Virtual Private Network Essay

Virtual Private Network
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Virtual Private Network
With the increase in internet adversaries, adopting the Virtual Private Network helps the user by masking their IP address, thus preventing unauthorized users from obtaining users’ location or access to data. By providing endpoint configurations, it has resulted in user satisfaction. Virtual private network software creates an encrypted and safe internet online connection; however, there are increased vulnerabilities that seek to jeopardize the security and integrity of the VPN services and its encryption level. With the increased use of Virtual private networks today, the VPN’s security is beginning to be threatened (Daud, 2018).
methods of improving the performance based on VPN technology and level of encryption
Herein are some of the methods that can be adopted to improve the performance of the VPN. Firstly, use of realistic bandwidth quotas in this case, for remote usage, their sessions should be supervised to ensure that they do not use excess bandwidth and, therefore, ensure that the termination capacity is sufficiently overstretched to meet demand. Secondly, to increase encryption level, split tunnels VPNs ensure internet traffic (Daud, 2018). That is not for the user domain; it is redirected to the local ISP, thus reducing strain. Adopting inbuilt protection ensures that the VPN is secured; using the software as a service boosts the VPS’s performance and ensures that its everyday applications are efficient. Thirdly, by using geographically disperse employee pockets, thus distributing their intranet network to different sources to guarantee safety, it is easy to adopt analytic tools by using the network visibility tools, which allows the team to be more accurate when diagnosing the problem (Guo, 2020).
Methods of improving the stability of configuration, location, VPN software version, and underlying OS
There is a different method of improving the configuration of the virtual private network and its underlying operating systems. Firstly, by using a wired connection. A wireless connection depends on the signal strength and location; however, a wired connection is less likely to sufferer any forms of interference. This is more stable with minimal interference that might cause it to slow down. Additionally, it is advisable to restart the router as frequently as possible as this restores the stability of the router or internet network. Moreover, it refreshes the connection, thus improves the better signal reception and is configuration (Wang, 2017).
Thirdly, by adopting an antivirus software that does conflict with the VPN software. While the two software seeks to perform a similar goal; thus, many end up conflicting, reducing its stability and increasing buffers, and reducing the experience when using the service. Another method to improve the stability and configuration a VPN software is by changing the server’s serve o one closer to the user’s location to bypass congestion due to low latency (Banford, 2018). Another way to improve the VPN Software’s configuration and stability is by using advanced options such as overriding the DNS with third-party DNS servers to improve its privacy. Additionally, the configuration can be improved by the congestion or network hop location through a traceroute. Adopting these best practices will improve the security mitigation systems while protecting the VPN from attacks and its associated technology and building the resilience, stability, and safety of the infrastructure.

References
Banford, J. E., Blevins, M. R., & Price, D. (2018). U.S. Patent No. 9,886,263. Washington, DC: U.S. Patent and Trademark Office.
Daud, F. A., Ab Rahman, R., Kassim, M., & Idris, A. (2018, October). Performance of Encryption Techniques Using Dynamic Virtual Protocol Network Technology. In 2018 IEEE 8th International Conference on System Engineering and Technology (ICSET) (pp. 29-34). IEEE.
Guo, L., Wu, Q., Liu, S., Duan, M., Li, H., & Sun, J. (2020). Deep learning-based real-time VPN encrypted traffic identification methods. Journal of Real-Time Image Processing, 17(1), 103-114.
Wang, W., Zhu, M., Wang, J., Zeng, X., & Yang, Z. (2017, July). End-to-end encrypted traffic classification with one-dimensional convolution neural networks. In 2017 IEEE International Conference on Intelligence and Security Informatics (ISI) (pp. 43-48). IEEE.

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