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Cyber Threats, Vulnerabilities & Countermeasures

Assignment Brief

Systems - Cyber Threats, Vulnerabilities & Countermeasures (CSI_7_SYS)

Coursework – Specification

Implementation of a Cyber Security Mechanism Assessment

Coursework

Additional Information

Issued

Due Date

%Weight

Coursework 2

This is an individual-based assessment

Week 7

16 April 2021

60%

Cybersecurity or information technology security (IT security) is the protection of computer systems and networks from information disclosure, theft of or damage to their hardware, software, or electronic data, as well as from the disruption or misdirection of the services they provide.

Coursework 2

This coursework is individual and worth 60% of the module total. Your objective is to choose and implement ONLY ONE defensive mechanism from the ones listed below, that could be used in the cyber-security field to provide protection against any threat. Describe a use-case scenario of using the defensive mechanism, and provide and a step-by-step implementation and usage guide. The available case studies for defensive mechanisms are:

1.  Developing and usage of a cryptographic Algorithm in Python (https://docs.python.org/3/) or C+

+ (https://www.cplusplus.com/ ). For this case study, students have to use a programming language and some cryptographic libraries to develop their own application.

2. Web-Security protection (for example against SQL-Injection, XSS e.t.c.). In this case study, students need to develop and demonstrate their own web-application that will include a defensive solution for a given threat. For this purpose you could use HTML (https://www.w3schools.com/html/ ) and PHP (https://www.php.net/ ) languages. Alternatively, you could use an existing tool or mechanism (install, environmental setup, usage e.t.c.) that provides protection over the web, demonstrate and discuss its effectiveness.

3. Implementation of network security mechanism (firewall, IDS/IPS e.t.c.). For this case study, students need to setup their own network (physical or virtual) implement their defensive mechanism into it and discuss things as network performance, protocols affected, network operations e.t.c.

4. Use of neural networks for malware detection.(e.q. https://github.com/PacktPublishing/Mastering- Machine-Learning-for-Penetration-Testing ). For this case study, students have to develop some code and use data-mining techniques and datasets in order to discuss the use of neural networks in cyber-security field.

You could choose a software or hardware product that could provide a solution.

Only 25 students max are allowed to be allocated into each of the above case studies. So, students need to express their interest (via MS-Teams private message) in a specific topic within the first two weeks, and the First-Come-First-Served policy will be followed. Otherwise, a case study will be randomly assigned to students based on availability. Since each student has been allocated to work on a specific case study for the coursework, can only work on the case study that you have been allocated to. You CANNOT swap case studies afterwards. Beware, if a different case study will be submitted than the one that has been allocated, there is a high risk be considered out of topic.

The Final Report

Students are required to write a professional report minimum of 2500 words, describing the work they have done and briefly justifying any details regarding the defensive mechanism. They must document all of their steps, commands issued, and console output in the form of a scientific report. The documentation should be thorough enough that your implementation can be replicated step-by-step by a technically competent reader.

Screenshot Requirements

Along, with the documentation, you have to provide screenshots describing the use-case and the defensive mechanism. All evidence provided needs to be followed by a supportive narrative.

Those screenshots could include information as:

  • Networking environment Attacker( e.q. IP address)

  • Tools (GUI/CLI environment) that have been used.

  • Results that show the effectiveness of the mechanism.

  • Any other evidence that could be used as a proof of concept.

Presentation

Students also need to include a short presentation to present their work. For this purpose you need to create a short video (.mp4), duration up to 10 minutes max, that will explain what you have done. Additionally, those who wish they could present to their classmates (via MS-Teams) during the presentation weeks at the end of the semester.

Submission Details

Students will have to submit 3 different FILES:

  1. The main report (.doc, .docx, .pdf), that will include the documentation of the coursework in a scientific format.

  2. A compressed file (.zip), that will include any source code that has been developed, installation files, link or tools that have been used for the implementation.

    • The presentation video (.mp4), audiovisual material presenting their work. Alternatively, in case  that the size of the video is too big, a YouTube or oneDrive link (in a “presentation_link.txt” file) could be used.

The filenames need to have the format:

  1. studentID_name-coursework_report.doc (example: 123456_John_Doe-coursework_report.doc)

  2. studentID_name-support_materials.zip (example: 123456_John_Doe-support_materials.zip)

  3. studentID_name-presentation.mp4 (example: 123456_John_Doe-presentation.pdf)

Marking Criteria

Criteria

Excellent (100-71%)

Comprehens ive

(70-61%)

Pass

(60-51%)

Weak (50-41%)

Poor (40-0%)

Total Marks

/60

Report     Structure and Readability

 

(Marks 10%)

Sophisticated, consistent, error free application of relevant topics conventions with great attention to detail.

