A Security Reputation Model for IoT Health Data Using S-AlexNet and Dynamic Game Theory in Cloud Computing Environment

Abstract

With the rapid development of cloud computing, users are exposed to increasingly serious security threats such as data leakage and privacy exposure when using cloud platform services. Problems in data security, such as inaccurate screening of indicators, lack of scientific validation of reputation evaluation results are also existed. In order to solve the problems, based on cloud environment, a security reputation model using S-AlexNet convolutional neural network and dynamic game theory (SCNN-DGT) is proposed. And it is used to protect the privacy of health data in Internet of Things (IoT). Firstly, the text information of user health data is pre-classified by using S-AlexNet convolutional neural network. Then, a recommendation incentive strategy based on dynamic game theory is proposed. So that the reputation model of user health data security is built, and the evaluation system of the model is established. Finally, an experimental study is carried out to verify the validity of the model and the model index screening. It is shown by experimental results that the model can solve the problems of low reliability of health data screening index, and low accuracy of credit distinction in cloud environment. Therefore, the reliability of mobile terminals is improved, and data security and privacy protection of mobile cloud services are strengthened effectively. INDEX TERMS Health data privacy protection, cloud computing, S-AlexNet convolutional neural network, dynamic game theory, big data security reputation model, recommendation incentive strategy, Internet of Things (IoT).

Enhancing Privacy and Data Security across Healthcare Applications Using Blockchain and Distributed Ledger Concepts

“…S-Alex convolution neural network and dynamic game theory (SCNN-DGT) designed by Kong et al [24] are used in the IoT-cloud computing environment for health data management. The initial step is obtaining the information of the healthcare and classifying them in Alex's net convolutional network.…”

Security Measurement in Industrial IoT with Cloud Computing Perspective: Taxonomy, Issues, and Future Directions

“…In [28], the authors trying to solve some security issues regarding errors of screening indicators lack validation Scientific Programming reputation scientifically. Based on these issues, a well-reputed security model is presented using S-Alex Net convolution neural network and dynamic game theory called SCNN-DGT.…”

“…Overviews Advantages Techniques Years [5] e SSG is proposed for cloud security; the defender and attackers are compared by applying the model; the utility function, best strategy, and payoff are analyzed in the game model e information on the attacker's behavior is collected by active and passive stages of the SSG; the efficient utility function is achieved by this model; the defender availability and cost are maximum and minimum, respectively e security Stackelberg model, active and passive stages, utility function modeling, natural roles, and defense strategy 2018 [27] is model works on a pay-per-use basis; doubtful traffic enters at one side of the model by applying different policies by the model components; a clean output data is provided to the clients e model not only improves the security but also the flexibility, control, effectiveness, and performance as well e IDPS and POC are used in this model 2016 [28] is proposed work aims to manage and secure cloud data; incorrect screening and privacy of the cloud data is encountered e outcomes of the experiments show that the proposed model solves the problem of low accuracy and reliability of the data in the cloud environment e neural network model called S-Alex Net and game-theoretical approach SCNN-DGT is discussed from chaotic to individual self-organizing in a random search process.…”

Energy Aware Clustered Blockchain Data for IoT: An End-to-End Lightweight Secure & Enroute Filtering Approach

“…Based on the threat level evaluated for nodes, actions are taken to improve network energy efficiency. Limitation: Coalitional game theory optimization require high processing time and each time running this algorithm introduces more overhead.In paper [22] proposed a security model that uses S-AlexNet convolutional neural network and dynamic game theory which is referred as shortly SCNN-DGT. The purpose of this theory is to classify user's health data.…”

“…𝑊 𝑖𝑗 𝑙 (22) Where 𝑊 𝑖𝑗 𝑘 represent the sum of weights connected between node i and node j with the length of l, n represent the amount of nodes present in the network and 𝛽 represent the factor of attenuation that satisfies the condition of 0 < 𝛽 < 1/ℷ 𝑀𝑎𝑥 . In Katz centrality, if the node has large value then it has more importance.…”