A Nano-Based High-Speed QCA Circuit for Information Security with Image Masking

A potential method for nanoscale computing, quantum-dot cellular automata (QCA) makes use of the electron tunneling between quantum dots inside a cell as well as the electrostatic interaction between surrounding dots. QCA technology outperforms traditional complementary metal-oxide semiconductor (CMOS) technology in terms of speed, power consumption, security, and space utilization. Due to the importance of security, this article investigates utilizing QCA to generate picture masks and security in these pictures. The mask picture is created by an encoder circuit, which may also be used as a decoder. Even if the secret key is still unknown, the original picture can be retrieved using the mask image. Improving the security characteristics in nano-communication, which uses QCA cells and nanodevices, is essential. Image masking entails encrypting an image using a random key to generate an encrypted picture, also known as a cipher image. After that, the original picture and the cipher image are merged to create a mask image, a hidden information set for users. With the secret key, this mask picture may obtain an image from another cipher image created with the same set of random keys. To ensure security in this paper, the suggested QCA encoder generates the mask picture. The efficacy of these designs was confirmed by using QCADesigner for functional verification. The simulation results show that the suggested solutions not only work well but also much surpass earlier approaches in terms of speed and space consumption. The higher performance of these optimum designs over other circuit designs highlights the potential of QCA technology to improve picture masking and security.

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Publication Details

Published
2024-12-24
DOI
https://doi.org/10.1109/ikt65497.2024.10892751
Primary Topic
Quantum-Dot Cellular Automata
Type
article
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article

A Nano-Based High-Speed QCA Circuit for Information Security with Image Masking

Saeid Seyedi, Hatam Abdoli
Quantum-Dot Cellular Automata
article

A Nano-Based High-Speed QCA Circuit for Information Security with Image Masking

Saeid Seyedi, Hatam Abdoli
article en

Abstract

A potential method for nanoscale computing, quantum-dot cellular automata (QCA) makes use of the electron tunneling between quantum dots inside a cell as well as the electrostatic interaction between surrounding dots. QCA technology outperforms traditional complementary metal-oxide semiconductor (CMOS) technology in terms of speed, power consumption, security, and space utilization. Due to the importance of security, this article investigates utilizing QCA to generate picture masks and security in these pictures. The mask picture is created by an encoder circuit, which may also be used as a decoder. Even if the secret key is still unknown, the original picture can be retrieved using the mask image. Improving the security characteristics in nano-communication, which uses QCA cells and nanodevices, is essential. Image masking entails encrypting an image using a random key to generate an encrypted picture, also known as a cipher image. After that, the original picture and the cipher image are merged to create a mask image, a hidden information set for users. With the secret key, this mask picture may obtain an image from another cipher image created with the same set of random keys. To ensure security in this paper, the suggested QCA encoder generates the mask picture. The efficacy of these designs was confirmed by using QCADesigner for functional verification. The simulation results show that the suggested solutions not only work well but also much surpass earlier approaches in terms of speed and space consumption. The higher performance of these optimum designs over other circuit designs highlights the potential of QCA technology to improve picture masking and security.

Bu-Ali Sina University (IR)
Openalex Percentile: Top 69%
Quantum-Dot Cellular Automata
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A Nano-Based High-Speed QCA Circuit for Information Security with Image Masking — Saeid Seyedi, Hatam Abdoli · (2024) | TGRS Research Map | TGRS