TY  - INPR
ID  - SisLab3757
UR  - https://www.hindawi.com/journals/scn/
A1  - Tran, Nghi Phu
A1  - Hoang, Dang Kien
A1  - Ngo, Quoc Dung
A1  - Nguyen, Dai Tho
A1  - Nguyen, Ngoc Binh
Y1  - 2019///
N2  - Malware on devices connected to the Internet via the Internet of Things (IoT) ) is evolving and is a core component of the fourth industrial revolution. IoT devices use the MIPS architecture with a large proportion running on embedded Linux operating systems, but the automatic analysis of IoT malware has not resolved. We proposed a framework to classify malware in IoT devices by using MIPS-based system behavior (system call - syscall) got from our F-Sandbox passive process and machine learning techniques. The F-Sandbox is a new type for IoT sandbox, automatically created from the real firmware of the specialized IoT devices, inheriting the specialized environment in the real firmware, therefore creating a diverse environment for sandboxing as an important characteristic of IoT sandbox. This framework classifies five families of IoT malware with F1-Weight = 97.44%.
PB  - Hindawi
JF  - Security and Communication Networks
SN  - 1939-0114
TI  - A Novel Framework to Classify Malware in MIPS Architecture-based IoT Devices
AV  - public
ER  -