Dual Privacy Protection is an approach to safeguarding data that applies two layers of privacy-preserving techniques, such as differential privacy and secure multiparty computation. NEC Labs America investigates dual privacy protection to enable responsible AI that maintains accuracy while protecting sensitive information. This strategy is especially relevant in biomedical research, financial analytics, and communications, where privacy is essential to compliance, trust, and ethical deployment.

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Dual Privacy Protection for Distributed Fiber Sensing with Disaggregated Inference and Fine-tuning of Memory-Augmented Networks

We propose a memory-augmented model architecture with disaggregated computation infrastructure for fiber sensing event recognition. By leveraging geo-distributed computingresources in optical networks, this approach empowers end-users to customize models while ensuring dual privacy protection.