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Internet of Things

Robust Encryption Framework for IoT Devices Based on Bit-plane Extraction, Chaotic Sine Models, and Quantum Operations

Mujeeb Ur Rehman, Arslan Shafqiue

Published Jun 2, 2024• 12 citations
Publisher

Abstract

In the domain of Internet of Things (IoT) applications, quantum computers offer the promise of addressing complex computational issues that traditional cryptographic methods find challenging. The unparalleled computational power of quantum computers makes existing cryptographic schemes, tailored to mitigate computational complexity, ineffective. This research introduces a robust encryption scheme designed specifically for digital data exchanged between IoT devices such as smartphones, smart sensors, and smart health monitoring devices. The proposed encryption framework is based on bit-plane extraction-based encryption, the chaotic sine model, the hyperchaotic map, the quantum baker map, and quantum operations such as quantum selective scrambling. The proposed methodology involves three key phases: the first and last phase related to permutation, which is performed at the bit level based on discrete bit-plane scrambling, bit-plane extraction, and hyperchaotic mapping. However, the second phase is based on diffusion, which depends on the chaotic sine model. During the initial stage, creating correlations among image pixels, along with a couple of chaotic sequences using a quantum baker map, is accomplished through a superposition of quantum- states. Before applying diffusion, the pixels of the grayscale image are encoded using a single qubit, and quantum operations are based on a quantum circuit featuring swap gates. To introduce pixel-level permutation, a hyperchaotic map generates random sequences within the range of 0 to 255. A circular shift further shuffles the pixel rows and pixel columns of the permuted image pixels. To enhance the digital image security further, bit-planes are extracted from the permuted bit-planes. Then, the bits within each bit plane are scrambled using a random sequence generated by the hyperchaotic map. Finally, the encoded bit planes are merged to produce a final encrypted image. Experimental results demonstrate the effectiveness of the proposed methodology, with security parameters such as correlation, entropy, and key space measuring at 0.0001, 7.999, and >2100, respectively. Furthermore, to assess performance in relation to computational complexity, a detailed analysis of computational time is conducted. The results reveal that the proposed encryption scheme can execute all encryption steps presented in the proposed method in less than one second. These findings demonstrate the secure transmission of digital data between IoT devices and show the suitability of the proposed encryption scheme for real-time applications.

