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The importance of network security has increased with the emergence of networked systems in contemporary computing, making it an essential aspect of protecting digital assets and safeguarding against cyber threats. The current security mechanisms, which rely on cryptographic keys, may be susceptible to a number of attacks, such as media access control (MAC) spoofing, which might provide unauthorized users access to network resources. This study introduces a new approach, namely a zero-trust security framework with quantum fingerprinting for devices accessing a network, that utilizes quantum technology to protect networks from security threats and intruders. The proposed architecture relies on quantum fingerprinting to authenticate devices trying to access the network, and it is built on the zero-trust security concept. The framework is intended to offer a thorough, multi-layered approach to network security that may change in response to evolving security risks and specifications. By protecting against MAC spoofing and other types of device impersonation, the adoption of quantum fingerprinting adds another degree of protection. The proposed framework may be used to construct a reliable and scalable network security solution in different network environments. [ABSTRACT FROM AUTHOR]

The ubiquitous cloud computing services provide a new paradigm to the work-from-home environment adopted by the enterprise in the unprecedented crisis of the COVID-19 outbreak. However, the change in work culture would also increase the chances of the cybersecurity attack, MAC spoofing attack, and DDoS/DoS attack due to the divergent incoming traffic from the untrusted network for accessing the enterprise's resources. Networks are usually unable to detect spoofing if the intruder already forges the host's MAC address. However, the techniques used in the existing researches mistakenly classify the malicious host as the legitimate one. This paper proposes a novel access control policy based on a zero-trust network by explicitly restricting the incoming network traffic to substantiate MAC spoofing attacks in the software-defined network (SDN) paradigm of cloud computing. The multiplicative increase and additive decrease algorithm helps to detect the advanced MAC spoofing attack before penetrating the SDN-based cloud resources. Based on the proposed approach, a dynamic threshold is assigned to the incoming port number. The self-learning feature of the threshold stamping helps to rectify a legitimate user's traffic before classifying it to the attacker. Finally, the mathematical and experimental results exhibit high accuracy and detection rate than the existing methodologies. The novelty of this approach strengthens the security of the SDN paradigm of cloud resources by redefining conventional access control policy. [ABSTRACT FROM AUTHOR]

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