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

• Autores: Xuezhi Zhao, Liangcheng Lin, Tao Guo, Jinbao Du, Baozhan Feng
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 2835-2848
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

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