposure and resource consumption. We further discuss several intelligent sensing paradigms that extract task-relevant information with limited active probing. A case study in low-altitude wireless networks illustrates that sensing-assisted beamforming can improve spatial resource utilization and the reliability of covert data delivery in time-varying channels. Finally, several open issues are discussed to support more adaptive covert wireless systems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 1 minor

Summary. The manuscript is a perspective article arguing that integrating sensing into covert communications shifts system design from passive concealment (based on blind interference or uncertainty) to state-aware decision-making, where adversary and environmental information guides transmission and jamming control. It identifies resulting challenges in exposure and resource consumption, discusses intelligent sensing paradigms that extract task-relevant information via limited active probing, presents an illustrative case study on sensing-assisted beamforming in low-altitude wireless networks for improved spatial resource use and covert delivery reliability in time-varying channels, and outlines open issues for more adaptive covert systems.

Significance. As a conceptual overview, the work usefully frames how sensing can enable adaptive covert designs while surfacing self-exposure risks, which could help direct research toward practical sensing-assisted covert systems in dynamic environments such as low-altitude networks. The explicit discussion of limited-probing paradigms as a mitigation strategy strengthens the perspective by addressing a key tension in the central claim.

minor comments (1)
  1. The case study is described only at a high level as an illustration; if the full manuscript contains any specific performance metrics or comparisons, a brief quantitative summary in the main text would improve concreteness without altering the perspective nature of the article.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive evaluation of our perspective article and the recommendation to accept. The summary accurately captures the manuscript's focus on shifting covert communications toward state-aware designs via sensing while surfacing exposure and resource challenges.

Circularity Check

0 steps flagged

No significant circularity in conceptual perspective article

full rationale

This manuscript is an overview/perspective piece with no new theorems, equations, derivations, fitted parameters, or quantitative models. Its central claim—that sensing shifts covert design toward state-aware control while surfacing exposure risks—is presented as a conceptual reframing rather than a reduction of any output to its own inputs by construction. No self-citation chains, ansatzes, or uniqueness theorems are invoked as load-bearing premises. The case study is explicitly labeled illustrative only. The derivation chain is therefore self-contained at the level of discussion and does not exhibit any of the enumerated circularity patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only; no free parameters, axioms, or invented entities can be extracted. Full text would be required for any ledger entries.

pith-pipeline@v0.9.1-grok · 5665 in / 1048 out tokens · 32521 ms · 2026-06-26T07:15:28.693270+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

15 extracted references · 2 canonical work pages

  1. [1]

    Covert communications: A comprehensive survey,

    X. Chen, J. An, Z. Xiong, C. Xing, N. Zhao, F. R. Yu, and A. Nallanathan, “Covert communications: A comprehensive survey,” IEEE Commun. Surveys Tuts., vol. 25, no. 2, pp. 1173– 1198, 2023

    2023

  2. [2]

    Intelligent covert communications: Hiding transmission via learning,

    F. Yang, N. Deng, Q. Shi, C. Xing, N. Zhao, and D. Niyato, “Intelligent covert communications: Hiding transmission via learning,” IEEE Commun. Mag., vol. 64, no. 4, pp. 142–148, 2026

    2026

  3. [3]

    Integrating sensing and communications in 6g? not until it is secure to do so,

    N. Su, F. Liu, J. Zou, C. Masouros, G. C. Alexandropoulos, A. Mourad, J. L. Hernando, Q. Zhang, and T.-T. Chan, “Integrating sensing and communications in 6g? not until it is secure to do so,” arXiv preprint arXiv:2503.15243, 2025

    work page arXiv 2025

  4. [4]

    On covert communi- cation with noise uncertainty,

    B. He, S. Yan, X. Zhou, and V. K. Lau, “On covert communi- cation with noise uncertainty,” IEEE Commun. Lett., vol. 21, no. 4, pp. 941–944, 2017

