arxiv: 2605.00258 · v1 · submitted 2026-04-30 · 💻 cs.IT · cs.SY· eess.SY· math.IT

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Joint Accuracy and Confidentiality in Semantic-Aware Secure Remote Reconstruction

Bowen Li , Nikolaos Pappas

Authors on Pith no claims yet

Pith reviewed 2026-05-09 19:22 UTC · model grok-4.3

classification 💻 cs.IT cs.SYeess.SYmath.IT

keywords confidential reconstruction accuracysecure remote reconstructionwireless networkseavesdroppingstationary analysisjoint optimizationsemantic-aware securitygeofencing

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The pith

A joint metric for accurate receiver reconstruction and eavesdropper failure shows separate analysis selects the wrong transmission policies.

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

The paper defines confidential reconstruction accuracy as the probability that a legitimate receiver reconstructs an update correctly while an eavesdropper fails on the same update. It models the joint process with a three-dimensional stationary analysis under randomized stationary policies to obtain closed-form expressions for long-term average performance and the optimal transmission probability. The work demonstrates that treating accuracy and confidentiality as separate marginal problems can select an incorrect transmission rate and misestimate what joint performance is achievable. It also identifies cases where transmitting more frequently or strengthening the legitimate channel reduces rather than improves the joint outcome, especially when the eavesdropper channel is strong.

Core claim

Under randomized stationary policies, a three-dimensional stationary analysis yields closed-form expressions for the long-term average confidential reconstruction accuracy and the optimal transmission probability. Conventional marginal analysis misidentifies the optimal policy and misestimates the achievable simultaneous accuracy-confidentiality performance. Nontrivial behaviors appear: more frequent transmissions or better legitimate channels do not necessarily improve joint performance, and when the eavesdropping channel is strong, improving the legitimate channel alone may be insufficient. The framework also induces a spatial safety boundary for geofencing.

What carries the argument

Confidential reconstruction accuracy (CRA), the probability of the joint event in which the legitimate receiver reconstructs correctly and the eavesdropper fails, which replaces separate marginal objectives in the policy optimization.

If this is right

Closed-form expressions give the transmission probability that maximizes long-term CRA.
Joint CRA can decrease when transmission frequency increases under certain channel conditions.
Strengthening only the legitimate channel can fail to raise CRA when the eavesdropper channel remains strong.
The same analysis produces a spatial safety boundary that defines safe operating regions for geofencing.

Where Pith is reading between the lines

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

System designers may need to track the joint distribution of receiver and eavesdropper outcomes rather than tuning each margin in isolation.
The stationary-policy restriction suggests checking whether time-varying policies or non-stationary channels produce qualitatively different trade-offs.
The CRA formulation could be adapted to other semantic communication settings where multiple performance objectives share the same source symbols.

Load-bearing premise

The closed-form expressions assume the joint reconstruction events admit a three-dimensional stationary model under randomized stationary transmission policies.

What would settle it

A numerical evaluation or wireless testbed measurement in which the transmission probability that maximizes CRA differs from the probabilities that separately maximize accuracy and minimize eavesdropper success.

Figures

Figures reproduced from arXiv: 2605.00258 by Bowen Li, Nikolaos Pappas.

**Figure 2.** Figure 2: Average simultaneous confidentiality and accuracy [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗

**Figure 3.** Figure 3: Probabilities of simultaneous confidentiality and accuracy [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗

**Figure 4.** Figure 4: (a) Probability of simultaneous confidentiality and accuracy [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗

**Figure 5.** Figure 5: Simulation layout and spatial maps under arbitrary eavesdropper locations. (a) shows the simulation layout; (b) shows Eve’s channel success-probability [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗

read the original abstract

In this paper, we consider remote reconstruction over wireless networks when simultaneous accuracy at the legitimate receiver and confidentiality against eavesdropping are required. These two objectives are often treated separately, even though they arise from the same update process and are marginals of a joint reconstruction event. This paper introduces confidential reconstruction accuracy (CRA), a metric to capture the joint event in which the legitimate receiver reconstructs correctly while the eavesdropper fails. Under randomized stationary policies, we develop a three-dimensional stationary analysis and derive closed-form expressions for the long-term average CRA and the optimal transmission probability. The results show that conventional marginal analysis can misidentify the optimal policy and misestimate the achievable simultaneous accuracy-confidentiality performance. They also reveal nontrivial behaviors: more frequent transmissions or better legitimate channels do not necessarily improve joint accurate and confidential reconstruction, and when the eavesdropping channel is strong, improving the legitimate channel alone may be insufficient. Finally, the framework induces the spatial safety boundary in a geofencing setting for secure remote reconstruction.

