TY - GEN
T1 - IoT Eye An Efficient System for Dynamic IoT Devices Auto-discovery on Organization Level
AU - Shen, Jie
AU - Li, YIng
AU - Li, Bo
AU - Chen, Hanteng
AU - Li, Jianxin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/20
Y1 - 2017/7/20
N2 - Internet of Things (IoT) serves not only as an essential part of the new generation information technology but as an important development stage in the information era. IoT devices such as unmanned aerial vehicles, robots and wearable equipments have been widely used in recent years. For most organizations' inner networks, innumerable dynamic connections with Internet accessible IoT devices occur at many parts all the time. It is usually these temporal links that arise potential threats to the security of the whole intranet. In this paper, we propose a new system named IoT Eye, which automatically discovers the IoT devices in real time. The IoT Eye detects all the potential IoT target hosts using an innovative two-stage architecture: (1) Scanning suspicious IP segments with stateless TCP SYN scan model and zero copy TCP stack; (2) Identifying each IoT device on various protocols using PI-AC, which is a novel high-performance multi-pattern matching algorithm. The preceding model ensures the IoT Eye searching each newly connected device out in rather small time delay, which minimizes the missing and wrong detection rates. Related intelligence on the active IoT devices linked with the organization's intranets are of great importance to the professionals. Since it can help them: (1) re-examine the borders of large intranets; (2) reduce non-essential device access; (3) fix security vulnerabilities timely.
AB - Internet of Things (IoT) serves not only as an essential part of the new generation information technology but as an important development stage in the information era. IoT devices such as unmanned aerial vehicles, robots and wearable equipments have been widely used in recent years. For most organizations' inner networks, innumerable dynamic connections with Internet accessible IoT devices occur at many parts all the time. It is usually these temporal links that arise potential threats to the security of the whole intranet. In this paper, we propose a new system named IoT Eye, which automatically discovers the IoT devices in real time. The IoT Eye detects all the potential IoT target hosts using an innovative two-stage architecture: (1) Scanning suspicious IP segments with stateless TCP SYN scan model and zero copy TCP stack; (2) Identifying each IoT device on various protocols using PI-AC, which is a novel high-performance multi-pattern matching algorithm. The preceding model ensures the IoT Eye searching each newly connected device out in rather small time delay, which minimizes the missing and wrong detection rates. Related intelligence on the active IoT devices linked with the organization's intranets are of great importance to the professionals. Since it can help them: (1) re-examine the borders of large intranets; (2) reduce non-essential device access; (3) fix security vulnerabilities timely.
KW - Internet of Things
KW - device discovering
KW - multiple pattern matching
UR - https://www.scopus.com/pages/publications/85028673004
U2 - 10.1109/CSCloud.2017.66
DO - 10.1109/CSCloud.2017.66
M3 - 会议稿件
AN - SCOPUS:85028673004
T3 - Proceedings - 4th IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2017 and 3rd IEEE International Conference of Scalable and Smart Cloud, SSC 2017
SP - 294
EP - 299
BT - Proceedings - 4th IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2017 and 3rd IEEE International Conference of Scalable and Smart Cloud, SSC 2017
A2 - Qiu, Meikang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2017 and 3rd IEEE International Conference of Scalable and Smart Cloud, SSC 2017
Y2 - 26 June 2017 through 28 June 2017
ER -