ORAN-DEFEND: Subspace Detection and Sanitization of Backdoor DRL xApps in Open RAN
Open Radio Access Networks (O-RAN) increasingly delegate near-real-time control to deep reinforcement learning (DRL) xApps obtained from third-party vendors, creating a new supply-chain attack surface. A backdoor policy behaves optimally until an adversary injects a covert trigger into the observed key performance indicator (KPI) telemetry, at which point it issues harmful control actions that degrade quality of service (QoS). We present ORAN-DEFEND, a retraining-free wrapper that sanitizes a frozen, potentially compromised xApp by projecting each KPI window onto a safe subspace estimated from a small number of trusted clean rollouts via singular value decomposition (SVD). We establish, b...
| Authors | Md Raihan Uddin, Fatemeh Lotfi, Tolunay Seyfi et al. |
|---|---|
| Primary category | cs.CR |
| Published | 7 July 2026 |
| Last updated at source | 7 July 2026 |
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