TY - JOUR
T1 - Characterizing DNS Behaviors of Internet of Things in Edge Networks
AU - Xu, Kuai
AU - Wang, Feng
AU - Jimenez, Sergio
AU - Lamontagne, Andrew
AU - Cummings, John
AU - Hoikka, Mitchell
N1 - Funding Information:
Manuscript received February 27, 2020; revised April 25, 2020; accepted May 19, 2020. Date of publication June 1, 2020; date of current version September 15, 2020. This work was supported in part by NSF under Grant 1816995. (Corresponding author: Kuai Xu.) The authors are with the School of Mathematical and Natural Sciences, Arizona State University, Glendale, AZ 85306 USA (e-mail: kuai.xu@asu.edu). Digital Object Identifier 10.1109/JIOT.2020.2999327
Publisher Copyright:
© 2014 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - The recent spate of cyber attacks and security threats toward Internet-of-Things (IoT) systems in smart cities, smart homes, and industry 4.0 calls for effective techniques to understand if, when, who, what IoT systems are exploited and compromised by Internet attackers. Toward this end, this article attempts to study DNS behavioral patterns of IoT systems in edge networks as a first step of characterizing their communication patterns and their interactions with IoT users, cloud servers, and other IoT or non-IoT devices in the same edge networks. Specifically, we analyze the temporal-spatial patterns of DNS behaviors of a variety of IoT systems in two dozens of edge networks and develop a simple yet effective Bloom filter mechanism for detecting anomalous traffic patterns based on unusual DNS queries and answers. To the best of our knowledge, this article is the first effort to systematically measure and monitor IoT network traffic from a DNS perspective for providing the security of heterogeneous IoT systems and ensuring IoT user privacy.
AB - The recent spate of cyber attacks and security threats toward Internet-of-Things (IoT) systems in smart cities, smart homes, and industry 4.0 calls for effective techniques to understand if, when, who, what IoT systems are exploited and compromised by Internet attackers. Toward this end, this article attempts to study DNS behavioral patterns of IoT systems in edge networks as a first step of characterizing their communication patterns and their interactions with IoT users, cloud servers, and other IoT or non-IoT devices in the same edge networks. Specifically, we analyze the temporal-spatial patterns of DNS behaviors of a variety of IoT systems in two dozens of edge networks and develop a simple yet effective Bloom filter mechanism for detecting anomalous traffic patterns based on unusual DNS queries and answers. To the best of our knowledge, this article is the first effort to systematically measure and monitor IoT network traffic from a DNS perspective for providing the security of heterogeneous IoT systems and ensuring IoT user privacy.
KW - Internet-of-Things (IoT) network traffic
KW - security and privacy
KW - smart cities
KW - smart homes
UR - http://www.scopus.com/inward/record.url?scp=85092199754&partnerID=8YFLogxK
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U2 - 10.1109/JIOT.2020.2999327
DO - 10.1109/JIOT.2020.2999327
M3 - Article
AN - SCOPUS:85092199754
SN - 2327-4662
VL - 7
SP - 7991
EP - 7998
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 9
M1 - 9105052
ER -