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This paper claims that a single transmit-beamforming design can simultaneously protect MIMO-OFDM ISAC systems against passive communication and sensing eavesdroppers without knowing their CSI, by injecting artificial noise and embedding art

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2026-08-02 21:26 UTC pith:DIW7NV6L

load-bearing objection Solid two-layer ISAC security optimization with an unjustified threat-model asymmetry that undermines the sensing-security claim. the 4 major comments →

arxiv 2602.20045 v2 pith:DIW7NV6L submitted 2026-02-23 eess.SP cs.ITmath.IT

Dual Security for MIMO-OFDM ISAC Systems: Artificial Ghosts or Artificial Noise

Yinchao Yang , Prabhat Raj Gautam , Yathreb Bouazizi , Michael Breza , Julie McCann This is my paper
classification eess.SP cs.ITmath.IT
keywords ISACMIMO-OFDMphysical layer securitysensing eavesdropperartificial noiseartificial ghostsambiguity functionbeamforming
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper proposes a transmit-beamforming design for MIMO-OFDM ISAC that secures both communication and sensing against passive eavesdroppers whose CSI is unknown. It does this in two layers: artificial noise injected into the beamformer interferes with communication eavesdroppers and degrades the reference signal that sensing eavesdroppers need for matched filtering; and the same beamformer shapes the 3-D ambiguity function to place high-energy artificial ghosts at fake angle-delay-Doppler coordinates. Legitimate receivers can suppress those ghosts because the BS is assumed to know the true target angles, while sensing eavesdroppers cannot, so the ghosts trigger false detections and lower the Eve's probability of identifying real targets. The design is posed as a four-way trade-off optimization that maximizes the legitimate sensing SNR subject to secrecy-rate, Eve-reference-rate, and peak/ISL constraints. Simulations with CFAR detection show the Eve's detection probability drops significantly while the BS's sensing remains usable.

Core claim

On its own terms, the paper's central claim is that one jointly designed transmit beamformer can simultaneously defend an ISAC system against two passive adversaries without knowing their CSI: a communication Eve trying to decode user data and a sensing Eve trying to estimate target angle, delay, and Doppler from reflected echoes. The first defense uses artificial noise to limit the sensing Eve's reference-signal quality (constraint on average data rate at the Eve) while jamming communication Eves. The second defense shapes the waveform's ambiguity function so that artificial peaks appear at chosen angle-delay-Doppler cells; the legitimate BS, knowing the true target AoD, filters them out, b

What carries the argument

The central object is the three-dimensional ambiguity function of the MIMO-OFDM waveform — the matched-filter output over angle, delay, and Doppler. The paper expresses this function as a linear function of the per-subcarrier per-symbol transmit covariance matrices for user beams and artificial noise (block-diagonal matrices W and Q), which turns waveform shaping into a convex problem after surrogate approximations. Peak-sidelobe-level (PSL) and integrated-sidelobe-level (ISL) constraints force the chosen ghost coordinates to have high response; the artificial-noise covariance simultaneously lowers the sensing Eve's reference-signal rate. The legitimate BS's ability to suppress ghosts rests

Load-bearing premise

The whole second security layer rests on the assumption (Assumption 3, Section II) that the legitimate BS knows each target's true angle of departure while sensing eavesdroppers do not; if a sensing Eve can also recover that angle — for example by listening to the initial beam-sweeping stage — it can resolve the true target among the artificial ghosts.

What would settle it

Run the proposed design against a sensing Eve that performs joint 3-D maximum-likelihood estimation of angle, delay, and Doppler (using the same beam-sweeping stage and large antenna array the paper grants it) and measure correct target detection probability; if it remains close to the no-security baseline, the second layer is falsified.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • Sensing eavesdropping can be mitigated in ISAC even when the transmitter has no CSI of the eavesdropper, closing a gap left by prior AN-only designs.
  • Artificial ghosts in the full angle-delay-Doppler domain make it much harder for an Eve to tell true targets from fakes, unlike range-domain-only fake targets.
  • The two defense layers are complementary: AN handles Eves with poor reference signals, while AGs still degrade even a perfect-reference Eve.
  • Enforcing communication secrecy automatically tightens sensing security, since both benefit from stronger artificial noise.
  • There is a quantifiable four-way trade-off: raising secrecy requirements or ghost strength lowers the legitimate BS's sensing SNR and, beyond a point, its detection probability.

