后 COVID 时代的新视角:通过去复用感知器进行远程牙科加密。

Joydeep Dey, Arindam Sarkar, Sunil Karforma
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引用次数: 0

摘要

本文提出了一种在新兴的远程牙科领域对口内信息进行安全加密的有效机制。由于全球冠状病毒病(COVID)患者急剧增加,远程牙科服务最适合于后冠状病毒病时代。我们提出了一种智能感知器,该感知器具有去多路复用能力,可将数据传输给牙医。通过病人和牙医对感知器应用的学习规则,开发出了精确的会话密钥。为简单起见,强烈建议以高度安全的方式传输牙龈炎数据,以保证患者数据的完整性。牙龈炎是一种重要的牙科疾病,主要由细菌定植引起。它表现为牙龈出血和牙龈发炎。在这种大流行病的背景下,远程牙科系统需要向牙医进行加密传输,以便及早诊断和治疗。然后,牙龈炎数据会被解复用器分成若干部分,然后生成个人建议的标头。这样做主要是为了混淆入侵者对口内数据真实性的认识。与经典算法相比,对建议的部分份额进行了 Chi-square、Avalanche、Strict Avalanche 等处理,以产生良好的结果。为了迷惑入侵者,对字符频率、浮动频率和自相关性进行了广泛测试。这是一种在后 COVID 时代利用安全 Teledental 功能的新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Newer post-COVID perspective: Teledental encryption by de-multiplexed perceptrons.

Newer post-COVID perspective: Teledental encryption by de-multiplexed perceptrons.

Newer post-COVID perspective: Teledental encryption by de-multiplexed perceptrons.

Newer post-COVID perspective: Teledental encryption by de-multiplexed perceptrons.

This paper presents an efficient mechanism for secured encryption of intraoral information in the emerging field of Teledental. Due to global rapid surge in the (Coronavirus Disease) COVID patients, the services of Teledental are best suited in the newer post-COVID era. A devised perceptron has been intelligently embedded with de-multiplexing ability to transmit data to the dentists has been proposed. Exact session key has been developed through learning rules applied on the perceptrons by both the patient and dentist. For simplicity, gingivitis data is highly recommended to transmit in a highly secured manner with patients' data integrity. Gingivitis is an important dental disease which is primarily caused by the bacterial colonization. It shows gum bleeding and inflammations in the gingiva. Encrypted transmission is required to the Dentist for early diagnosis and treatment in Teledental system in this pandemic context. Gingivitis data are then broken into parts by the demultiplexer followed by individual proposed header generation. It is predominantly done to confuse the intruders about the originality of the intraoral data. Chi-square, Avalanche, Strict Avalanche, etc. were carried on the proposed partial shares to generate good outcomes when compared to classical algorithms. To confuse the intruders, character frequency, floating frequency, and autocorrelation were tested extensively. It is a newer approach to avail the secured Teledental features in post-COVID time.

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