基于卷积神经网络的安全防御模式研究

云计算、大数据、5G通信等技术的快速发展，有力的促进了计算机网络在多个领域的普及和使用，人们已经进入到了“互联网+”时代，实现了工作、生活和学习的数字化、智能化和共享化。计算机网络在为人们提供各种便利服务的同时也面临着许多的安全威胁，比如木马、病毒等，不法分子攻击网络数据中心，破坏用户服务终端及服务器，为人们带来严重的威胁。网络安全学者或企业机构也提出了许多安全防御技术，比如入侵检测技术、深度包过滤技术、防火墙技术、数据加密技术等，一定程度上提高了网络安全防御的能力，但是随着互联网数据流量的增多，需要引入更加先进的人工智能技术，以便能够快速的采集、分析网络数据流，确定数据流中是否存在病毒或木马，以便及时的对其进行查杀，进一步提高网络安全防御的主动性、积极性

Research on security defense mode based on convolutional neural network

The rapid development of cloud computing, big data, 5G communication and other technologies has effectively promoted the popularization and use of computer networks in many fields. People have entered the "Internet +" era and realized the digitization of work, life and learning , Intelligent and shared. While providing various convenient services to people, computer networks are also facing many security threats, such as Trojan horses, viruses, etc. Criminals attack network data centers, destroy user service terminals and servers, and pose a serious threat to people. Network security scholars or corporate organizations have also proposed many security defense technologies, such as intrusion detection technology, deep packet filtering technology, firewall technology, and data encryption technology, which have improved the ability of network security defense to a certain extent, but with the increase in Internet data traffic Increased, it is necessary to introduce more advanced artificial intelligence technology in order to be able to quickly collect and analyze network data streams to determine whether there are viruses or Trojans in the data stream, so as to timely kill them, and further improve the initiative of network security defense