Tensorflow Implementation and result of Auto-encoder Based Communication System From Research Paper : "An Introduction to Deep Learning for the Physical Layer" http://ieeexplore.ieee.org/document/8054694/

covert-ml is a GAN-based covert communication method that enables establishing a reliable, undetectable covert channel within autoencoder wireless communication systems with the minimum impact.

These codes aim to model a communication system by AutoEncoders and simulate its authentication based on Hanzo papers

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Hybrid diagnostic system combining rule-based engine and enhanced autoencoder with multi-protocol communication (HTTP, UDP, Layer 2)

Developed SRL-TS, a robust framework for secure time synchronization in distributed systems, integratingReinforcement Learning (PPO) and autoencoder-based anomaly detection to dynamically adjust sync intervals anddetect malicious time updates.Implemented multi-node timestamp communication and control using TCP socket programming.