Bridging Digital Deception and Physical Fidelity: A Spatio-Temporal Attack on Cognitive Radars
Academic work demonstrates spatio-temporal adversarial techniques against deep-learning-based cognitive radar, underscoring that ML vulnerabilities now extend to RF sensing in electronic-warfare contexts.
Summary written by editorial AI · Source link below
arXiv:2610.27585v1 Announce Type: cross Abstract: As cognitive radars evolve towards the end-to-end processing of one-dimensional complex baseband sequences, deep networks face severe adversarial threats. However, existing attacks encounter dual limitations in practical electronic warfare: low cross-architecture transferability and severe vulnerability to physical channel distortions, which degrades their tactical reliability. To overcome these bottlenecks, we propose a physical prior-driven Se
Editorial Analysis
As military and critical-infrastructure radar migrates to end-to-end deep learning, adversarial attacks on these systems could disrupt situational awareness in ways traditional jamming cannot.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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