Cyber security is a vital concern for companies with internet-based cloud networks. These networks are constantly vulnerable to attack, whether from inside or outside organization. Due to the ever-changing nature of the cyber world, security solutions must be updated regularly in order to keep infrastructure secure. With the use of attack detection approaches, security systems such as antivirus, firewalls, or intrusion detection systems have become more effective. However, conventional systems are unable to detect zero-day attacks or behavioral changes. These drawbacks can be overcome by setting up a honeypot. In this paper, a hybrid Honeynet model deployed in Docker (H-DOC) bait has been proposed that comprises both low interaction and high interaction honeypot to attract the malicious attacker and to analyze the behavioral patterns. This is a form of bait, designed to detect or block attacks, or to divert an attacker's attention away from the legitimate services. It focuses only on the SSH protocol, as it is widely used for remote system access and is a popular target of attacks. The proposed Hybrid H-DOC method identify ransomware activity, attack trends, and timely decision-making through the use of an effective rule and tunes the firewall. The attack detection accuracy of the proposed Hybrid H-DOC method when compared with IDH, Decepti-SCADA, AS-IDS and HDCM is 13.97%, 11.82%, 8.60% and 5.07% respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.