True random number generators(TRNG)are im-portant counterparts to pseudorandom number generators(PRNG),especially for high security applications such as cryptography.They produce unpredictable,non-repeatable random sequences.However,most TRNGs require special-ized hardware to extract entropy from physical phenom-ena and tend to be slower than PRNGs.These generators usually require post-processing algorithms to eliminate bi-ases but in turn,reduces performance.In this paper,a new post-processing method based on hyperchaos is proposed for software-based TRNGs which not only eliminates statistical biases but also provides amplification in order to improve the performance of TRNGs.The proposed method utilizes the in-herent characteristics of chaos such as hypersensitivity to in-put changes,diffusion,and confusion capabilities to achieve these goals.Quantized bits of a physical entropy source are used to perturb the parameters of a hyperchaotic map,which is then iterated to produce a set of random output bits.To de-pict the feasibility of the proposed post-processing algorithm,it is applied in designing TRNGs based on digital audio.The generators are analyzed to identify statistical defects in addi-tion to forward and backward security.Results indicate that the proposed generators are able to produce secure true ran-dom sequences at a high throughput,which in turn reflects on the effectiveness of the proposed post-processing method.