{"title":"基于轻量级密码学的生物特征图像加密多秘密共享创建","authors":"Elavarasi Gunasekaran, Vanitha Muthuraman","doi":"10.1166/JCTN.2020.9441","DOIUrl":null,"url":null,"abstract":"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\n 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\n 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\n 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.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5469-5476"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Light Weight Cryptography Based Encrypted Multiple Secret Share Creation for Biometrics Images\",\"authors\":\"Elavarasi Gunasekaran, Vanitha Muthuraman\",\"doi\":\"10.1166/JCTN.2020.9441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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\\n 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\\n 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\\n 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.\",\"PeriodicalId\":15416,\"journal\":{\"name\":\"Journal of Computational and Theoretical Nanoscience\",\"volume\":\"17 1\",\"pages\":\"5469-5476\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational and Theoretical Nanoscience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1166/JCTN.2020.9441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Chemistry\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Theoretical Nanoscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1166/JCTN.2020.9441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Chemistry","Score":null,"Total":0}
Light Weight Cryptography Based Encrypted Multiple Secret Share Creation for Biometrics Images
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.