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