# A Novel Image Encryption Algorithm Based on Voice Key and Chaotic Map
## 2 Principles of the Proposed Method
### Proposed Image Encryption and Decryption Algorithm
#### 2.2.1 Encryption Process
In addition, the commonly used analytical methods of encryption algorithms also include histogram and information entropy analysis [43; 44; 45; 46]. The encryption method proposed in this article is used for face recognition. Therefore, the gray distribution of the image can be arbitrarily changed while keeping the facial characteristics unchanged to construct the required histogram distribution and information entropy value without affecting the application of the algorithm. ## 5 Conclusions

This paper proposed an image encryption and decryption algorithm based on a voice data key. The remote identification scheme designed using this algorithm improves the robustness of the traditional face recognition verification method. The experiments show that the encryption and decryption algorithms are highly sensitive to the key and the sensitivity is adjustable. If the time-domain waveform of the user's voice differed by a single peak, or the peak frequency differs by 1 Hz, the encrypted image cannot be decrypted. The algorithm key space \(2^{232}\) has sufficient resistance to exhaustive attacks. On the basis of this algorithm, the key space can be further increased by adjusting the parameters. The correlation experiment between adjacent pixels showed that the maximum value of correlation coefficients is 0.1764, which appeared in the horizontal direction of the encrypted red channel at a peak frequency of 1200 Hz. The analysis of the differential attack experiment revealed that the minimum value of NPCR was 0.9891, which appeared in the encrypted blue channel at the peak frequency of 1200 Hz, and the UACI value was also close to the ideal value. The experiments showed that this scheme is feasible and has strong scalability. It can be extended by selecting different voice features of the users, by selecting different chaotic map, and by selecting different parameters of Equation (4) (\(K7\), k8 and k9). The highlights of this scheme are as follows. First, it uses two kinds of feature information of the user for authentication. Second, it uses the voice feature as a key. Third, it is suitable for large-scale promotion and application, i.e., the client only needs a computer or a mobile phone as an input device, and no other hardware devices are required to perform remote authentication from different places. The limitation of this scheme is that the identity authentication cannot be performed for deaf and mute individuals. One possible solution is that deaf and mute individuals may manually enter a key, but this will reduce the security of the system. In addition, the scheme can currently only authenticate one targeted individual, and only people can be authenticated. If the scheme is applied to other goals, the key extraction problem and the image recognition problem should also be solved. The next step would be to integrate artificial intelligence into the system to solve the problem of image recognition for authentication of different targets. Conceptualization, J.L. and T.F. ; methodology, J.L., T.F. and C.F; software, T.F. ; validation, J.L. ; writing--original draft preparation, J.L., L.H. and T.F. ; writing--review and editing, J.L., C.F. and L.H. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China (51774092), the Daqing City Guiding Science and Technology Plan Project (zd-2021-87), National Natural ScienceFoundation of Heilongjiang Province (LH2020E012) and the China Postdoctoral Science Foundation (2016M601399). **Institutional Review Board Statement**: Not applicable. **Informed Consent Statement**: Not applicable. **Data Availability Statement**: The data presented in this study are available on request from the corresponding author. **Conflicts of Interest**: The authors declare no conflict of interest. ## References

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