CAJ | 학술논문

针对不良网络内容对数字教育的使用者尤其是青少年用户的威胁,提出了不良网络内容的识别与阻断系统模型,并研究了其中3项关键技术,包括高速网络流量数据的获取与还原技术、不良网络内容快速识别技术以及不良网络内容的自动阻断技术。在此基础上设计开发出一套不良网络内容识别与阻断系统,在Cernet西北网中心进行的验证与测试中,不良网络内容快速识别技术的准确率达到98.1%,不良网络内容自动阻断技术的成功率达到97.3%,为保障校园网的绿色安全提供了可靠的技术保证。
침대불량망락내용대수자교육적사용자우기시청소년용호적위협,제출료불량망락내용적식별여조단계통모형,병연구료기중3항관건기술,포괄고속망락류량수거적획취여환원기술、불량망락내용쾌속식별기술이급불량망락내용적자동조단기술。재차기출상설계개발출일투불량망락내용식별여조단계통,재Cernet서북망중심진행적험증여측시중,불량망락내용쾌속식별기술적준학솔체도98.1%,불량망락내용자동조단기술적성공솔체도97.3%,위보장교완망적록색안전제공료가고적기술보증。
To solve the problem of harmful information spreading for e-Learning users, it is proposed a system frameworkfor harmful network content detection and blocking, and three key methods are studied, including capturing and recovering method for large scale network traffic data, harmful content detection method and automatic blocking method for harmful content visiting. Based on these methods, a system is developed and tested in the real environment of northwest center of Cemet. The results show that the accuracy rate of harmful content detection method is 98.1%, the success rate of blocking method for harmful content visiting is 97.3%, and the system could detect and block the harmful information spreading effectively.