首页|Recent Findings in Machine Learning Described by a Researcher from Arab American University (An Adaptive Security Framework for Internet of Things Networks Leve raging SDN and Machine Learning)
Recent Findings in Machine Learning Described by a Researcher from Arab American University (An Adaptive Security Framework for Internet of Things Networks Leve raging SDN and Machine Learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligen ce have been presented. According to news reporting from Arab American Universit y by NewsRx journalists, research stated, “The Internet of Things (IoT) is expan ding rapidly with billions of connected devices worldwide, necessitating robust security solutions to protect these systems.” The news correspondents obtained a quote from the research from Arab American Un iversity: “This paper proposes a comprehensive and adaptive security framework c alled Enhanced Secure Channel Authentication using random forests and software-d efined networking (SCAFFOLD), tailored for IoT environments. The framework estab lishes secure communication channels between IoT nodes using software-defined ne tworking (SDN) and machine learning techniques. The key components include encry pted channels using session keys, continuous traffic monitoring by the SDN contr oller, ensemble machine-learning for attack detection, precision mitigation via SDN reconfiguration, and periodic reauthentication for freshness. A mathematical model formally defines the protocol.”
Arab American UniversityCybersecurityCyborgsEmerging TechnologiesMachine LearningSoftware
NETL
NSTL
