IoT Device Fingerprinting for Relieving Pressure in the Access Control

摘要：

　　As mass devices access to network in the era of the Internet of Things(IoT),the network access control becomes more impor-tant.Traditional authentication mechanisms are no longer suitable for IoT devices with limited physical and computational resources because of their complexity.This problem can be solved by the device fingerprinting,which can identify devices only by their traffic characteristics.However,existing device fingerprinting tech-nologies cannot accurately identify devices'type from the same manufacturer which equips these devices with similar hardwares and softwares.Therefore,we proposed the TSMC-SVM algorithm which introduced the cosine similarity into the SVM for improving the identification accuracy of these similar devices described above.Experiments illustrate that the average identification accuracy of the TSMC-SVM reaches 93.2%.

关键词： Device fingerprinting IoT Machine learning Access control

作者: Yubo Song Qiang Huang Junjie Yang Ming Fan Aiqun Hu Yu Jiang

作者单位: School of Cyber Science and Engineering,Southeast University Jiangsu,Nanjing,PRC

会议类型: 国际会议

会议名称: 2019国图灵大会(ACM Turing Celebration conference-China 2019 )

会议地点: 成都

会议语种:英文

页码: 875-882

在线出版日期: 2019-05-17（万方平台首次上网日期，不代表论文的发表时间）