@Article{cmc.2020.010593,
AUTHOR = {Yanbin Sun, Xiaojun Pan, Chao Xu, Penggang Sun, Quanlong Guan, Mohan Li, Men Han},
TITLE = {Identifying Honeypots from ICS Devices Using Lightweight Fuzzy Testing},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {65},
YEAR = {2020},
NUMBER = {2},
PAGES = {1723--1737},
URL = {http://www.techscience.com/cmc/v65n2/39902},
ISSN = {1546-2226},
ABSTRACT = {The security issues of industrial control systems (ICSs) have become 
increasingly prevalent. As an important part of ICS security, honeypots and antihoneypots have become the focus of offensive and defensive confrontation. However, 
research on ICS honeypots still lacks breakthroughs, and it is difficult to simulate real 
ICS devices perfectly. In this paper, we studied ICS honeypots to identify and address 
their weaknesses. First, an intelligent honeypot identification framework is proposed, 
based on which feature data type requirements and feature data acquisition for honeypot 
identification is studied. Inspired by vulnerability mining, we propose a feature 
acquisition approach based on lightweight fuzz testing, which utilizes the differences in 
error handling between the ICS device and the ICS honeypot. By combining the proposed 
method with common feature acquisition approaches, the integrated feature data can be 
obtained. The experimental results show that the feature data acquired is effective for 
honeypot identification.},
DOI = {10.32604/cmc.2020.010593}
}