Automatic Analysis Architecture of IoT Malware Samples

• Main Authors: Javier Carrillo-Mondejar, Juan Manuel Castelo Gomez, Carlos Núñez-Gómez, Jose Roldán Gómez, José Luis Martínez
• Format: Article
• Language: English
• Published: Hindawi-Wiley 2020-01-01
• Series: Security and Communication Networks
• Online Access: http://dx.doi.org/10.1155/2020/8810708

The weakness of the security measures implemented on IoT devices, added to the sensitivity of the data that they handle, has created an attractive environment for cybercriminals to carry out attacks. To do so, they develop malware to compromise devices and control them. The study of malware samples is a crucial task in order to gain information on how to protect these devices, but it is impossible to manually do this due to the immense number of existing samples. Moreover, in the IoT, coexist multiple hardware architectures, such as ARM, PowerPC, MIPS, Intel 8086, or x64-86, which enlarges even more the quantity of malicious software. In this article, a modular solution to automatically analyze IoT malware samples from these architectures is proposed. In addition, the proposal is subjected to evaluation, analyzing a testbed of 1500 malware samples, proving that it is an effective approach to rapidly examining malicious software compiled for any architecture.