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

<p>With the progress of the times, big data will follow the development of the Internet and show a broader development space. But the characteristics of big data itself also make it more difficult to solve the problems of network attacks and theft of sensitive information. Therefore, it is more important to conduct in-depth research on network information security in many fields in the context of big data. In this paper, we build a DFN-Big Data network model based on deep feed-forward network as the algorithm, and conduct an in-depth study on network information security. The calculation results show that, among several leakage methods of personal information, the leakage caused by hacking is the most dangerous and unpredictable. The percentage of cyber incidents caused by hacking is 43%. The network security problem caused by excessive collection of personal user information is also very serious, and its percentage is 34%. Establishing a sound legal regulatory system can effectively reduce the occurrence of network information leakage. Compared with other security technology solutions, a sound legal regulatory system increases network information security by 67%. Information protection technology improves network information security by 87%.</p>
</abstract>

With the progress of the times, big data will follow the development of the Internet and show a broader development space. But the characteristics of big data itself also make it more difficult to solve the problems of network attacks and theft of sensitive information. Therefore, it is more important to conduct in-depth research on network information security in many fields in the context of big data. In this paper, we build a DFN-Big Data network model based on deep feed-forward network as the algorithm, and conduct an in-depth study on network information security. The calculation results show that, among several leakage methods of personal information, the leakage caused by hacking is the most dangerous and unpredictable. The percentage of cyber incidents caused by hacking is 43%. The network security problem caused by excessive collection of personal user information is also very serious, and its percentage is 34%. Establishing a sound legal regulatory system can effectively reduce the occurrence of network information leakage. Compared with other security technology solutions, a sound legal regulatory system increases network information security by 67%. Information protection technology improves network information security by 87%.

Analysis of network information security issues under the background of big data

Applied Mathematics and Nonlinear Sciences

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

{"article-title":"Analysis of network information security issues under the background of big data"}

With the progress of the times, big data will follow the development of the Internet and show a broader development space. But the characteristics of big data...

Analysis of network information security issues under the background of big data

Online veröffentlicht: 10. März 2023

Seitenbereich: 2835 - 2848

Eingereicht: 15. Jan. 2022

Akzeptiert: 04. Juli 2022

DOI: https://doi.org/10.2478/amns.2023.1.00004

Schlüsselwörter
Big data, DFN algorithm, Big data network model, Information security, Information protection technology

© 2023 Xuezhi Zhao et al., published by Sciendo

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

Analysis of network information security issues under the background of big data

Online veröffentlicht: 10. März 2023

Seitenbereich: 2835 - 2848

Eingereicht: 15. Jan. 2022

Akzeptiert: 04. Juli 2022

DOI: https://doi.org/10.2478/amns.2023.1.00004

SchlüsselwörterBig data, DFN algorithm, Big data network model, Information security, Information protection technology

© 2023 Xuezhi Zhao et al., published by Sciendo

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

Schlüsselwörter
Big data, DFN algorithm, Big data network model, Information security, Information protection technology