Machine learning model parameter based encryption

A computer-implemented method comprising:

• receiving a first password by a password encoder, the password encoder comprising one or more machine learning models;
• generating, by the password encoder using the first password, a first key;
• modifying model parameters of an encoder model using the first key to result in a modified encoder;
• receiving first data encapsulating second data in a hidden compartment;
• encoding, by the modified encoder, the first data to generate an embedding;
• decoding, by a decoder operating in tandem with the modified encoder, the embedding to result in a representation of the second data, the decoder comprising one or more machine learning models;
• providing the representation of the second data to a consuming application or process;
• wherein inputting the first data into the encoder and the decoder prior to modification results in a representation of the first data.

A computer-implemented method comprising:

• receiving a first password by a password encoder, the password encoder comprising one or more machine learning models;
• generating, by the password encoder using the first password, a first key;
• modifying weights and biases of a decoder operating in tandem with an encoder using the first key to result in a modified decoder, the decoder comprising one or more machine learning models, the encoder being different from the password encoder and comprising one or more machine learning models;
• receiving first data encapsulating second data in a hidden compartment;
• encoding, by the encoder, the first data to generate an embedding;
• decoding, by the modified decoder, the embedding to result in a representation of the second data;
• and
• providing the representation of the second data to a consuming application or process;
• wherein inputting the first data into the decoder prior to modification results in a representation of the first data.