Abstract
In softwarized industrial networking, honeypot identification is very important for both the attacker and the defender. Existing honeypot identification relies on simple features of honeypot. There exist two challenges: The simple feature is easily simulated, which causes inaccurate results, whereas the advanced feature relies on high interactions, which lead to security risks. To cope with these challenges, in this article, we propose a secure fuzzy testing approach for honeypot identification inspired by vulnerability mining. It utilizes error handling to distinguish honeypots and real devices. Specifically, we adopt a novel identification architecture with two steps. First, a multiobject fuzzy testing is proposed. It adopts mutation rules and security rules to generate effective and secure probe packets. Then, these probe packets are used for scanning and identification. Experiments show that the fuzzy testing is effective and corresponding probe packet can acquire more features than other packets. These features are helpful for honeypot identification.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.