Excellent writing, structure, spelling, grammar and referencing.

Comprehensive application of relevant topics conventions with few errors.

Very good writing, structure, spelling, grammar,  but with minor errors.

Generally correct application of relevant topics conventions, with some errors and / or inconsistencies. The length of the report is at least 2500 words

Poorly written with confusing structure, spelling, grammar and / or errors. Below the minimum of 2500 words

Poorly written, less than 2500 words, with no academic style, structure, spelling, grammar and/or multiple errors.

 

 

 

 

Sufficiently written with little structure, spelling, grammar with some errors

 

 

Abstract           and Introduction

 

(Marks 10%)

A well-articulated abstract and introduction that provides a clear, logical, and succinct description of content, objectives, scope and requirements. The organization of the review, which draws the reader’s attention to a central concern, debate, or contention.

A well-articulated abstract and introduction that provides a clear, logical description of content, objectives, scope, requirements and organization of the review

Satisfactory abstract and introduction that has a good reflection and description of the content, objective, scope, and organization of the report.

An abstract that articulates some key components of the report. An introduction that outlines the content, scope, and organization of the report

Either no abstract or introduction, or one that poorly or partially situates the reader in the context of the concern, debate, or contention addressed in the report

 

Conclusions and Critical Analysis

 

(Marks 10%)

Excellent breadth, accuracy and detail in understanding key aspects of subject.

Contributes to subject debate. Very good awareness of ambiguities and limitations of knowledge. Provides high-level summary, very accurate and detailed.

Very high-quality analysis developed independently. Sustained evaluation and synthesis of resources.

Good depth of understanding of key aspects of subject shown Evidence of coherent knowledge. Very good contribution to subject debate.

Very good understanding and interpretation of results.

Demonstrated good understanding of key aspects of subject. Some evidence of coherent knowledge and own critique.

Sufficiently summarize the report with good interpretation of results

Weak evidence of superficial understanding of subject. Inaccuracies, does not summarize well the report or lack of succinctness.

Some attempt at evaluation and some synthesis of resources.

Little or no evidence of understanding of subject.

Inaccuracies.

Lack of understanding and interpretation of results, no critical analysis or does not summarize the report.

 

Defensive Mechanism

Description of the mechanism and Use Case(s)

 

(Marks 15%)

Shows breadth, accuracy and detail in understanding key aspects of subject.

Contributes to subject debate. Some awareness of ambiguities and limitations of knowledge.

Knowledge and understanding are consistent and accurately developed with a level of criticality.

Accurate and extensive understanding of key aspects

of subject. Evidence of coherent knowledge.

Knowledge and understanding are basic/relatively superficial.

Accurate understanding of key aspects of subject. Evidence of coherent knowledge.

Knowledge and understanding are detailed and satisfactory.

Some evidence of superficial understanding of subject. Minor Inaccuracies.

Knowledge and understanding shows consistent gaps.

Little or no evidence of understanding of subject. Many Inaccuracies.

Knowledge and understanding are poor and lacks academic rigor.

 

Implementation and scenario Execution

 

(Marks 30%)

Excellent problem-solving ability and implementation of the proposed methodologies and solutions.

 

Ability to Adapt to unforeseen practical and theoretical challenges to achieve project objectives. Well crafted technical solution, addressing all aspects of the user requirements.

Very good problem-solving ability and implementation of the proposed

methodologies and Solutions.

 

Adapt to practical and theoretical challenges to achieve project objectives.

Sufficient problem- solving ability and implementation of the

proposed methodologies and solutions.

 

Some adaptation to practical and theoretical challenges to achieve project

Limited problem- solving

ability and implementation of the proposed

methodologies and Solutions.

 

Limited exploration of possible solution(s) using established approaches to

Poor or lack of problem-solving ability and implementation of the

proposed methodologies and solutions.

 

Little or no exploration of solution(s).

Question or

 

 

 

Comprehensive technical solution, addressing various aspects of the user requirements.

objectives identified goals. Good technical solution, addressing most aspects of the user requirements.

resolve practical and theoretical problems. Weak attempt at the technical solution, addressing only few aspects of the user requirements.

problem unresolved. Poor attempt at technical proposition.

 

Presentation (Marks 25%)

Showed excellent confidence & composure. Very clear, persuasive and compelling with skilful use of the presentation format.