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.

Desk Editor's Note private letter to a colleague

The paper's new joint CRA metric and finding that marginal analysis can pick wrong policies are worth checking, but the closed-forms rest on an unverified 3D stationary Markov model.

read the letter

The key point is that this paper defines confidential reconstruction accuracy as a joint metric for correct reconstruction at the legitimate receiver and failure at the eavesdropper, then shows through analysis that optimizing the two goals separately can pick the wrong transmission probability. They model the updates with randomized stationary policies and use a three-dimensional stationary Markov chain to derive closed-form expressions for the long-term CRA and the optimizing probability. This reveals that marginal analysis not only misidentifies the best policy but also underestimates the joint performance. Additional findings include that increasing transmission frequency or improving the legitimate channel does not always boost the joint accuracy-confidentiality outcome, and that a strong eavesdropping channel can make legitimate improvements insufficient on their own. They extend the framework to a geofencing scenario to set spatial safety boundaries. The contribution is clear in moving beyond separate treatments of accuracy and secrecy, which the abstract notes are marginals of the same joint event. The closed-forms provide analytical insight, and the nontrivial behaviors challenge some intuitive assumptions in wireless security design. The soft spot lies in the three-dimensional stationary analysis itself. The central claims about policy misidentification and performance misestimation depend on the accuracy of those closed-form expressions from the global balance equations. Any issue with the state definitions—covering legitimate success, eavesdropper failure, and the third dimension—or the transition probabilities would undermine the results. The stationarity assumption under randomized policies may also restrict applicability to more dynamic settings. Without seeing the full derivations or simulation validations, the soundness of the math remains uncertain. This paper targets researchers in information-theoretic security and semantic communications for remote systems. A reader focused on joint optimization in conflicting wireless objectives would gain from the new metric and the policy insights. It merits peer review to have the analysis scrutinized and the claims tested. I recommend sending it for review rather than desk rejecting it.

Referee Report

2 major / 2 minor

Summary. The manuscript introduces confidential reconstruction accuracy (CRA) as a joint metric capturing correct reconstruction at the legitimate receiver and failure at the eavesdropper. Under randomized stationary policies, it performs a three-dimensional stationary Markov analysis to derive closed-form expressions for the long-term average CRA and the optimizing transmission probability. The central results are that marginal analysis misidentifies the optimal policy and misestimates joint performance, with additional findings on nontrivial behaviors (e.g., higher transmission rates or better legitimate channels not always improving CRA) and an induced spatial safety boundary for geofencing applications.

Significance. If the closed-form derivations are correct, the work is significant because it demonstrates that joint analysis is required for accuracy-confidentiality tradeoffs in semantic-aware secure reconstruction, rather than treating the objectives marginally. The provision of closed-form CRA expressions and the optimal policy under the 3D stationary model is a strength, enabling exact optimization and revealing counterintuitive results that challenge standard intuitions about transmission frequency and channel quality. The geofencing application further extends the framework to practical spatial settings.

major comments (2)

[Three-dimensional stationary analysis and derivation of closed-form CRA] The claim that marginal analysis misidentifies the optimal transmission probability and misestimates joint CRA performance rests entirely on the closed-form long-term average CRA derived from the three-dimensional stationary distribution. The abstract states that a 3D analysis is used, but the manuscript must explicitly define the state space (legitimate reconstruction success, eavesdropper failure, and the third dimension), the transition probabilities, and the solution of the global balance equations; any inconsistency here would invalidate both the CRA formula and the policy comparison.
[Results on nontrivial behaviors and optimal policy] The nontrivial behaviors (more frequent transmissions or better legitimate channels not necessarily improving joint performance, and insufficiency of improving the legitimate channel alone when the eavesdropping channel is strong) are derived from the same stationary CRA expression. These results require verification that the stationary probabilities correctly capture the joint event under randomized policies, as the assumption of stationarity may not extend to all channel conditions or non-stationary scenarios.

minor comments (2)