Where Pith is reading between the lines

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

  • If a sensing Eve is allowed to estimate AoD jointly rather than treat each angle hypothesis separately, the premise of Assumption 3 disappears; the same beam-sweeping stage that realizes the assumption would reveal the true AoD to the Eve, collapsing the second layer. This is not tested in the paper.
  • The AG mechanism is waveform-agnostic in spirit; a similar ambiguity-function shaping could be applied to OTFS or other delay-Doppler waveforms, provided the reference-signal degradation and AoD-secrecy assumptions carry over.
  • A natural testable extension is an adaptive adversary that runs a joint multi-dimensional estimator over angle-delay-Doppler and compares detection probability against the paper's per-dimension MF assumption; if detection probability does not drop materially, the AG layer's effectiveness would need revisiting.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

4 major / 6 minor

Summary. This paper proposes a two-layer physical-layer security design for MIMO-OFDM ISAC systems. The first layer injects artificial noise (AN) to degrade the reception of communication eavesdroppers and to limit the quality of the reference signal available to sensing eavesdroppers. The second layer shapes the three-dimensional ambiguity function to place artificial ghost (AG) peaks at selected angle–delay–Doppler coordinates, so that sensing eavesdroppers are misled, while the legitimate BS can suppress these ghosts because it knows the true target angle of departure. The transmit beamformers and AN covariance are jointly optimized to maximize the BS post-matched-filter sensing SNR subject to constraints on Eve reference-signal rate, AG peak and sidelobe levels, worst-case secrecy rate, and power, using SDR, DC surrogates, and Gaussian randomization. Simulations demonstrate trade-offs among sensing SNR, secrecy rate, and detection probabilities for the BS and sensing Eves.

Significance. If the security claims are substantiated, the paper would make a useful contribution to ISAC physical-layer security by unifying AN-based and ambiguity-function-based defenses in a single optimization framework. The problem formulation is systematic, and the SDR/DC solution pipeline is standard and reproducible. The paper explicitly models worst-case Eve capabilities (perfect reference recovery, large arrays) and provides extensive numerical results. However, the central security claim rests on an unexamined asymmetry in knowledge of the target AoD (Assumption 3), and the 'no CSI' claim is stronger than the formulation actually implements. These issues need to be resolved before the contribution can be accepted as a robust security mechanism.

