## 1 Introduction
This favors the method's classification in the authenticity checking category. Discrepancies between the variation of the ENF extracted from the analyzed recording and the reference indicate that the recording has been tampered with. Cut, copy-paste, move, and other similar operations can be detected in this way, showing that the method can be used for integrity checking of audio recordings. It is shown in [6], on the information page that the mains frequency is the same in all the countries that are connected to the synchronous grid, except short time fluctuations. Of course, the best results are obtained if the ENF is measured locally, using commercial meters, for example the ones available from [6]. The ENF criterion has a blend of characteristics of active and passive methods. It can be considered active because it uses reference data, but also passive because the reference data is not embedded into recordings using a certain developed method, but naturally, as a result of coupling between the power distribution network and the audio recording devices. The power line frequency (or mains frequency, ENF) has a nominal value of 50 or 60 Hz, depending on the country. Most of the world adopted the 50 Hz system. Both values are in the audible range. Depending on the performance of the audio recording devices, the power line signal can be picked up by them, manifesting as a noise called mains hum. The ENF criterion became one of the industry-standard multimedia forensics tools. A fully automated audio verification process based on it is used in the United Kingdom [8] and Singapore [9]. As the technology advanced, the recording devices got better at rejecting this noise, making the ENF criterion less effective. A short review of the proposed solutions follows. In [10] the characteristics of various transforms, like DFT (Discrete Fourier Transform), DCT (Discrete Cosine Transform), and DWT (Discrete Wavelet Transform) are discussed in the context of audio watermarking. In [11], the authors present a singular value decomposition (SVD) DWT-based watermarking algorithm that uses the statistical properties of the DWT coefficients to determine the quantization steps for the signals to be watermarked. In general, the transform-based algorithms are more resistant to various attacks, but they are more computationally complex. Time-based watermark algorithms also exist, like [12; 13; 14]. These algorithms are characterized by less required computation power, while also being less robust. Audio watermarking is still a topic in which new advances arise [15; 16; 17]. The new sonic watermarking system proposed in this paper is different from most other algorithms because it allows the use of the ENF criterion principles to analyse recordings made with new audio recording devices. Besides this introduction, the paper is structured as follows: Section 2 describes the fundamental requirements for an audio watermark suitable for integrity checking and authentication of audio recordings, Section 3 thoroughly describes the proposed method starting with presenting the scenario, all the involved signals, the watermark generator, the watermark extraction and processing methods to determine the integrity of a recording, Section 4 presents and discusses the results, and Section 5 concludes the paper.