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Providing End-to-End Security Using Quantum Walks in IoT Networks

Authors :
Ahmed A. Abd El-Latif
Bassem Abd-El-Atty
Salvador E. Venegas-Andraca
Haitham Elwahsh
Md. Jalil Piran
Ali Kashif Bashir
Oh-Young Song
Wojciech Mazurczyk
Source :
IEEE Access, Vol 8, Pp 92687-92696 (2020)
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

Internet of Things acts an essential role in our everyday lives and it definitely has the potential to grow on the importance and revolutionize our future. However, the present communication technologies have several security related issues which is required to provide secure end to end connectivity among services. Moreover, due to recent, rapid growth of quantum technologies, most common security mechanisms considered secure today may be soon imperilled. Thus, the modern security mechanisms during their construction also require the power of quantum technologies to resist various potential attacks from quantum computers. Because of its characteristics, quantum walks (QW) is considered as a universal quantum computation paradigm that can be accepted as an excellent key generator. In this regard, in this paper a new lightweight image encryption scheme based on QW for secure data transfer in the internet of things platforms and wireless networking with edge computing is proposed. The introduced approach utilises the power of nonlinear dynamic behaviour of QW to construct permutation boxes and generates pseudo-random numbers for encrypting the plain image after dividing it into blocks. The results of the conducted simulation and numerical analyses confirm that the presented encryption algorithm is effective. The encrypted images have randomness properties, no useful data about the ciphered image can be obtained via analysing the correlation of adjacent pixels. Moreover, the entropy value is close to 8, the number of the pixel change rate is greater than 99.61%, and there is high sensitivity of the key parameters with large key space to resist various attacks.

Details

Language :
English
ISSN :
21693536
Volume :
8
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.f9605f554804c118f745331c48b373f
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2020.2992820