major comments (4)
  1. [Section II, Assumption 3; Section V.D, Fig. 9] The AG security layer relies entirely on the assumption that the BS knows the true target AoD while the sensing Eve does not. But the ambiguity function in (22) is a function only of the transmitted signals W and Q and is observable by all receivers. The BS's mainlobe at (0,0,θ_l,t,θ_l,t) is present in the Eve's matched-filter output as well. Given the capabilities granted to the Eve in Assumptions 1 and 4 (N_mr >> N_t, perfect reference recovery, perfect AoA estimation), it is not argued why the Eve cannot estimate θ_l.t, e.g., from the beam-sweeping stage that 'realizes' Assumption 3 or from joint multi-dimensional estimation across its array. If the Eve can estimate the true AoD, it can apply the same angular filtering as the BS, and the detection-probability reductions in Figs. 6–9 overstate the security provided by the AG layer. Please provide an explicit adversary model for AoD est
  2. [Section II.E, Assumption 2; (29c), (29f)] The abstract claims the design does not require Eve CSI, but constraints (29c) and (29f) involve sums over sets M_r and M_c and use explicit Eve angles θ_mr and θ_mc in the channel models (25) and (27). Under Assumption 2 (the BS has no knowledge of Eve positions or existence), these sets and angles are unavailable. To substantiate the Eve-agnostic claim, the constraints should be robust over a continuum of angles (e.g., worst-case over [-π/2, π/2]) or the claim should be softened. The simulations place Eves at fixed locations (e.g., (3,1) and (2,-8)), so they do not demonstrate operation without Eve knowledge.
  3. [Section V, AG coordinates; (29d)–(29e)] The AG coordinates are fixed inputs ((0,5,62°), (0,2,35°), (3,4,40°)), and constraints (29d)–(29e) force the AF to have peaks at those coordinates. Consequently, the appearance of ghosts in Fig. 7(b) and part of the detection-probability reduction in Fig. 6 are direct consequences of the design constraints rather than independent evidence that the AGs confuse the Eve. Please include a baseline that allocates the same power to sidelobe shaping at arbitrary (non-AG) locations, or report the probability that the Eve's strongest peak is at the true target (not merely the presence of extra false alarms). In addition, report statistical variability over multiple noise realizations for the detection-probability curves, since only single curves are shown.
  4. [Section IV.B, (34)] The convexity claim for problem (34) is not fully transparent. Constraint (34b) is written as γ ≥ η_B, but γ in (20) is defined in terms of the original beamforming matrix W_{nc,ns}, not the lifted rank-one variables W_{nc,ns,k}. After SDR, γ should be explicitly expressed as (β²|a_r^H(θ_l,B)|²/σ_r²) Tr(a_t(θ_l,t)a_t^H(θ_l,t) Σ_k W_{nc,ns,k}), which is linear. Similarly, the matrices ar{W}^{(e)}_{nc,ns}, W^{(e)}, ar{Q}^{(e)} used in (30)–(33) are not defined in the main text; they are introduced in the notation block of (22). Please state these definitions and show that each constraint in (34) is convex in the final variables.
minor comments (6)
  1. [Equation (23)] PSL_l is actually the AF value at a specific ghost coordinate g, not the peak sidelobe level. This naming is confusing; suggest renaming it 'ghost peak level' or clarifying the indexing in (29d).
  2. [Equations (29d)–(29e)] The subscripts g are missing; as written, PSL_l and ISL_l appear to be scalars per target, but (23) defines PSL_l for each ghost g. Please add the g index consistently.
  3. [Equation (25)] The quantity C_mr is called 'average data rate' but is actually the mutual information of a hypothetical LoS channel with AN treated as noise. Since the link to reference-signal estimation accuracy is not derived, please state explicitly that this is a design surrogate.
  4. [Section V.D, Fig. 7 caption] The caption says the sensing Eve is at (3,1) in (b) and (e) but at (30,10) in (c) and (f); earlier in Section V the default Eve location is (3,1). Please clarify which locations are used in each subfigure.
  5. [Section IV.A, (29f)] The worst-case secrecy rate S_k = min_{m_c} [C_k - C_{k,m_c}]^+ requires knowledge of the set M_c. Under Assumption 2 this set is unknown; see major comment 2. A robust formulation over all angles would avoid this inconsistency.
  6. [Algorithm 1] The convergence criterion checks ar{W} and Q but not the surrogate linearization points; please cite or state a standard DC convergence result to justify termination.

Circularity Check

0 steps flagged

No significant circularity: AGs are design constraints and the simulations are downstream consequences, not independent predictions; the AoD asymmetry is a threat-model assumption rather than a derived result.

full rationale

The paper's derivation chain is a transmit-beamforming optimization: the variables are W and Q, the objective (29a) maximizes BS post-MF sensing SNR, and the security mechanisms appear as explicit constraints (29c)-(29f). The artificial-ghost coordinates are fixed inputs, and constraints (29d)-(29e) directly require AF peaks at those coordinates, so the appearance of ghosts in Fig. 7(b) and the resulting CFAR detection-probability reductions in Fig. 6 are consequences of the design constraints, not independent predictions from first principles. The paper does not claim to discover the ghost locations; it states that 'The AG profiles in (22) and (23) are configured at (0,5,62°), (0,2,35°), and (3,4,40°),' so the simulation is a feasibility/performance check rather than a circular confirmation. The load-bearing assumption that the sensing Eve cannot know the true AoD (Assumption 3) is an unproven threat-model assumption, not a result derived from the model; its weakness is a correctness/security-model concern, not a circularity. The only self-citation, [46], is used alongside the independent [45] for the standard semidefinite relaxation of the rank-one constraint and is not load-bearing. The central optimization is self-contained and its simulation outcomes are not equivalent by construction to the claimed security results.

