TY - GEN
T1 - Collusion attacks in Internet of Things
T2 - 12th IEEE Sensors Applications Symposium, SAS 2017
AU - Yaseen, Qussai
AU - Jararweh, Yaser
AU - Al-Ayyoub, Mahmoud
AU - Al Dwairi, Monther
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/4/6
Y1 - 2017/4/6
N2 - This paper discusses the problem of collusion attacks in Internet of Things (IoT) environments and how mobility of IoT devices increases the difficulty of detecting such types of attacks. It demonstrates how approaches used in detecting collusion attacks in WSNs are not applicable in IoT environments. To this end, the paper introduces a model based on the Fog Computing infrastructure to keep track of IoT devices and detect collusion attackers. The model uses fog computing layer for real-time monitoring and detection of collusion attacks in IoT environments. Moreover, the model uses a software defined system layer to add a degree of flexibility for configuring Fog nodes in order to enable them to detect various types of collusion attacks. Furthermore, the paper highlights the possible overhead on Fog nodes and network when applying the proposed model, and claims that the Fog layer infrastructure can provide the required resources for the scalability of the model.
AB - This paper discusses the problem of collusion attacks in Internet of Things (IoT) environments and how mobility of IoT devices increases the difficulty of detecting such types of attacks. It demonstrates how approaches used in detecting collusion attacks in WSNs are not applicable in IoT environments. To this end, the paper introduces a model based on the Fog Computing infrastructure to keep track of IoT devices and detect collusion attackers. The model uses fog computing layer for real-time monitoring and detection of collusion attacks in IoT environments. Moreover, the model uses a software defined system layer to add a degree of flexibility for configuring Fog nodes in order to enable them to detect various types of collusion attacks. Furthermore, the paper highlights the possible overhead on Fog nodes and network when applying the proposed model, and claims that the Fog layer infrastructure can provide the required resources for the scalability of the model.
UR - https://www.scopus.com/pages/publications/85018340954
U2 - 10.1109/SAS.2017.7894031
DO - 10.1109/SAS.2017.7894031
M3 - Conference contribution
AN - SCOPUS:85018340954
T3 - SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings
BT - SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 13 March 2017 through 15 March 2017
ER -