A Key Management Techniques in Wireless Sensor Networks

Ahmed, S; Salah, E; El‐Sayed, Ayman

doi:10.5120/cae2017652600

Cited by 7 publications

(2 citation statements)

References 50 publications

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“…SPNs have also been used in combination with other cryptographic techniques, such as key management and authentication, to provide a more comprehensive approach to image security [10]. For example, some image encryption algorithms based on SPNs use secret key management techniques to ensure that the encryption key is securely distributed and protected from unauthorized access [11].…”

Section: Introductionmentioning

confidence: 99%

Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption

et al. 2023

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With the explosion of the generation, transmission and sharing of image data over the Internet and other unsecured networks, the need for and significance of the development of novel image encryption algorithms are unprecedented. In this research work, we propose a novel framework for image encryption that is based on two hyperchaotic maps utilized in conjunction with the single neuron model (SNM). The framework entails three successive stages, where in every stage a substitution box (S-box) is applied, then XORing with an encryption key is carried out. The S-boxes and the encryption keys are generated from the numerical solutions of the hyperchaotic maps and the SNM. The performance of the proposed framework is gauged through a number of metrics, reflecting superior performance and complete asymmetry between the plain images and their encrypted versions. The main advantages of this work are (1) vast key space and (2) high encryption efficiency. The superior key space of 22551 is the result of employing the two hyperchaotic maps, while the improved efficiency, resulting in an average encryption rate of 8.54 Mbps, is the result of using the SNM as well as the employment of optimized parallel processing techniques. In addition, the proposed encryption framework is shown to output encrypted images that pass the NIST SP 800 suite. Average achieved values for the metrics include MSE of 9626, PSNR of 8.3 dB, MAE of 80.99, entropy of 7.999, NPCR of 99.6% and UACI of 31.49%.

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Section: Introductionmentioning

confidence: 99%

Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption

et al. 2023

View full text Add to dashboard Cite

show abstract

“…SPNs have also been used in combination with other cryptographic techniques, such as key management and authentication, to provide a more comprehensive approach to image security [12]. For example, some image encryption algorithms based on SPNs use secret key management techniques to ensure that the encryption key is securely distributed and protected from unauthorized access [13].…”

Section: Introductionmentioning

confidence: 99%

Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption

Alexan¹,

Chen²,

Por³

et al. 2023

Preprint

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With the explosion of the generation, transmission and sharing of image data over the Internet and other unsecured networks, the need and significance for the development of novel image encryption algorithms is unprecedented. In this research work, we propose a novel framework for image encryption that is based on two hyperchaotic maps, utilized in conjunction with the single neuron model (SNM). The framework entails three successive stages, where in every stage, a substitution box (S-box) is applied, then XORing with an encryption key is carried out. The S-boxes and the encryption keys are generated from the numerical solutions of the hyperchaotic maps and the SNM. The performance of the proposed framework is gauged through a number of metrics, reflecting superior performance and complete asymmetry between the plain images and their encrypted versions. However, the main advantages of this work are: (1) The attained width of the key space; and (2) The achieved efficiency in software implementation. The superior key space of 2^{2551} is the result of employing the two hyperchaotic maps, while the improved efficiency, resulting in an average encryption rate of 8.54 Mbps, is the result of the utilization of the single neuron model, as well as the employment of optimized parallel processing techniques. In addition, the proposed encryption framework is shown to output encrypted images that pass the NIST SP 800 suite.

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Robust encryption method based on AES-CBC using elliptic curves Diffie–Hellman to secure data in wireless sensor networks

2022

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A Key Management Techniques in Wireless Sensor Networks

Cited by 7 publications

References 50 publications

Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption

Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption

Hyperchaotic Maps and the Single Neuron Model: A Novel Framework for Chaos-Based Image Encryption

Robust encryption method based on AES-CBC using elliptic curves Diffie–Hellman to secure data in wireless sensor networks

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