Axiom & Free-Parameter Ledger

4 free parameters · 6 axioms · 1 invented entities

Everything the security claims rest on beyond the free thresholds: the epistemic asymmetry of Assumption 3, the worst-case Eve capability package (Assumptions 1, 4), the on-grid target idealization, and standard SDR+DC machinery. None of these are calibrated to data; the design is validated only against simulated channels with the chosen geometry. AGs are engineered signal features rather than postulated physics, so the entity ledger is light.

free parameters (4)
  • AG coordinate set G = (0,5,62°), (0,2,35°), (3,4,40°) in Sec. V
    Ghost locations in delay-Doppler-angle space are hand-chosen inputs to constraints (29d)-(29e); the security results in Figs. 6-9 are reported for these specific placements with no sensitivity analysis.
  • Ghost strength thresholds η_PSL, η_ISL = swept from -25 to -10 dB (PSL), -4 to 2 dB (ISL)
    Hand-chosen constraint levels determining how much AF energy is diverted to ghosts; the central trade-off plots are parametric in these values.
  • Security operating points η_E, η_s = η_E ∈ {2,5} bps/Hz, η_s ∈ {1.5,2.5} bps/Hz in Fig. 6
    Constraint levels for the Eve reference-signal rate and the user secrecy rate; all detection-probability results depend on the chosen operating points.
  • Scenario geometry and on-grid target placement = BS (0,0), Eve (3,1)/(30,10), target (12,11) at 46 m/s, target 2 (85,42) at 120 m/s
    Positions, velocities, and the assumption that targets lie exactly on the delay-Doppler grid determine the achievable AF contrast and detection results; off-grid or different geometries are not tested.
axioms (6)
  • domain assumption Assumption 3: BS knows the true target AoDs; sensing Eves do not
    Justifies why the BS can spatially filter ghosts while the Eve cannot; introduced in Section II and used in Sec. V.D to explain the BS's detection robustness. This is the weakest load-bearing premise of the second security layer.
  • domain assumption Assumptions 1 and 4: sensing Eve has N_mr >> N_t array, knows the BS location, can perfectly separate the reference signal, and can accurately estimate echo AoA
    Defines the worst-case adversary whose capabilities motivate both defense layers (AN for the reference, AG for the echo).
  • domain assumption Targets lie exactly on the delay-Doppler grid (τ = ℓ/(N_c Δf), μ = ν/(N_s T_tot))
    Used in Sec. II.D to write (13) and the AF decomposition (22); off-grid targets would leak across bins and could mask or fake ghosts. No off-grid robustness analysis is given.
  • domain assumption Perfect CSI for legitimate users at the BS; geometry-based channels with free-space path loss
    Section II.E and Table II; the communication-side constraints (26)-(27) presume channel knowledge that the Eve side is denied — an asymmetry the paper does not discuss.
  • standard math DC first-order Taylor surrogates plus SDR relaxation yield a converged, rank-recoverable solution
    Sec. IV.B and Algorithm 1; a standard heuristic in this literature, but no convergence proof or Gaussian-randomization tightness analysis is provided.
  • domain assumption ICI negligible (μ/Δf ≪ 1); AoA estimated separately via MUSIC and spatially filtered pre-processing
    Sec. II.B and Remark 1; needed to factor the received signal into separate angle, delay, and Doppler processing and to justify the separable 3-D AF.
invented entities (1)
  • Artificial ghosts (AGs) independent evidence
    purpose: Engineered ambiguity-function sidelobes that present fake angle-delay-Doppler target profiles to sensing Eves while legitimate receivers suppress them via known target angles.
    AGs are deterministic features of the optimized transmit signal (W, Q): any implementation reproduces them and they are directly measurable from the transmitted waveform's ambiguity function. They are engineered signal features, not unexplained physical postulates; the asymmetry claim (BS suppresses, Eve cannot) is exactly what rests on Assumption 3.

