Innovative Graded-Index PCF–Based SPR Sensor for Advanced Deepfake Detection and Real-Time Media Integrity Analysis

Deepfake content poses a significant challenge to cybersecurity and media integrity, exploiting advanced AI techniques to generate hyper-realistic yet deceptive visuals. Existing detection methods often lack scalability and precision, particularly in real-time applications. This study presents a novel graded-index photonic crystal fiber (GI-PCF)–based surface plasmon resonance (SPR) sensor, offering an innovative solution for advanced deepfake detection and media authentication. By integrating a graded-index core with nanostructured plasmonic layers, the sensor achieves superior light confinement, optimized refractive index sensitivity, and enhanced detection precision. Experimental results demonstrate key achievements, including a figure of merit (FOM) of 450 RIU⁻¹, sensitivity of 12,500 nm/RIU, and detection accuracy of 98.7%. These advancements highlight the sensor’s capability to detect minute optical anomalies in tampered media, establishing a scalable and robust framework for real-time media verification and deepfake mitigation.