As internet traffic continues to grow exponentially, the ability to accurately classify and analyze it becomes increasingly important for ensuring network performance, security, and reliability. Traditional traffic classification methods often rely on static rules which are becoming less effective for the increasing complexity of network environments, the dynamicity of protocols, and the growth of encrypted traffic. This necessitates the development of more sophisticated techniques that can accurately represent and classify internet packets based on their intrinsic characteristics that derive both from the header and payload. The primary challenge lies in creating a representation of each packet that summarizes its significant features while being computationally efficient and scalable.