Audio Splicing Detection and Localization Using Environmental Signature

Audio splicing is one of the most common manipulation techniques in the area of audio forensics. In this paper, the magnitudes of acoustic channel impulse response and ambient noise are proposed as the environmental signature. Specifically, the spliced audio segments are detected according to the magnitude correlation between the query frames and reference frames via a statically optimal threshold. The detection accuracy is further refined by comparing the adjacent frames. The effectiveness of the proposed method is tested on two data sets. One is generated from TIMIT database, and the other one is made in four acoustic environments using a commercial grade microphones. Experimental results show that the proposed method not only detects the presence of spliced frames, but also localizes the forgery segments with near perfect accuracy. Comparison results illustrate that the identification accuracy of the proposed scheme is higher than the previous schemes. In addition, experimental results also show that the proposed scheme is robust to MP3 compression attack, which is also superior to the previous works.Comment: Submitted to IEEE Transactions on Information Forensics and Securit

Detecção de réplicas em evidências de áudio usando um esquema adaptativo de audio fingerprinting

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2017.Este trabalho aborda o problema de autenticação passiva de áudio e objetiva propor um método automático para detecção de edições fraudulentas produzidas através da replica- ção de trechos curtos de sinal dentro de uma mesma evidência de áudio. O método proposto é baseado em um esquema adaptativo de Audio Fingerprinting. Diversos sistemas de Audio Fingerprinting existentes são analisados, e, conforme os requisitos estipulados para a aplicação forense, de elevada robustez e usabilidade, uma abordagem de Audio Fingerprinting binária baseada na distribuição do espectro de Fourier é escolhida. Um sistema adaptativo é proposto, o qual é ajustado teoricamente e empiricamente para cada evidência de áudio. As simulações mostram uma robustez do método contra distorções no domínio do tempo e da frequência. A capacidade de discriminar áudios correspondentes a um mesmo texto e diferenciá-los de réplicas também é analisada. Novas modificações são propostas, como o emprego de um critério de dupla detecção, e o sistema final obtido demonstrou ser aplicável a áudios de longa duração e robusto contra mascaramentos por inserção de ruído.This work addresses the problem of passive audio authentication and aims to propose an automatic method to detect forgeries produced by the replication of an audio signal within the same audio evidence. The proposed method uses an adaptive Audio Fingerprinting system. Several existing systems are analyzed, and, according to the de_ned requirements of usability and robustness against masking distortions, an adaptive binary Audio Fingerprinting scheme based on the Fourier spectrum distribution is chosen. An adaptive system is proposed, which is theoretically and empirically adjusted for each audio evidence. Simulations show that the designed system is robust against time and frequency-domain distortions. The power to discriminate repeated text speech and distinguish it from audio replicas is also analyzed. Further adjustments are suggested, such as the use of a double detection criteria, and the _nal scheme was able to detect short replicas, distorted by noise insertion, even within long audio evidence