论文部分内容阅读
随着互联网的普及和发展,其已经在很多行业得到广泛使用,取得了显著的应用成效。互联网即为人们的工作、学习、生活提供了便捷支撑,同时也带来了潜在的安全威胁,造成互联网应用系统的安全风险非常大,非常容易产生不可估量的经济损失。同时,互联网运行项目的增多,数据量也急剧上升,因此传统的安全防御技术已经无法支撑当前互联网应用和操作需求,亟需采用先进的大数据技术,利用数据挖掘、模式识别从海量的网络数据中发掘潜在的病毒和木马信息,从而可以识别网络中的安全威胁造成的后果严重程度,进而启动深层次的防御系统,及时将安全威胁清除掉,保证网络正常运行。
With the popularity and development of the Internet, it has been widely used in many industries and achieved remarkable results. The Internet provides convenient support for people’s work, study and life as well as potential security threats. As a result, the security risk of Internet application systems is very large, and it is very easy to have incalculable economic losses. At the same time, the number of Internet operation projects has increased and the data volume has risen sharply. Therefore, the traditional security defense technology can no longer support the current Internet applications and operational needs. Therefore, it is urgent to adopt advanced big data technologies to utilize data mining and pattern recognition from massive network data In the discovery of potential virus and Trojan information, which can identify the network security threats caused by the severity of the consequences, and then start a deep defense system, timely removal of security threats to ensure the normal operation of the network.