The project involves collecting and preprocessing data, splitting it into training and testing sets, defining the model architecture, training the model, and evaluating its performance. The ultimate goal is to develop an accurate and reliable model that can detect backdoors in Android applications, which can help improve the security of mobile devices.
The project involves a combination of data processing, machine learning, and software engineering skills, including programming in Python and familiarity with machine learning libraries such as Keras, Scikit-learn, and Pandas.