Presentation addresses the needs of the audience very well.

Were mostly confidence & composed. presentation is clear, mostly persuasive, compelling and skilfully presented.

Presentation addresses the needs of the audience to a large degree.

Good use of the presentation format and skills. Presentation takes into account the needs of the audience.

Presentation format is adequate. Showed some confidence & composure, but has room for improvement. Presentation may sometimes not take into account the needs of the audience.

Showed no confidence or composure. presentation format is not used adequately, and the needs of the audience are not taken into account.

 

Comments:

Final Mark:

100% Plagiarism Free & Custom Written,
tailored to your instructions

Sample Answer

Implementation of a Network Intrusion Detection System Using Snort

Abstract

Cyber threats targeting network infrastructures continue to increase in complexity, scale, and frequency. Traditional perimeter security mechanisms alone are no longer sufficient to detect and mitigate sophisticated attacks such as reconnaissance scanning, brute force attempts, and malicious payload delivery. This report presents the implementation of a network-based Intrusion Detection System (IDS) using Snort as a defensive cybersecurity mechanism. The objective is to demonstrate how Snort can be deployed within a controlled network environment to detect suspicious activity, generate alerts, and support security monitoring. A realistic attack scenario is developed, followed by a detailed step-by-step implementation guide that allows replication by a technically competent reader. The effectiveness, limitations, and performance impact of the IDS are critically evaluated to assess its suitability as a defensive mechanism in modern networks.

Introduction

Cybersecurity is fundamentally concerned with protecting computer systems and networks from unauthorised access, data breaches, service disruption, and misuse. As organisations increasingly rely on interconnected systems, network-level attacks have become one of the most common vectors used by attackers. These attacks often exploit weaknesses in protocols, misconfigurations, or human error, making detection as important as prevention.

While firewalls remain essential for controlling traffic flow, they are limited in their ability to detect malicious activity that appears legitimate at a protocol level. Intrusion Detection Systems address this limitation by analysing network traffic and identifying patterns associated with known or suspicious attack behaviour. This coursework focuses on the implementation of a network-based IDS using Snort, an open-source and widely adopted security tool.

The aim of this report is to design, implement, and evaluate Snort as a defensive mechanism within a virtual network environment. A practical use case is presented where Snort detects network reconnaissance and malicious traffic originating from an attacker machine. The report documents all configuration steps, commands, and observations to ensure full reproducibility.

Defensive Mechanism Overview

Intrusion Detection Systems

An Intrusion Detection System is a security mechanism that monitors network traffic or host activity to detect signs of malicious behaviour. Unlike firewalls, which block or allow traffic based on predefined rules, IDS solutions focus on visibility and alerting. They can operate in two main forms: host-based IDS and network-based IDS.

Network-based IDS monitor traffic flowing through network interfaces and analyse packets in real time. This makes them particularly effective against attacks such as port scanning, denial-of-service attempts, and exploitation of network services.

Snort IDS

Snort is an open-source network intrusion detection and prevention system developed by Cisco. It operates by capturing network packets and analysing them against a set of predefined rules. These rules describe patterns associated with known attacks, protocol anomalies, or suspicious behaviour.

Snort supports three main modes: packet sniffer mode, packet logger mode, and intrusion detection mode. In this implementation, Snort is configured in intrusion detection mode to monitor traffic and generate alerts when malicious activity is detected.

Use Case Scenario

Scenario Description

The use case simulates a small organisational network consisting of a target server and an internal workstation. An attacker machine is placed on the same virtual network to perform reconnaissance and attack attempts. The objective is to detect malicious behaviour using Snort before any successful compromise occurs.

Threat Model

The primary threats considered in this scenario include:

  • Network reconnaissance using port scanning

  • Suspicious ICMP traffic

  • Attempted exploitation of open services

These threats are realistic and commonly observed during the early stages of cyber attacks.

Network Environment Setup

Virtual Environment

The implementation was carried out using a virtualised environment to ensure isolation and repeatability. The following systems were used:

  • Attacker machine: Kali Linux

  • Target system: Ubuntu Server

  • IDS system: Ubuntu Linux with Snort installed

All machines were configured on the same virtual network using host-only networking.

IP Addressing

Each system was assigned a static IP address to simplify monitoring and analysis. The IDS system was configured to monitor traffic on the primary network interface.

Screenshots of the network configuration, IP addresses, and interface settings are included in the supporting materials zip file.

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Yes. Every step is designed to be reproducible.

Yes. The focus is strictly on a network IDS using Snort.

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