基于深度学习的智慧校园勒索病毒防御架构设计  

Design of a deep learning-based ransomware defense architecture for smart campuses

作　　者：朱朝阳 朱晓 朱磊 许杏 Zhu Chaoyang;Zhu Xiao;Zhu Lei;Xu Xing(Information Network Center,Guangxi University,Nanning 530004,China;School of Electronic Information,Guangxi Vocational and Technical Institute of Industry,Nanning 530001,China;School of Information Technology,Guangxi Police College,Nanning 530028,China)

机构地区：[1]广西大学信息网络中心,广西南宁530004 [2]广西工业职业技术学院电子信息学院,广西南宁530001 [3]广西警察学院信息技术学院,广西南宁530028

出　　处：《网络安全与数据治理》2024年第8期22-27,共6页CYBER SECURITY AND DATA GOVERNANCE

基　　金：中国高校产学研创新基金(2022IT214);2023年广西教育厅中青年提升科研项目(2023KY1318)。

摘　　要：智慧校园建设是现代高校信息化发展的必然趋势,然而,网络安全问题,尤其是勒索病毒攻击,对智慧校园的正常运作构成了严重威胁。传统的安全防护手段难以应对不断演变的勒索病毒,因此,提出一种基于深度学习的自适应勒索病毒防御架构(Adaptive Ransomware Defense Architecture Based on Deep Learning, ARDAD),旨在提升智慧校园云平台的勒索病毒防御能力。ARDAD通过整合多层次防护、行为分析和动态响应等安全机制,实时监控网络、文件和服务器,并利用深度学习技术识别和拦截勒索病毒,实现对智慧校园云平台的安全防护。The construction of smart campuses is an inevitable trend in the informatization development of modern universities.However,cybersecurity issues,especially ransomware attacks,pose a serious threat to the normal operation of smart campuses.Traditional security measures struggle to cope with the constantly evolving ransomware,thus this paper proposes an Adaptive Ransomware Defense Architecture based on Deep Learning(ARDAD)to enhance the ransomware defense capabilities of smart campus cloud platforms.ARDAD integrates security mechanisms such as multi-level protection,behavior analysis,and dynamic response,monitoring networks,files,and servers in real-time.It utilizes deep learning techniques to identify and intercept ransomware,ultimately achieving security protection for smart campus cloud platforms.

关 键 词：智慧校园 勒索病毒 深度学习 自适应安全架构 网络安全 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]