化学算法:基于分子逻辑门的数据保护

IF 39 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Yu Dong, Shiyu Feng, Weiguo Huang and Xiang Ma
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引用次数: 0

摘要

数据安全对于保障文档、货币、商户标签等纸质资产的完整性、真实性和保密性至关重要,进而对个人隐私乃至国家安全产生深远影响。高安全级别的逻辑数据保护范例通常仅限于软件(数字电路),很少应用于使用刺激响应材料(srm)的物理设备。主要原因是大多数srm缺乏可编程和可控的开关行为。传统的srm通常在响应刺激时产生静态、单一和高度可预测的信号,将其限制为简单的“BUFFER”或“INVERT”逻辑运算,安全性较低。然而,srm的最新进展使外部刺激下的动态、多维和不可预测的输出信号成为可能。这一突破为基于具有复杂逻辑运算和算法的srm的复杂加密和防伪硬件铺平了道路。本文主要关注基于srm的数据保护,强调在srm构建的硬件中集成复杂的逻辑和算法,而不是化学或材料结构的演变。它还讨论了当前的挑战,并探讨了该领域的未来方向,例如将srm与人工智能(AI)相结合。这篇综述填补了现有文献的空白,并代表了进入基于srm的加密和防伪技术的未知领域的开创性步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Algorithm in chemistry: molecular logic gate-based data protection

Algorithm in chemistry: molecular logic gate-based data protection

Algorithm in chemistry: molecular logic gate-based data protection

Data security is crucial for safeguarding the integrity, authenticity, and confidentiality of documents, currency, merchant labels, and other paper-based assets, which sequentially has a profound impact on personal privacy and even national security. High-security-level logic data protection paradigms are typically limited to software (digital circuits) and rarely applied to physical devices using stimuli-responsive materials (SRMs). The main reason is that most SRMs lack programmable and controllable switching behaviors. Traditional SRMs usually produce static, singular, and highly predictable signals in response to stimuli, restricting them to simple “BUFFER” or “INVERT” logic operations with a low security level. However, recent advancements in SRMs have collectively enabled dynamic, multidimensional, and less predictable output signals under external stimuli. This breakthrough paves the way for sophisticated encryption and anti-counterfeiting hardware based on SRMs with complicated logic operations and algorithms. This review focuses on SRM-based data protection, emphasizing the integration of intricate logic and algorithms in SRM-constructed hardware, rather than chemical or material structural evolutions. It also discusses current challenges and explores the future directions of the field—such as combining SRMs with artificial intelligence (AI). This review fills a gap in the existing literature and represents a pioneering step into the uncharted territory of SRM-based encryption and anti-counterfeiting technologies.

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来源期刊
Chemical Society Reviews
Chemical Society Reviews 化学-化学综合
CiteScore
80.80
自引率
1.10%
发文量
345
审稿时长
6.0 months
期刊介绍: Chemical Society Reviews is published by: Royal Society of Chemistry. Focus: Review articles on topics of current interest in chemistry; Predecessors: Quarterly Reviews, Chemical Society (1947–1971); Current title: Since 1971; Impact factor: 60.615 (2021); Themed issues: Occasional themed issues on new and emerging areas of research in the chemical sciences
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