pith-pipeline@v1.3.0-alltime-deepseek · 20154 in / 26198 out tokens · 238186 ms · 2026-08-02T21:26:35.083452+00:00 · methodology

0 comments
read the original abstract

Integrated sensing and communication (ISAC) enables the efficient sharing of wireless resources to support emerging applications, but it also gives rise to new sensing-based security vulnerabilities. Here, potential communication security threats whereby confidential messages intended for legitimate users are intercepted, but also unauthorized receivers (Eves) can passively exploit target echoes to infer sensing parameters without users being aware. Despite these risks, the joint protection of sensing and communication security in ISAC systems remains unexplored. To address this challenge, this paper proposes a two-layer dual-secure ISAC framework that simultaneously protects sensing and communication against passive sensing Eves and communication Eves, without requiring their channel state information (CSI). Specifically, transmit beamformers are jointly designed to inject artificial noise (AN) to introduce interference to communication Eves, while deliberately distorting the reference signal available to sensing Eves to impair their sensing capability. Furthermore, the proposed design generates artificial ghosts (AGs) with fake angle-range-velocity profiles observable by all receivers. Legitimate receivers can suppress these AGs, whereas sensing Eves cannot, thereby significantly reducing their probability of correctly detecting the true targets. Numerical results demonstrate that the proposed framework effectively enhances both communication and sensing security, while preserving the performance of communication users and legitimate sensing receivers.

Figures

Figures reproduced from arXiv: 2602.20045 by Julie McCann, Michael Breza, Prabhat Raj Gautam, Yathreb Bouazizi, Yinchao Yang.

Figure 1
Figure 1. Figure 1: A monostatic ISAC system with a target l ∈ L, a communication user k ∈ K, a bistatic sensing eavesdropper mr ∈ Mr, and a communication eavesdropper mc ∈ Mc. continuously transmits signals, allowing any receiver to infer the BS location. Assumption 3 can be realized through an initial beam sweeping or omnidirectional transmission stage, enabling the BS to determine whether targets or objects exist within it… view at source ↗
Figure 2
Figure 2. Figure 2: Illustration of the sensing security vulnerability in an ISAC system. [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: The sensing SNR for BS (γnc,ns,l,B) versus the secrecy rate for users (ηS). The values of ηPSL is set to -25 dB and ηE = 3 bps/Hz. Sensing secure [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The sensing SNR for BS (γnc,ns,l,B) versus the secrecy rate for users (ηS). The values of ηISL is set to -4 dB and ηE = 5 bps/Hz. ηS leads to a reduction in the sensing SNR at the BS. This indicates that achieving higher communication security comes at the cost of degraded sensing performance. The underlying reason is that stricter communication secrecy requirements demand more transmit power to be allocat… view at source ↗
Figure 5
Figure 5. Figure 5: The sensing Eve reference signal transmission rate ( [PITH_FULL_IMAGE:figures/full_fig_p010_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Detection probability versus ηPSL under different design parameters. Two types of sensing Eve reference signals are considered: an MVU-based reference signal and an idealized reference signal assuming perfect cancellation of the channel matrix. methods. Meanwhile, a marginal reduction in the BS detection probability is also observed, indicating that improving sensing security via AN incurs a trade-off with… view at source ↗
Figure 7
Figure 7. Figure 7: Delay-Doppler maps observed at the BS and sensing Eve [PITH_FULL_IMAGE:figures/full_fig_p012_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Delay–Doppler map of target 1 observed by sensing Eve [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Delay-angle maps observed at the BS and sensing Eve [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗

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Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Dual-Security for Indoor OFDM-ISAC Systems via Temporal Artificial Noise

    eess.SP 2026-07 conditional novelty 5.0

    Temporal artificial noise in the OFDM guard interval degrades an authorized sensing user's data decoding and an authorized communication user's target sensing, without harming either user's legitimate task.

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