[System model] Clarify the exact definition of the third dimension in the state space and how it interacts with the joint reconstruction event.
[Numerical results] Provide numerical validation or plots comparing the closed-form CRA against simulated long-term averages to confirm the expressions.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments, which have helped us improve the clarity of the three-dimensional analysis. We have revised the manuscript to explicitly detail the state space, transitions, and balance equations while preserving all original results and derivations.

read point-by-point responses

Referee: [Three-dimensional stationary analysis and derivation of closed-form CRA] The claim that marginal analysis misidentifies the optimal transmission probability and misestimates joint CRA performance rests entirely on the closed-form long-term average CRA derived from the three-dimensional stationary distribution. The abstract states that a 3D analysis is used, but the manuscript must explicitly define the state space (legitimate reconstruction success, eavesdropper failure, and the third dimension), the transition probabilities, and the solution of the global balance equations; any inconsistency here would invalidate both the CRA formula and the policy comparison.

Authors: We agree that explicit definitions are required for full verification. In the revised manuscript, Section III-B now contains a dedicated subsection that defines the three-dimensional state space as (X_t, Y_t, Z_t), where X_t indicates legitimate reconstruction success, Y_t indicates eavesdropper reconstruction failure, and Z_t tracks the transmission action under the randomized stationary policy. Transition probabilities are stated explicitly in terms of the legitimate channel success probability q_L, eavesdropper success probability q_E, and transmission probability p. The global balance equations are solved in closed form to yield the stationary distribution π, from which the long-term CRA is obtained as the sum of π over states satisfying X=1 and Y=1. The complete algebraic solution appears in the new Appendix B. These additions confirm the CRA expression and the subsequent policy comparisons without altering any numerical results. revision: yes
Referee: [Results on nontrivial behaviors and optimal policy] The nontrivial behaviors (more frequent transmissions or better legitimate channels not necessarily improving joint performance, and insufficiency of improving the legitimate channel alone when the eavesdropping channel is strong) are derived from the same stationary CRA expression. These results require verification that the stationary probabilities correctly capture the joint event under randomized policies, as the assumption of stationarity may not extend to all channel conditions or non-stationary scenarios.

Authors: The joint stationary distribution is constructed precisely so that the probability mass on states with simultaneous legitimate success and eavesdropper failure equals the long-term CRA; marginals recovered from this distribution recover the individual success rates, providing an internal consistency check that we have now made explicit in the revised text. The nontrivial behaviors follow directly from differentiating the closed-form CRA with respect to p and the channel parameters. We acknowledge that the analysis assumes stationary channels and policies, as stated in the problem setup; the long-term average under non-stationary conditions would require different tools. A new remark in Section V notes this scope limitation while emphasizing that the closed-form results remain valid within the stationary regime considered. revision: partial

Circularity Check

0 steps flagged

No circularity: CRA closed-forms derived from standard 3D Markov balance equations

full rationale

The paper defines CRA as the joint probability of correct legitimate reconstruction and eavesdropper failure, then applies a three-dimensional stationary Markov chain under randomized stationary policies to obtain closed-form long-term averages and the optimizing transmission probability directly from the global balance equations. This is a self-contained derivation from the modeled state transitions and does not reduce any prediction or optimality claim to a fitted input, self-citation chain, or redefinition of the metric itself. The comparison showing marginal analysis is suboptimal follows as a direct algebraic consequence of the joint expressions versus the separate marginal ones, with no load-bearing step that collapses to its own inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 1 invented entities

Based on the abstract, the central claim rests on standard assumptions in wireless communication theory and the new definition of CRA. No explicit free parameters are identified.

axioms (2)

domain assumption Randomized stationary policies govern the transmission decisions.
The analysis is developed under these policies as stated in the abstract.
domain assumption The reconstruction process can be modeled as a three-dimensional stationary process.
Used to derive closed-form expressions for long-term average CRA.

invented entities (1)

Confidential reconstruction accuracy (CRA) no independent evidence
purpose: To capture the joint event of correct reconstruction at the legitimate receiver and failure at the eavesdropper.
New metric defined in the paper; no independent evidence provided beyond the definition.

pith-pipeline@v0.9.0 · 5475 in / 1310 out tokens · 42952 ms · 2026-05-09T19:22:39.864635+00:00 · methodology

discussion (0)

Reference graph

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