“Noise Injection” seeks to explore methods by which an individual’s data streams can be obfuscated or rendered statistically invalid via the injection of irrelevant data into an existing data stream.  The project serves to explore the methods by which the data on which machines are trained can be engineered to invalidate the training.  This serves the purpose of both building a mechanism of delivering some amount of Internet privacy to the individual, as well as providing an understanding of how data engineering attacks can be executed so that methods can in turn be developed to defeat malicious attacks by bad-actors.