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Final year project report.
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- London Metropolitan University (LMU)
Final year project report for Bsc. Computing.
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CS6P05NI Final Year ProjectModule Code & Module Title
CS6P05NI Final Year Project
Assessment Weightage & Type
40% FYP Final Report
Automated Anomaly Detection Honeypot
Semester
2020 Autumn
Student Name:
London Met ID:
College ID:
Internal Supervisor:
External Supervisor:
Assignment Due Date:
Assignment Submission Date:
Word Count: 9198
I confirm that I understand my coursework needs to be submitted online via Google Classroom under the relevant
module page before the deadline in order for my assignment to be accepted and marked. I am fully aware that late
submissions will be treated as non-submission and a mark of zero will be awarded.
,CS6P05NI Final Year Project
Acknowledgement
First and foremost, I am grateful to Mr. Sujil Maharjan and Mr. Suryansh Mathema, my first
supervisors, for their unwavering enthusiasm and motivation. I would not have been able to
accomplish this report without their support and mentoring. I am also truly thankful to Mr. Raman
Pradhananga, my second supervisor for allowing me to pursue my research interests with complete
freedom and for his unconditional support. Through consultations and discussions with him, I was
able to rise as a researcher and as a person, which also aided me to see the broader perspective.
I owe Mr. Akchayat Bikram Joshi a debt of gratitude for his invaluable guidance and genuine
concern in my work at critical times. I appreciate Mr. Satyam Pradhan's willingness to review my
study and provide detailed input.
I would also like to express my gratitude to Mr. Aaditya Khati for taking the time to address my
questions and for assisting me in gaining a better understanding of the project in its current context.
Last but not least, I would like to express my appreciation towards my friends for assisting me
with the project as well as providing inspirational motivation.
,CS6P05NI Final Year Project
Abstract/Summary
This project addresses the emergent trends in extant honeypot research to contribute to the
knowledge gaps in the honeypot environment by integrating machine learning. It provides the
results that fulfill the project objectives mentioned in the proposal of the project. To achieve these
objectives, detailed comprehensive research was carried out on honeypot and machine learning to
gain familiarity and insights into the need of the project around the world. A comprehensive
investigation was also conducted into system port vulnerabilities, which are the most common
threat that attackers can use to launch an attack. Based on the proposal and the core network
scenario described, the dataset was used along with two classification algorithms,
anomaly detection was achieved using a supervised machine learning technique.
, CS6P05NI Final Year Project
Table of Content
CHAPTER 1: INTRODUCTION ................................................................................................ 1
1.1 PROJECT DESCRIPTION................................................................................................ 2
1.2 CURRENT SCENARIO ...................................................................................................... 4
1.3 PROBLEM DOMAIN AND PROJECT AS A SOLUTION ........................................... 5
1.4 AIM AND OBJECTIVES ................................................................................................... 7
1.4.1 AIM................................................................................................................................ 7
1.4.2 OBJECTIVES............................................................................................................... 7
1.5 STRUCTURE OF THE REPORT ..................................................................................... 8
1.5.1 BACKGROUND........................................................................................................... 8
1.5.2 DEVELOPMENT......................................................................................................... 8
1.5.3 TESTING AND ANALYSIS ....................................................................................... 9
1.5.4 CONCLUSION ............................................................................................................. 9
CHAPTER 2: BACKGROUND .................................................................................................. 10
2.1 ABOUT THE END USERS .............................................................................................. 11
2.2 UNDERSTANDING THE SOLUTION .......................................................................... 12
2.2.1 SYSTEM ARCHITECTURE .................................................................................... 12
2.2.2 WORKING MECHANISM ...................................................................................... 13
2.2.3 BACKGROUND......................................................................................................... 15
2.3 SIMILAR PROJECTS...................................................................................................... 22
2.3.1 HONEYCOMB ........................................................................................................... 22
2.3.2 SPECTER ................................................................................................................... 22
2.3.3 ‘AN INTELLIGENT HONEYPOT’ – AIDEN MITCHELL .................................. 22
2.4 SIMILAR STUDIES ......................................................................................................... 23
2.4.1 ‘CONTEXT-AWARE HONEYPOT’- SHUBHAM AGGARWAL ....................... 23
2.4.2 ‘DDOS MITIGATION AND INTRUSION PREVENTION USING
HONEYPOTS’- MD. M. RAHMAN, S. ROY AND M. A. YOUSUF ............................. 23
2.5 COMPARISONS ............................................................................................................... 24
CHAPTER 3: DEVELOPMENT ............................................................................................... 26
3.1 CONSIDERED METHODOLOGIES ............................................................................... 27
3.1.1 SCRUM METHODOLOGY ....................................................................................... 27
3.1.2 ITERATIVE MODEL ............................................................................................... 28
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