Ryandy, Ryandy and Lim, Charles and Silaen, Kalpin Erlanggaa (2020) Actionable Threat Intelligence Generation Based on Darknet Traffic Analysis. Bachelor thesis, Swiss German University.

Preview	Text Ryandy 11602002-TOC.pdf Download (1MB) | Preview
	Text Ryandy 11602002-1.pdf Restricted to Registered users only Download (630kB)
	Text Ryandy 11602002-2.pdf Restricted to Registered users only Download (3MB)
	Text Ryandy 11602002-3.pdf Restricted to Registered users only Download (994kB)
	Text Ryandy 11602002-4.pdf Restricted to Registered users only Download (2MB)
	Text Ryandy 11602002-5.pdf Restricted to Registered users only Download (264kB)
Preview	Text Ryandy 11602002-Ref.pdf Download (641kB) | Preview

Abstract

The rise of Cyber security threat is evolving rapidly because the advancement of adversary and the adversary payload. In this era a solo fighter Cyber security defender is not an option and more and more Cyber Security Defender join hand to eliminate the emerging threat and eliminate the usage of the same payload to compromise system this joint work is realized by implementing Cyber Threat intelligent and in this thesis the main purpose is to automatically generate Actionable Cyber Threat Intelligence that is able to capture emerging threat by deploying passive monitoring, trap, deception tool into the darknet environment where supposed there shouldn’t have a connection incoming and outgoing to the system, because of that the traffic that is coming to the darknet environment should be treated as an attack. This research categorize the result of the xperiment based on the honeypot-based security threats, to generate into the Cyber Threat Information.

Item Type:	Thesis (Bachelor)
Uncontrolled Keywords:	Actionable Threat Intelligence, Darknet Monitoring, Threat Categorization, Analysis of Threat, Traffic Analysis, Malware Analysis
Subjects:	Q Science > QA Mathematics > QA76 Computer software > T Technology > T Technology (General) > T58.5 Information technology
Divisions:	Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User:	Faisal Ifzaldi
Date Deposited:	02 Nov 2020 13:49
Last Modified:	02 Nov 2020 13:49
URI:	http://repository.sgu.ac.id/id/eprint/1824

Actions (login required)

View Item