The lack of security measures among the Internet of Things (IoT) devices and their persistent online connection give adversaries a prime opportunity to target them or even abuse them as intermediary targets in larger attacks such as distributed denial-of-service (DDoS) campaigns. In this paper, we analyze IoT malware and focus on the endpoints reachable on the public Internet, and play an essential part in the IoT malware ecosystem. Namely, we analyze endpoints acting as dropzones and their targets to gain insights into the underlying dynamics in this ecosystem, such as the affinity between the dropzones and their target IP addresses, and the different patterns among endpoints. Towards this goal, we reverse-engineer 2,423 IoT malware samples and extract strings from them to obtain IP addresses. We further gather information about these endpoints from public Internet-wide scanners, such as Shodan and Censys. For the masked IP addresses, we examine the Classless Inter-Domain Routing (CIDR) networks accumulating to more than 100 million (≈78.2% of total active public IPv4 addresses) endpoints.
|Title of host publication||Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, SEC 2019|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||6|
|State||Published - 7 Nov 2019|
|Event||4th ACM/IEEE Symposium on Edge Computing, SEC 2019 - Arlington, United States|
Duration: 7 Nov 2019 → 9 Nov 2019
|Name||Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, SEC 2019|
|Conference||4th ACM/IEEE Symposium on Edge Computing, SEC 2019|
|Period||7/11/19 → 9/11/19|
Bibliographical noteFunding Information:
This research was supported by Korea National Research Foundation under grant 2016K1A1A2912757 and a collaborative seed research grant from Cyber Florida.
© 2019 Association for Computing Machinery.
- Internet of Things