Measurement: Sensors (Jun 2023)
IOT monitoring membrane computing based on quantum inspiration to enhance security in cloud network
Abstract
Human computation is a technology inspired by nature. The majority of its computational sources are physiologically motivated computations. The existing calculation, on the other hand, uses some conventional techniques to complete the work. In the cloud, IaaS is one of the most basic services, offering a wide range of functions to a large number of customers. Modelling a number of species using P systems with different membrane structure types to predict the number of individuals is a major advantage of the proposed work. Even though it provides large number services (or) features to the user always it faces many numerous obstacles in Infrastructure service in cloud network, such as Authentication and Authorization, Data leakage and monitoring, End to End encryption, there is a risk of lack of security. Traditional encryption approaches also employ efficient methods to build cloud network security. It does, however, have some flaws in terms of IaaS. The work proposed membrane infrastructure based on the quantum inspiration. It will used to overcome such challenges. It is possible to minimize current constraints by employing this strategy. The paper proposes to employ basic distributed computational methods in an open and natural setting to provide membrane systems as a suitable framework for cloud environments for providing unique security among cloud users. They employ a framework for defending against intruder attacks. It is possible to address key cloud computing security difficulties by integrating Quantum Computing between the membrane environments with Cloud Computing technology. The proposed effectiveness and outcomes are monitored with the help of Internet of Things (IoT). This level introduces a revolutionary method to cloud security by incorporating quantum protocols into a membrane environment. The proposed SEDFA is the better method with all types of datasets and the Communication Cost by 5%, Encoding Time (ET) by 2 s, and Decoding Time (DT) by 0.5 s.
