Publication | Closed Access
IoTCMal: Towards A Hybrid IoT Honeypot for Capturing and Analyzing Malware
45
Citations
9
References
2020
Year
Unknown Venue
EngineeringInformation SecurityCommand InjectionIot ProtocolIot SecurityIot SystemSmart SystemsInternet Of Things SecurityMalware BinariesIot ChallengeInternet Of ThingsSecurity DiagnosticsNetworked Computer SystemsComputer ScienceAnalyzing MalwareData SecurityMalware FamiliesBotnet DetectionMalware AnalysisIot Forensics
Nowadays, the emerging Internet-of-Things (IoT) emphasize the need for the security of network-connected devices. Additionally, there are two types of services in IoT devices that are easily exploited by attackers, weak authentication services (e.g., SSH/Telnet) and exploited services using command injection. Based on this observation, we propose IoTCMal, a hybrid IoT honeypot framework for capturing more comprehensive malicious samples aiming at IoT devices. The key novelty of IoTC-MAL is three-fold: (i) it provides a high-interactive component with common vulnerable service in real IoT device by utilizing traffic forwarding technique; (ii) it also contains a low-interactive component with Telnet/SSH service by running in virtual environment. (iii) Distinct from traditional low-interactive IoT honeypots[1], which only analyze family categories of malicious samples, IoTCMal primarily focuses on homology analysis of malicious samples. We deployed IoTCMal on 36 VPS <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> instances distributed in 13 cities of 6 countries. By analyzing the malware binaries captured from IoTCMal, we discover 8 malware families controlled by at least 11 groups of attackers, which mainly launched DDoS attacks and digital currency mining. Among them, about 60% of the captured malicious samples ran in ARM or MIPs architectures, which are widely used in IoT devices.
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