Big data network security defense mode of deep learning algorithm

Author:

Yu Yingle1

Affiliation:

1. Tandon School of Engineering, New York University , Brooklyn 11201 , New York , USA

Abstract

Abstract With the rapid development and progress of big data technology, people can already use big data to judge the transmission and distribution of network information and make better decisions in time, but it also faces major network threats such as Trojan horses and viruses. Traditional network security functions generally wait until the network power is turned on to a certain extent before starting, and it is difficult to ensure the security of big data networks. To protect the network security of big data and improve its ability to defend against attacks, this article introduces the deep learning algorithm into the research of big data network security defense mode. The test results show that the introduction of deep learning algorithms into the research of network security model can enhance the security defense capability of the network by 5.12%, proactively detect, and kill cyber attacks that can pose threats. At the same time, the security defense mode will evaluate the network security of big data and analyze potential network security risks in detail, which will prevent risks before they occur and effectively protect the network security in the context of big data.

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Network Security Test Evaluation Model of Automobile Digital Key;Proceedings of the 8th International Conference on Cyber Security and Information Engineering;2023-09-22

2. Challenges and Solutions for Network Security in the Information Age;2023 International Seminar on Computer Science and Engineering Technology (SCSET);2023-04

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