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人类对密码学的心理障碍:来自精神分裂症患者 EEG 的真随机数生成器及其在分组加密的替代盒中的应用。

Human Psychological Disorder towards Cryptography: True Random Number Generator from EEG of Schizophrenics and Its Application in Block Encryption's Substitution Box.

机构信息

Department of Computer Science, Quaid-i-Azam University, Islamabad, Pakistan.

Department of Software Engineering, Foundation University Islamabad, Islamabad, Pakistan.

出版信息

Comput Intell Neurosci. 2022 Jun 21;2022:2532497. doi: 10.1155/2022/2532497. eCollection 2022.

Abstract

Schizophrenia is a multifaceted chronic psychiatric disorder that affects the way a human thinks, feels, and behaves. Inevitably, natural randomness exists in the psychological perception of schizophrenic patients, which is our primary source of inspiration for this research because true randomness is the indubitably ultimate valuable resource for symmetric cryptography. Famous information theorist Claude Shannon gave two desirable properties that a strong encryption algorithm should have, which are confusion and diffusion in his fundamental article on the theoretical foundations of cryptography. Block encryption strength against various cryptanalysis attacks is purely dependent on its confusion property, which is gained through the confusion component. In the literature, chaos and algebraic techniques are extensively used to design the confusion component. Chaos- and algebraic-based techniques provide favorable features for the design of the confusion component; however, researchers have also identified potential attacks on these techniques. Instead of existing schemes, we introduce a novel methodology to construct cryptographic confusion component from the natural randomness, which are existing in the psychological perception of the schizophrenic patients, and as a result, cryptanalysis of chaos and algebraic techniques are not applicable on our proposed technique. The psychological perception of the brain regions was captured through the electroencephalogram (EEG) readings during the sensory task. The proposed design passed all the standard evaluation criteria and validation tests of the confusion component and the random number generators. One million true random bits are assessed through the NIST statistical test suite, and the results proved that the psychological perception of schizophrenic patients is a good source of true randomness. Furthermore, the proposed confusion component attains better or equal cryptographic strength as compared to state-of-the-art techniques (2020 to 2021). To the best of our knowledge, this nature of research is performed for the first time, in which psychiatric disorder is utilized for the design of information security primitive. This research opens up new avenues in cryptographic primitive design through the fusion of computing, neuroscience, and mathematics.

摘要

精神分裂症是一种多方面的慢性精神障碍,会影响人类的思维、感觉和行为方式。不可避免的是,精神分裂症患者的心理感知存在自然随机性,这是我们这项研究的主要灵感来源,因为真正的随机性是对称密码学无可置疑的最终有价值资源。著名信息论学家克劳德·香农(Claude Shannon)在其关于密码学理论基础的基础文章中给出了一个强加密算法应该具有的两个理想属性,即混淆和扩散。块加密对各种密码分析攻击的强度完全取决于其混淆属性,而混淆属性是通过混淆组件获得的。在文献中,混沌和代数技术被广泛用于设计混淆组件。混沌和基于代数的技术为混淆组件的设计提供了有利的特性;然而,研究人员也已经确定了针对这些技术的潜在攻击。我们没有采用现有的方案,而是引入了一种从精神分裂症患者的心理感知中存在的自然随机性构建密码混淆组件的新方法,因此,混沌和代数技术的密码分析不适用于我们提出的技术。通过感觉任务期间的脑电图 (EEG) 读数来捕获大脑区域的心理感知。所提出的设计通过了混淆组件和随机数生成器的所有标准评估标准和验证测试。通过 NIST 统计测试套件评估了一百万个真正的随机位,结果证明精神分裂症患者的心理感知是真正随机数的良好来源。此外,与最先进的技术相比,所提出的混淆组件具有更好或相等的密码强度(2020 年至 2021 年)。据我们所知,这是首次利用精神障碍来设计信息安全原语的研究。这项研究通过融合计算、神经科学和数学,为密码学原语设计开辟了新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c713/9239775/c805b73e1c68/CIN2022-2532497.001.jpg

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