Department of Computer Science and Engineering, School of Technology, GITAM Deemed to be University, Visakhapatnam 530045, Andhra Pradesh, India.
Department of Electrical and Computer Engineering, Lebanese American University, Beirut 1102 2801, Lebanon.
Sensors (Basel). 2022 Sep 6;22(18):6741. doi: 10.3390/s22186741.
The industry-based internet of things (IIoT) describes how IIoT devices enhance and extend their capabilities for production amenities, security, and efficacy. IIoT establishes an enterprise-to-enterprise setup that means industries have several factories and manufacturing units that are dependent on other sectors for their services and products. In this context, individual industries need to share their information with other external sectors in a shared environment which may not be secure. The capability to examine and inspect such large-scale information and perform analytical protection over the large volumes of personal and organizational information demands authentication and confidentiality so that the total data are not endangered after illegal access by hackers and other unauthorized persons. In parallel, these large volumes of confidential industrial data need to be processed within reasonable time for effective deliverables. Currently, there are many mathematical-based symmetric and asymmetric key cryptographic approaches and identity- and attribute-based public key cryptographic approaches that exist to address the abovementioned concerns and limitations such as computational overheads and taking more time for crucial generation as part of the encipherment and decipherment process for large-scale data privacy and security. In addition, the required key for the encipherment and decipherment process may be generated by a third party which may be compromised and lead to man-in-the-middle attacks, brute force attacks, etc. In parallel, there are some other quantum key distribution approaches available to produce keys for the encipherment and decipherment process without the need for a third party. However, there are still some attacks such as photon number splitting attacks and faked state attacks that may be possible with these existing QKD approaches. The primary motivation of our work is to address and avoid such abovementioned existing problems with better and optimal computational overhead for key generation, encipherment, and the decipherment process compared to the existing conventional models. To overcome the existing problems, we proposed a novel dynamic quantum key distribution (QKD) algorithm for critical public infrastructure, which will secure all cyber-physical systems as part of IIoT. In this paper, we used novel multi-state qubit representation to support enhanced dynamic, chaotic quantum key generation with high efficiency and low computational overhead. Our proposed QKD algorithm can create a chaotic set of qubits that act as a part of session-wise dynamic keys used to encipher the IIoT-based large scales of information for secure communication and distribution of sensitive information.
工业物联网(IIoT)描述了 IIoT 设备如何增强和扩展其生产设施、安全性和效率的功能。IIoT 建立了一个企业对企业的设置，这意味着各个行业都有几个工厂和制造单位，这些工厂和制造单位依赖于其他部门的服务和产品。在这种情况下，各个行业需要在共享环境中与其他外部部门共享他们的信息，而这个共享环境可能并不安全。检查和检查如此大规模的信息，并对大量的个人和组织信息执行分析保护，需要进行身份验证和保密，以确保在黑客和其他未经授权的人员非法访问后，总数据不会受到威胁。同时，这些大量的机密工业数据需要在合理的时间内进行处理，以提供有效的成果。目前，存在许多基于数学的对称和非对称密钥加密方法以及基于身份和属性的公钥加密方法，以解决上述问题和限制，例如计算开销和在大规模数据隐私和安全的加密和解密过程中关键生成所花费的更多时间。此外，加密和解密过程所需的密钥可以由第三方生成，而第三方可能会受到威胁，导致中间人攻击、暴力攻击等。同时，还有一些其他的量子密钥分发方法可用于在无需第三方的情况下生成加密和解密过程所需的密钥。然而，在这些现有的 QKD 方法中，仍然存在一些攻击，如光子数分裂攻击和伪造状态攻击等。我们工作的主要动机是解决和避免这些现有的问题，并与现有的传统模型相比，在密钥生成、加密和解密过程中具有更好和更优的计算开销。为了克服现有的问题，我们提出了一种新的用于关键公共基础设施的动态量子密钥分发(QKD)算法，该算法将保护 IIoT 中的所有网络物理系统。在本文中，我们使用了新的多量子比特表示来支持高效和低计算开销的增强型动态量子密钥生成。我们提出的 QKD 算法可以创建一组混沌量子比特，作为用于加密基于 IIoT 的大规模信息的会话级动态密钥的一部分，用于安全通信和分发敏感信息。
