<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Inadequate network security defense measures threaten the information and property security of the state and the public, and how to safeguard network security is of vital practical significance. This paper proposes a dynamic security threat assessment model and a robust optimal control strategy to improve the efficiency of detecting network vulnerabilities and the accuracy of detecting network threats in a cloud computing environment. It also protects the privacy of the user's identity through a multi-factor continuous authentication method, encrypts and protects the user's data using a homomorphic encryption algorithm, and strengthens the ability of computers to resist intrusion. Three case studies are conducted to verify the effectiveness of the proposed technical approach: dynamic assessment of security threats, control policy, authentication, and network encryption. The results show that in the network vulnerability control policy and authentication case study, when adding the control policy <italic>T<sub>k</sub></italic> = 40, the percentage of network normal nodes, malicious nodes and restorer nodes are 0.98, 0.02, and 0.009, respectively, and the encrypted plaintext ASCII value is distributed in [0,60] in an unordered manner, and the network is in a very desirable security state. Real-time accurate assessments of network security state can be provided by cloud computing-based network security vulnerability and encryption technology.</p>
</abstract>

Inadequate network security defense measures threaten the information and property security of the state and the public, and how to safeguard network security is of vital practical significance. This paper proposes a dynamic security threat assessment model and a robust optimal control strategy to improve the efficiency of detecting network vulnerabilities and the accuracy of detecting network threats in a cloud computing environment. It also protects the privacy of the user's identity through a multi-factor continuous authentication method, encrypts and protects the user's data using a homomorphic encryption algorithm, and strengthens the ability of computers to resist intrusion. Three case studies are conducted to verify the effectiveness of the proposed technical approach: dynamic assessment of security threats, control policy, authentication, and network encryption. The results show that in the network vulnerability control policy and authentication case study, when adding the control policy Tk = 40, the percentage of network normal nodes, malicious nodes and restorer nodes are 0.98, 0.02, and 0.009, respectively, and the encrypted plaintext ASCII value is distributed in [0,60] in an unordered manner, and the network is in a very desirable security state. Real-time accurate assessments of network security state can be provided by cloud computing-based network security vulnerability and encryption technology.

Research on Computer Network Security Vulnerabilities and Encryption Technology in Cloud Computing Environment

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Inadequate network security defense measures threaten the information and property security of the state and the public, and how to safeguard network security...

Research on Computer Network Security Vulnerabilities and Encryption Technology in Cloud Computing Environment

Pubblicato online: 31 gen 2024

Pagine: -

Ricevuto: 18 dic 2023

Accettato: 23 dic 2023

DOI: https://doi.org/10.2478/amns-2024-0171

Parole chiave
Dynamic assessment model, Optimal control policy, Continuous authentication, Homomorphic encryption, Network security vulnerability

© 2024 Peng Peng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Computer Network Security Vulnerabilities and Encryption Technology in Cloud Computing Environment

Pubblicato online: 31 gen 2024

Pagine: -

Ricevuto: 18 dic 2023

Accettato: 23 dic 2023

DOI: https://doi.org/10.2478/amns-2024-0171

Parole chiaveDynamic assessment model, Optimal control policy, Continuous authentication, Homomorphic encryption, Network security vulnerability

© 2024 Peng Peng, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Dynamic assessment model, Optimal control policy, Continuous authentication, Homomorphic encryption, Network security vulnerability