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Quantum cryptography (QC) provides security to information through laws of nature, particularly quantum mechanics. The necessity of making QC a living reality has provided the impetus to advancement in material science, which led to many publications since 1996. Therefore, in this work, we analyze the articles in the Scopus database concerning the contribution of material science in the development of QC through scientometric methods. A total of 1395 articles published from 1996 to 2022 were retrieved from the Scopus database. Subsequently, these articles were analyzed to retrieve publication patterns, major collaborating nations, significant documents, recent trends, and future directions. A comprehensive introduction to QC is also included to facilitate a better grasp of this field for a wide range of readers. The findings of this study show that China is the leading nation in developing QC through material science, closely followed by the United States and India. Moreover, the study indicates significant areas of QC where extensive work is being done from the material science standpoint through keyword and significant document analysis. Hence, the outcomes of this article can be valuable for researchers, newcomers, technology managers, and policymakers interested in the future of QC. [ABSTRACT FROM AUTHOR]

In the present optical fog/cloud computing environment, optical line terminals and optical network units are used as the most promising optical fog devices (OFDs). The inherent characteristics of fog computing provide certain granted privileges to the attacker to hack devices and make them malicious. Also, existing security solutions generate false alarms that affect the performance of the underlying network. In this paper, a secure framework is proposed that not only predicts the malicious OFDs but also reduces false alarms. Hidden Markov model and intrusion detection system are used to detect the malicious one by computing the probability of shifting (POS) and then shift it to the virtual honeypot which is kept hidden by deploying it at the optical fog layer. In addition, it also reduces the generation of false alarm and logs all malicious activities for further analysis. In the experiment section, Python is used to validate the proposed framework. Further, HMM is simulated and tested in the MATLAB to reduce the false alarm rate. Results show that the proposed framework effectively reduces the false alarms and detects the malicious one and then shifts it onto the virtual honeypot efficiently. [ABSTRACT FROM AUTHOR]