METHOD AND DEVICE FOR DETECTING FUZZING ANALYSIS ON AN ELECTRONIC DEVICE

A method is provided for detecting a fuzzing analysis in a device. In the method, a new message of a message type is received from a second device. The message type of the new message is predicted from previously received messages. In one embodiment, the prediction is performed using a machine learning model. Also, the message type of the new message is determined. The message type may be determined by decoding and parsing the new message using instruction execution circuitry of a processor. A likelihood that the predicted message type compares favorably to the determined message type of the new message is computed. In another embodiment, a lookup table of likely subsequent messages to previously received messages is stored in the first electronic device. If it is determined that the predicted message type does not compare favorably to a threshold likelihood value, an indication of a fuzzing attack is indicated.