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Due to advanced development in information technologies, cybersecurity and biometric approaches becomes significantly increased. A new multiple secret share creation scheme for biometric images is proposed. To enhance the shares security, each shares are encrypted by using stream cipher of lightweight cryptography (LWC). For increasing the effectiveness of the stream cipher, here the optimal key selection process takes place by elephant herd optimization (EHO) algorithm. The performance of the projected technique of by elephant herd optimization based stream cipher (SC-EHO) is assessed and the results are examined under diverse aspects on iris images. The experimental results depicted that the projected technique has reached to maximum security compared to other methods. The experimental values ensured that the SC-EHO algorithm has obtained a higher PSNR of 56.30dB and throughput of 31MB.

Owing to the rapid growth of information technologies, a rising need for cybersecurity and biometric technologies is increasingly evolving. Biometrics image protection is an important problem as digital images and medical details are distributed via public networks. This research work proposed a threshold-based share creation scheme for Biometrics images. To enhance the security level of the shares, each shares are encrypted by Light Weight Cryptography (LWC)-Stream Cipher method. To increase the stream cipher encryption efficiency, optimal keys are selected by Ant Lion Optimization (ALO) technique. The benefit of consuming stream ciphers is that the speed of execution is maximum over block cipher and less complex. The benefit of the suggested stream cipher approach is that the decoding of the keys in the keystream and the characters in the plain text denotes decrypted biometrics image will improve device reliability. From the implementation results proposed model achieves the maximum PSNR with the security of Biometrics images, compared to other existing techniques.