Networks, Security & Forensic Computing
Browse student projects below. You can get in touch with any student by clicking the arrow in a profile and filling out the form.
This software will allow any technician to modify interface configurations for routers and switches from Cisco, Juniper and Brocade over the network. The software's design will bring a familiar interface for all devices. Uses a central SQL database to store required login information to be used by all users.
This prototype is a Chrome Add-ons Unique password Generator wallet that generates a password hash using a master key and the URL being visited by the user, this method fights URL spoofing and generates strong and unique passwords for every website, without the worry of a password being stored.
A research-based project into the importance of efficient Threat Intelligence within a business, including the importance of automation. This project created generic frameworks for Threat Intelligence and Actionable Responses to Threat, alongside a case study of an Industry Standard Threat Tool and a Proof of Concept Input/Ouptut Tool.
This project covers a forensic investigation into anti-forensic tools and techniques, showing a variety of techniques used to obscure the forensic procedure and which were successful and which tools created problems. (A few techniques are Encryption, Cryptography, Geo-data manipulation. Forensic programs used are EnCase & Autopsy with X-ways theoretical)
The project will consist of the review and analysis of a few free password cracking tools which are available online for download. Taking the results from the analysis to aid in the creation of a simple password cracking prototype fit for live forensic investigations.
Chinese chipsets in smartphones are becoming increasingly common, but due to their lack of documentation and support, it can be difficult to perform a forensic extraction on them. This program performs a data extraction from a Chinese chipset and a comparison is made to extractions from industry standard tools.
The main interest of this project is to evaluate which monitoring systems will be most effective for monitoring certain networks that will be a combination of, virtual infrastructures, core networking equipment and storage equipment.
This project is an investigation into the forensic integrity of drone gathered data. It will highlight the factors and standards in which the data is assessed against to be considered forensically sound.
An investigation into how effective anti-forensic techniques used to conceal data in a storage device on Windows machines are at hiding data from a forensic investigator using tools and techniques that would allow their findings to be used as evidence in court
This project aims to develop a lightweight mobile forensic tool focusing on Android Operating System for the purpose of extracting images and messages from a system.
Computer networks are ever growing on an exponential scale, now more than ever engineer headcount needs to be detached from device count. This project has researched and implemented network automation to speed up the tasks network engineers undertake, reduce network downtime and improve the reliability and performance of networks.
An automation framework for the development of software defined tasks aimed towards the management and monitoring of network devices and servers.
Using Machine learning Markov Chain Text Generation method to automate text generation for phishing testing purposes and to test its efficiency
A portable digital evidence extractor created from a Raspberry Pi. Intended for searching removable storage devices (such as USBs) for specific files and copying any found files onto another storage device for further investigation.
To create an application that can read RFID tags and mimic them using a phones in-built NFC.
This project investigates the process of machine learning and if it can be effective at detecting intrusions such as DDoS. The dataset 'KDD' is used as a data example which is trained and tested using machine learning tools such as RapidMiner, Python and visualised using Tensorflow.