    2017

  5. [5]

    Covert communication in the presence of an uninformed jam- mer,

    T. V. Sobers, B. A. Bash, S. Guha, D. Towsley, and D. Goeckel, “Covert communication in the presence of an uninformed jam- mer,” IEEE Trans. Wireless Commun., vol. 16, no. 9, pp. 6193– 6206, 2017

    2017

  6. [6]

    Aerial-networked ISAC-empowered collaborative energy-efficient covert communications,

    J. Wu et al., “Aerial-networked ISAC-empowered collaborative energy-efficient covert communications,” Chinese J. Aeron., p. 103451, 2025

    2025

  7. [7]

    Sensing-aided covert communications: Turning interference into allies,

    X. Wang, Z. Fei, P. Liu, J. A. Zhang, Q. Wu, and N. Wu, “Sensing-aided covert communications: Turning interference into allies,” IEEE Trans. Wireless Commun., vol. 23, no. 9, pp. 10726–10739, 2024

    2024

  8. [8]

    Collaborative secret and covert communications for multi-user multi-antenna uplink UA V systems: Design and optimization,

    J. Xu, L. Bai, X. Xie, and L. Zhou, “Collaborative secret and covert communications for multi-user multi-antenna uplink UA V systems: Design and optimization,” IEEE Trans. Wireless Commun., vol. 24, no. 7, pp. 6020–6035, 2025

    2025

  9. [9]

    Joint power allocation and rate control for rate splitting multiple access networks with covert communica- tions,

    N. Q. Hieu, D. T. Hoang, D. Niyato, D. N. Nguyen, D. I. Kim, and A. Jamalipour, “Joint power allocation and rate control for rate splitting multiple access networks with covert communica- tions,” IEEE Trans. Commun., vol. 71, no. 4, pp. 2274–2287, 2023

    2023

  10. [10]

    Achieving covert wireless communications using a full-duplex receiver,

    K. Shahzad, X. Zhou, S. Yan, J. Hu, F. Shu, and J. Li, “Achieving covert wireless communications using a full-duplex receiver,” IEEE Trans. Wireless Commun., vol. 17, no. 12, pp. 8517–8530, 2018

    2018

  11. [11]

    Intelligent covert communication: Recent advances and future research trends,

    Z. Li, J. Shi, J. Si, L. Lv, L. Guan, B. Hao, Z. Tie, D. Wang, C. Xing, and T. Q. Quek, “Intelligent covert communication: Recent advances and future research trends,” Engineering, vol. 44, pp. 101–111, 2025

    2025

  12. [12]

    Covert communications with simultaneous multi-modal transmission,

    R. Aggarwal, J. S. Kong, T. J. Moore, J. Choi, P. Spasojevic, and F. T. Dagefu, “Covert communications with simultaneous multi-modal transmission,” in Proceedings of the 17th ACM Conference on Security and Privacy in Wireless and Mobile Networks, pp. 1–7, 2024

    2024

  13. [13]

    Semantic sensing: A task-oriented paradigm,

    X. Zhang, J. A. Zhang, C. Liu, W. Yuan, G. Y. Li, and M. G. Amin, “Semantic sensing: A task-oriented paradigm,” arXiv preprint arXiv:2603.29102, 2026

    work page arXiv 2026

  14. [14]

    Low-altitude wireless networks: A comprehensive survey,

    J. Wu et al., “Low-altitude wireless networks: A comprehensive survey,” China Commun., vol. 23, no. 3, pp. 99–141, 2026

    2026

  15. [15]

    Predictive precoder design for otfs-enabled urllc: A deep learning ap- proach,

    C. Liu, S. Li, W. Yuan, X. Liu, and D. W. K. Ng, “Predictive precoder design for otfs-enabled urllc: A deep learning ap- proach,” IEEE J. Sel. Areas Commun., vol. 41, no. 7, pp. 2245– 2260, 2023

    2023