TY - GEN
T1 - Countering cross-technology jamming attack
AU - Chi, Zicheng
AU - Li, Yan
AU - Liu, Xin
AU - Wang, Wei
AU - Yao, Yao
AU - Zhu, Ting
AU - Zhang, Yanchao
N1 - Funding Information:
This work is supported in part by NSF grants CNS-1824491, CNS-1824355, CNS-1652669, CNS-1933069, CNS-1619251 and CNS-1514381. We also thank anonymous reviewers for their valuable comments.
Publisher Copyright:
© 2020 ACM.
PY - 2020/7/8
Y1 - 2020/7/8
N2 - Internet-of-things (IoT) devices are sharing the radio frequency band (e.g., 2.4 GHz ISM band). The exponentially increasing number of IoT devices introduces potential security issues at the gateway in IoT networks. In this paper, we introduce a set of new attacks through concealed jamming-an adversary pretends to be (or compromises) a legitimate WiFi device, then sends out WiFi packets to prevent ZigBee devices' communication or collide with ZigBee's packets. By doing this, concealed jamming has the potential to severely delay the reception of ZigBee packets that may contain important information (e.g., critical health data from wearables, fire alarms, and intrusion alarms). To defend against these attacks, we designed a novel ZigBee data extraction technique that can recover ZigBee data from the ZigBee packets that were collided with WiFi packets. We extensively evaluated our design in different real-world settings. The results show that ZigBee devices (protected by our proposed methods) achieve similar performance as those that are not under the concealed jamming attack. Moreover, compared with unprotected devices, their throughput is more than 15 times higher than the unprotected one that is under concealed jamming attacks.
AB - Internet-of-things (IoT) devices are sharing the radio frequency band (e.g., 2.4 GHz ISM band). The exponentially increasing number of IoT devices introduces potential security issues at the gateway in IoT networks. In this paper, we introduce a set of new attacks through concealed jamming-an adversary pretends to be (or compromises) a legitimate WiFi device, then sends out WiFi packets to prevent ZigBee devices' communication or collide with ZigBee's packets. By doing this, concealed jamming has the potential to severely delay the reception of ZigBee packets that may contain important information (e.g., critical health data from wearables, fire alarms, and intrusion alarms). To defend against these attacks, we designed a novel ZigBee data extraction technique that can recover ZigBee data from the ZigBee packets that were collided with WiFi packets. We extensively evaluated our design in different real-world settings. The results show that ZigBee devices (protected by our proposed methods) achieve similar performance as those that are not under the concealed jamming attack. Moreover, compared with unprotected devices, their throughput is more than 15 times higher than the unprotected one that is under concealed jamming attacks.
KW - denial of service attack
KW - security
KW - wireless networks
UR - http://www.scopus.com/inward/record.url?scp=85091989060&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091989060&partnerID=8YFLogxK
U2 - 10.1145/3395351.3399367
DO - 10.1145/3395351.3399367
M3 - Conference contribution
AN - SCOPUS:85091989060
T3 - WiSec 2020 - Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks
SP - 99
EP - 110
BT - WiSec 2020 - Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks
PB - Association for Computing Machinery
T2 - 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2020
Y2 - 8 July 2020 through 10 July 2020
ER -