SCAFFISD: A Scalable Framework for Fine-Grained Identification and Security Detection of Wireless Routers
Title | SCAFFISD: A Scalable Framework for Fine-Grained Identification and Security Detection of Wireless Routers |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Zhu, Fangzhou, Liu, Liang, Meng, Weizhi, Lv, Ting, Hu, Simin, Ye, Renjun |
Conference Name | 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) |
Keywords | access point, Communication system security, Device Identification, Object recognition, performance evaluation, Predictive Metrics, privacy, Prototypes, pubcrawl, Resiliency, router, Router Systems Security, Scalable Security, security, Vulnerability, wireless network, wireless networks |
Abstract | The security of wireless network devices has received widespread attention, but most existing schemes cannot achieve fine-grained device identification. In practice, the security vulnerabilities of a device are heavily depending on its model and firmware version. Motivated by this issue, we propose a universal, extensible and device-independent framework called SCAFFISD, which can provide fine-grained identification of wireless routers. It can generate access rules to extract effective information from the router admin page automatically and perform quick scans for known device vulnerabilities. Meanwhile, SCAFFISD can identify rogue access points (APs) in combination with existing detection methods, with the purpose of performing a comprehensive security assessment of wireless networks. We implement the prototype of SCAFFISD and verify its effectiveness through security scans of actual products. |
DOI | 10.1109/TrustCom50675.2020.00160 |
Citation Key | zhu_scaffisd_2020 |