Our research contributions, publications, and technical achievements in quantum-resilient cybersecurity
Developed a privacy-preserving federated learning system using TensorFlow Federated (TFF) with FedAvg aggregation for distributed anomaly detection across multiple organizations.
Learn More →Implemented Kyber KEM (Key Encapsulation Mechanism) for post-quantum encryption, ensuring secure communication channels resistant to quantum computing attacks.
Learn More →Built an immutable blockchain ledger for tamper-proof event logging, cryptographic signatures, and integrity verification of security events and model updates.
Learn More →Created an autoencoder-based anomaly detection system that provides real-time threat scoring and alerting with high accuracy and low false positive rates.
Learn More →Ongoing research in quantum-resistant security, federated learning optimization, and blockchain-based verification systems for next-generation cybersecurity.
View Research →Pioneering the integration of three critical security layers: federated learning for privacy, post-quantum encryption for future-proofing, and blockchain for transparency.
View System →Core development language for machine learning, cryptography, and blockchain implementation.
Federated learning framework for privacy-preserving distributed machine learning.
Kyber KEM and lattice-based cryptographic algorithms for quantum-resistant security.
Custom blockchain implementation for immutable event logging and verification.