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
朱朝阳 1朱晓 2朱磊 3许杏1
作者信息
- 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
- 折叠
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.
Abstract
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 Ran-somware Defense Architecture based on Deep Learning(ARDAD)to enhance the ransomware defense capabilities of smart cam-pus cloud platforms.ARDAD integrates security mechanisms such as multi-level protection,behavior analysis,and dynamic re-sponse,monitoring networks,files,and servers in real-time.It utilizes deep learning techniques to identify and intercept ransom-ware,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Key words
smart campus/ransomware/deep learning/adaptive security architecture/cybersecurity引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据