TITLE:
Captcha-Based Honey Net Model against Malicious Codes
AUTHORS:
Adeniyi Akanni, Williams Akanni, Oluwafunmilasyo Helen Daso
KEYWORDS:
Passive Attack, Active Attack, Honey Net, Malware, Internet of Things (IoT), Log
JOURNAL NAME:
Journal of Computer and Communications,
Vol.11 No.3,
March
31,
2023
ABSTRACT: The rate of passive and active attacks has been on the increase lately affecting both individuals and institutions. Even when internal control procedures are in place, malicious codes from intruders into the network have left so much to be desired. As a result, many Chief Information Security Officers have grown grey hair because of their inability to effectively handle attacks from various ends. Various attempts and technologies have been made in the time past with a measure of success. Intrusion Detection Software (IDS), Intrusion Prevention Software, firewall, honey pots and honey nets have been deployed and with great respite from losses arising from cyber-attacks. Cyber security is the duty of everyone and all must see it as such. As tiers of government and law enforcement agents are doing their best, everybody must be seen to play their parts. Fraudsters have also not seemed to be tired of seeking vulnerabilities to exploit. Then, cyber security experts should not let off their guards but make efforts to harden their security. A way of doing is to intelligently provide a solution that has the capability of detecting and proactively hardening security. This paper proposes a honey net model that is captcha-based and capable of extracting details from hackers with a view to building a robust defense against black hat attackers. This research was able to prevent the botnet with the use of captcha and also redirect suspected traffic to the honeynet which was then captured for the purpose of improving the security of the network. The result showed that any bandwidth greater than the set threshold was not allowed to go into the network but redirected to honeynet where details were logged. Also, with a threshold of 100 mbs, inbound traffic of higher bandwidth such as 110 mbs and 150 mbs was denied access thereby giving 100% detection rate.