Cryptography by Synchronization of Hopfield Neural Networks that Simulate Chaotic Signals Generated by the Human Body

Ramos, Elias de Almeida; Filho, Joao Carlos Britto; Reis, Ricardo

doi:10.1109/newcas44328.2019.8961314

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Other uses of Hopfield NNs include using creating asymmetric cryptography by using the semblances of the NN with the human body to do synchronization [161]. Other uses for Hopfield NNs and its human-like similarities is using it in conjunction with DNA cryptography [104].…”

Section: -Neural Physically Unclonable Function (Puf)mentioning

confidence: 99%

The Dichotomy of Neural Networks and Cryptography: War and Peace

Zolfaghari

Koshiba

2022

ASI

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In recent years, neural networks and cryptographic schemes have come together in war and peace; a cross-impact that forms a dichotomy deserving a comprehensive review study. Neural networks can be used against cryptosystems; they can play roles in cryptanalysis and attacks against encryption algorithms and encrypted data. This side of the dichotomy can be interpreted as a war declared by neural networks. On the other hand, neural networks and cryptographic algorithms can mutually support each other. Neural networks can help improve the performance and the security of cryptosystems, and encryption techniques can support the confidentiality of neural networks. The latter side of the dichotomy can be referred to as the peace. There are, to the best of our knowledge, no current surveys that take a comprehensive look at the many ways neural networks are currently interacting with cryptography. This survey aims to fill that niche by providing an overview on the state of the cross-impact between neural networks and cryptography systems. To this end, this paper will highlight the current areas where progress is being made as well as the aspects where there is room for future research to be conducted.

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Section: -Neural Physically Unclonable Function (Puf)mentioning

confidence: 99%

The Dichotomy of Neural Networks and Cryptography: War and Peace

Zolfaghari

Koshiba

2022

ASI

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“…The most traditional encryption methods for digital images just concern the correlation between adjacent pixels and high redundancy of neighbor pixels [13,14]. The cryptography with chaotic dynamics has exceptional properties [15][16][17][18][19][20][21][22], because of the complexity and unpredictability of chaotic system. In this paper, a combination scheme of Arnold's cat map, Qi 3D four-wing chaos-system, and the Logistic system is employed which is sensitive to the keys from the analysis and evaluation.…”

Section: Introductionmentioning

confidence: 99%

A chaos-based medical image encryption method

Wang

2020

IJEECS

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<span lang="EN-US">The information in the e-health system involves the patient’s privacy which is extremely sensitive. For instance, these information record social security numbers and detailed medical history. When the breach happens, there are illegal, or disclosure behaviors taken to privacy that should be compromised security. In this paper, the medical digital images are protected by the proposed chaos-based encryption method in the process of transmission and utilization. Then the authentication is granted to patients and telemedicine staffs by the decryption method proposed. The Qi 3-D four wing chaotic system is employed in this method. The proposed method promises the keys with higher complexity and unpredictability than traditional cryptography methods by introducing the chaotic dynamics in the new cryptography. Digital medical images are used to validate the proposed method under the brute and the differential attacks. The pixels of the image are scrambled completely based on cat map and the sub-blocks of the image are diffused in the way that the original image is changed into a chaotic image robust to all kinds of attacks. The experiments show that the proposed method has higher performance and higher computation for decryption.</span>

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AI Makes Crypto Evolve

Zolfaghari

Koshiba

2022

ASI

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The recent literature reveals a dichotomy formed by a coevolution between cryptography and Artificial Intelligence (AI). This dichotomy consists of two sides, namely Crypto-Influenced AI (CIAI) and AI-Influenced Cryptography (AIIC). While it is pertinent to investigate this dichotomy from both sides, the first side has already been studied. In this review, we focused on AIIC. We identified and analyzed the stages on the evolutionary path of AIIC. Moreover, we attempted to anticipate what the future may hold for AIIC given the impact of quantum computing on the present and the future of AI.

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Cryptography by Synchronization of Hopfield Neural Networks that Simulate Chaotic Signals Generated by the Human Body

Cited by 3 publications

References 9 publications

The Dichotomy of Neural Networks and Cryptography: War and Peace

The Dichotomy of Neural Networks and Cryptography: War and Peace

A chaos-based medical image encryption method

AI Makes Crypto Evolve

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