Methods and devices for detecting a spoofing attack are provided. The method includes receiving a speech signal; applying a Fast Fourier Transform (FFT) to the speech signal to extract FFT features therefrom and feeding the extracted FFT features to a pre-trained deep neural network to assign a first confidence score to the speech signal; applying a Discrete cosine transform (DCT) to the speech signal to extract DCT features therefrom and feeding the extracted DCT features to a pre-trained deep neural network to assign a second confidence score to the speech signal; applying a pre-trained deep convolutional network (DCN) based on an end-to-end architecture to the speech signal to assign a third confidence score to the speech signal; computing a total confidence score based on the assigned confidence scores; and comparing the computed total confidence score to a predefined threshold to detect whether the received speech signal is spoofed.