DOI
10.1016/j.iot.2024.101241

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In the domain of Internet of Things (IoT) applications, quantum computers offer the promise of addressing complex computational issues that traditional cryptographic methods find challenging. The unparalleled computational power of quantum computers makes existing cryptographic schemes, tailored to mitigate computational complexity, ineffective. This research introduces a robust encryption scheme designed specifically for digital data exchanged between IoT devices such as smartphones, smart sensors, and smart health monitoring devices. The proposed encryption framework is based on bit-plane extraction-based encryption, the chaotic sine model, the hyperchaotic map, the quantum baker map, and quantum operations such as quantum selective scrambling. The proposed methodology involves three key phases: the first and last phase related to permutation, which is performed at the bit level based on discrete bit-plane scrambling, bit-plane extraction, and hyperchaotic mapping. However, the second phase is based on diffusion, which depends on the chaotic sine model. During the initial stage, creating correlations among image pixels, along with a couple of chaotic sequences using a quantum baker map, is accomplished through a superposition of quantum- states. Before applying diffusion, the pixels of the grayscale image are encoded using a single qubit, and quantum operations are based on a quantum circuit featuring swap gates. To introduce pixel-level permutation, a hyperchaotic map generates random sequences within the range of 0 to 255. A circular shift further shuffles the pixel rows and pixel columns of the permuted image pixels. To enhance the digital image security further, bit-planes are extracted from the permuted bit-planes. Then, the bits within each bit plane are scrambled using a random sequence generated by the hyperchaotic map. Finally, the encoded bit planes are merged to produce a final encrypted image. Experimental results demonstrate the effectiveness of the proposed methodology, with security parameters such as correlation, entropy, and key space measuring at 0.0001, 7.999, and >2100, respectively. Furthermore, to assess performance in relation to computational complexity, a detailed analysis of computational time is conducted. The results reveal that the proposed encryption scheme can execute all encryption steps presented in the proposed method in less than one second. These findings demonstrate the secure transmission of digital data between IoT devices and show the suitability of the proposed encryption scheme for real-time applications.
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The advent of quantum computers could enable the resolution of complex computational problems that conventional cryptographic protocols find challenging. As a result, the formidable computing capabilities of quantum computers may render all present-day cryptographic schemes that rely on computational complexity ineffectual. Inspired by these possibilities, the primary purpose of this paper is to suggest a quantum image encryption scheme based on quantum cellular automata with mixed multi-chaos hybrid maps and a hyperchaotic system with quantum operations. To achieve desirable encryption outcomes, we designed an encryption scheme involving two main operations: (1) pixel-level diffusion and (2) pixel-level permutation. Initially, the secret keys generated using the hyperchaotic system were closely tied to the original image. During the first phase, the establishment of correlations among the image pixels, in addition to the three chaotic sequences obtained from the hyperchaotic system, was achieved with the application of a quantum-state superposition and measurement principle, wherein the color information of a pixel is described using a single qubit. Therefore, the three channels of the plain image were subjected to quantum operations, which involve Hadamard transformation and the quantum-controlled NOT gate, before the diffusion of each color channel with the hyperchaotic system. Subsequently, a quantum ternary Toffoli gate was used to perform the diffusion operation. Next, the appropriate measurement was performed on the three diffused channels. To attain the confusion phase, a blend of mixed multi-chaos hybrid maps and a two-dimensional quantum cellular automaton was used to produce random and chaotic sequence keys. Subsequently, the circular shift was utilized to additionally shuffle the rows and columns of the three diffused components, in order to alter the positions of their pixel values, which significantly contributes to the permutation process. Lastly, the three encoding channels, R, G, and B, were merged to acquire the encrypted image. The experimental findings and security analyses established that the designed quantum image encryption scheme possesses excellent encryption efficiency, a high degree of security, and the ability to effectively withstand a diverse variety of statistical attacks.
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In the Internet of Things environment, the secure transmission of digital images has attracted much attention. To improve the confidentiality, we propose an image cryptosystem adopting a quantum chaotic map and the certain security-enhanced mechanisms. Firstly, we use the good random characteristics of quantum chaotic sequences to enhance security performance. Then, we introduce a plaintext correlation mechanism and a diffusion-permutation-diffusion structure in the cryptosystem. Finally, we verify the cryptosystem on a common secure communication platform. The theoretical and statistical analysis results demonstrate that the cryptosystem has excellent performance and can resist various cryptographic attacks. Moreover, feasibility and effectiveness of the image cryptosystem are verified on the Internet of Things secure communication experimental platform. It proves that the proposed image cryptosystem is a preferred and promising secure communication technology solution.
Data, especially image data, is transmitted at an incredible rate due to the exponential growth in the number of connected devices brought about by the fast development of consumer electronics. Data transmission security remains fundamental in effective communication systems, especially with the emergence of the quantum era. Quantum advancements challenge traditional asymmetric cryptography, necessitating the requirement for new encryption schemes. The multimedia encryption schemes pose further challenges due to its large size, structural complexity, real-time requirements, and unique attack vectors specific to multimedia data. The current classical image encryption algorithms do not fully address the challenges posed by Quantum technology for securing the multimedia transmission. This paper proposes a hybrid framework combining Quantum Key Distribution (QKD), chaos-based encryption, and Post-Quantum Cryptography (PQC) to secure multimedia data, particularly images, in IoT consumer electronic networks. Integrating 2D-Logistic Sine Coupling Map (2D-LSCM), initialized with the Keys generated from QKD, and NTRU algorithm, this scheme achieves robust security and efficient performance. This new architecture improves processing speeds and enhances specificity and sensitivity values, fortifying chaotic map performance. Our experimental results and comprehensive security analysis demonstrate the security and performance of the framework. Correlation Analysis using Person correlation coefficient, with a nearing zero value, ensures the confidentiality of the encrypted image.