ABSTRACT

Audio files are frequent targets of malicious users who seek illegal profit trading with fake-quality content. For increasing the confidence in the integrity of audio files, the detection of fake-quality content is an important task. This paper proposes a method for detecting Advanced Audio Coding (AAC) compression on suspicious WAV files, in which the variance of the Modified Discrete Cosine Transform (MDCT) characterises four compression bitrates: uncompressed, 64 kbps, 128 kbps, and 256 kbps. This scheme takes advantage of the reduction of the variance of the high-frequency MDCT coefficients in compressed signals. Data obtained from MDCT coefficients generate a high-dimensional feature space. Hence, Principal Component Analysis, followed by Linear Discriminant Analysis, is used for projecting the high-dimensional data onto a lower-dimensional space. Besides, six supervised learning algorithms are compared for classifying four compression bitrates. The experiments show that using audio samples with 20 seconds and 1024 MDCT coefficients, an accuracy of 93% is reached with a Bayesian classifier. Collaterally, the detection between uncompressed and compressed signals attains an accuracy of 97% with Multinomial Logistic Regression. In conclusion, the proposed approach can detect previous AAC compression and can be potentially used when it is unfeasible to recover the suspicious signal completely.

摘要

音频文件是恶意用户的常见目标，他们通过虚假质量内容寻求非法利润交易。为了提高对音频文件完整性的信心，检测假质量内容是一项重要任务。本文提出了一种检测可疑 WAV 文件的高级音频编码 (AAC) 压缩的方法，其中改进离散余弦变换 (MDCT) 的方差表征了四种压缩比特率：未压缩、64 kbps、128 kbps 和 256 kbps。该方案利用了压缩信号中高频 MDCT 系数方差的减小。从 MDCT 系数获得的数据生成一个高维特征空间。因此，主成分分析，然后是线性判别分析，用于将高维数据投影到低维空间。此外，比较了六种监督学习算法对四种压缩比特率的分类。实验表明，使用具有 20 秒和 1024 个 MDCT 系数的音频样本，使用贝叶斯分类器可以达到 93% 的准确率。此外，使用多项 Logistic 回归，未压缩和压缩信号之间的检测精度达到 97%。总之，所提出的方法可以检测以前的 AAC 压缩，并且可以在无法完全恢复可疑信号时使用。贝叶斯分类器的准确率达到 93%。此外，使用多项 Logistic 回归，未压缩和压缩信号之间的检测精度达到 97%。总之，所提出的方法可以检测以前的 AAC 压缩，并且可以在无法完全恢复可疑信号时使用。贝叶斯分类器的准确率达到 93%。此外，使用多项 Logistic 回归，未压缩和压缩信号之间的检测精度达到 97%。总之，所提出的方法可以检测以前的 AAC 压缩，并且可以在无法完全恢复可疑信号时使用。