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Ruggedizing LTE Security Using Hybridization of AES and RSA to Provide Double Layer Security

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Data Analytics and Management

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 54))

Abstract

Achieving better security for the transmission of data over cellular networks has always being a hard nut to crack. Security of long-term evolution (LTE) network is prime concern because of existence of malicious attackers. The security of network can be enhanced by utilizing cryptography. However, each cryptographic algorithm has its own pros and cons. So, hybridization (merging two or more algorithms) is one of the solutions to achieve better security. In this paper, double layer protection is implemented in order to ruggedize the security mechanism of LTE networks. The proposed algorithm utilizes better speed of AES and robust security of Rivest–Shamir–Adleman (RSA) together to achieve a hybrid system with improved performance compared to the traditional algorithm. The cryptanalysis has been intricated by increasing the number of keys to six. Further, the time required for encryption of keys is less when compared to decryption making the network more rugged and secure. In order to further enhance the speed, the concept of parallel processing is utilized. Then, proposed framework is analysed based on various parameters, and it is experimentally concluded that it provides approximately 22.7% increment in acceleration when compared to encryption rate and about 22.3% increment in acceleration when compared to decryption rate. 10% enhancement in percentage of avalanche effect has been achieved thereby increasing confusion in ciphertext and reducing chances of decoding. 5.39% increment in PSNR values of the proposed algorithm has been achieved when compared to existing algorithm.

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Correspondence to Anu Ahlawat .

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Ahlawat, A., Nandal, V. (2021). Ruggedizing LTE Security Using Hybridization of AES and RSA to Provide Double Layer Security. In: Khanna, A., Gupta, D., Pólkowski, Z., Bhattacharyya, S., Castillo, O. (eds) Data Analytics and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 54. Springer, Singapore. https://doi.org/10.1007/978-981-15-8335-3_12

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