Cyber Security and Digital Forensics MSc

The goal of cryptography is to make information secret so that only trusted individuals can access it. Cryptography has become critically important in the digital age. It is the cornerstone of secure communication and data storage, particularly in the area of e-commerce. This module aims to provide you with knowledge and critical understanding of the key concepts in cryptography. You will study the fundamental principles of cryptography. To aid your understanding, you will explore commonly used symmetric and asymmetric encryption and digital signature schemes in detail. Furthermore, you will be exposed to current state of the art developments in relation to cryptography. Finally, this module seeks to give you practical development skills in applying cryptographic techniques to a specific application scenario.

Data mining is a collection of tools, methods and statistical techniques for exploring and extracting meaningful information from large data sets. It is a rapidly growing field due to the increasing quantity of data gathered by organisations. There is a potential high value in discovering the patterns contained within such data collections. In this module you will look at different data mining techniques and use appropriate data-mining tools in order to evaluate the quality of the discovered knowledge. You will study approaches to preparing data for exploration, supervised and un-supervised approaches to data mining, exploring unstructured data and the social impact of data mining. You will be expected to develop your knowledge such that you are able to contribute to discussions around current application areas and research topics and to increase your background knowledge and understanding of issues and developments associated with data mining.

Upon completion of this module, you will have a critical understanding of threats to digital systems and how these threats are possible, usually by exploiting weaknesses in digital systems. You will explore a number of key cyber security techniques, such as, for example, cryptography and access control, and gain an understanding of how these techniques protect systems. You will also be enabled to critically evaluate and engage in scholarship in the discipline, including proposing and testing both research and investigative hypotheses.

Digital Forensics (DF) is the process of identifying, acquiring, analysing and reporting on digital evidence (DE) used in a wide range of investigations. Digital Forensic Investigations (DFIs) have a variety of applications, being used in civil, administrative, and criminal proceedings in pursuit of DE. A typical DFI would involve the investigation of crimes such as hacking, digital espionage, counter- terrorism and possession of illegal imagery, etc. The aim of this module is to provide you with the knowledge and critical understanding of the key concepts in Digital Forensics. Through this module, you will be taught how to identify, preserve, extract and analyse digital evidence in a forensically-sound manner and report on your findings. Furthermore, this module will equip you with practical skills in applying specialised forensic tools, such as FTK Imager and Autopsy, and techniques, such as data carving and file system analysis, to a specific application scenario.

Artificial intelligence (AI) is the study and development of intelligent behaviour exhibited in computational form. Its purpose is to demonstrate intelligent characteristics that provide enriched system functionality beyond that of traditional software systems. The benefits of AI spreads across many application areas, and one such area is that of cyber security. Artificial intelligence can be loosely categorised into symbolic and statistical approaches, which are often used depending on application requirements. In this module, you will study the different types of AI systems and focus on their different application use cases in cyber security. You will learn different techniques, such as Hidden Markov Models, Support Vector Machines to understand the fundamentals of AI technology. This module has a strong application focus, ensuring you gain knowledge and experience of how these techniques can be used in security in applications such as malware analysis, intrusion detection, and security policy analysis.

Upon completion of this module, you will acquire a thorough understanding of the security attacks that may threaten wired and wireless networked systems and how these attacks are possible, usually by exploiting vulnerabilities in the design, implementation, or operation of network protocols. You will explore several key network security techniques, such as IP security and network authentication protocols, and gain an understanding of how these techniques protect networks. You will also learn how to identify security vulnerabilities in enterprise networks and propose sophisticated secure designs to face such threats.

In this module you will explore current state of the art developments in relation to Distributed Ledger Technologies (DLT). DLT are the foundation by which electronic transactions can be recorded and shared in a way that offers transparency without the need for a centralised authority, such as a bank in the finance industry. The module will enable you to develop strategies to evaluate and select DLT that are most appropriate for a chosen domain, including Internet of Things and FinTech.

This module enables you to work independently on a project related to a self-selected problem. A key feature in this final stage of the course is that you will be encouraged to undertake an in-company project with an external Client. Where appropriate, however, the Project may be undertaken with an internal Client - research-active staff - on larger research and knowledge transfer projects. The Project is intended to be integrative, a culmination of knowledge, skills, competencies and experiences acquired in other modules, coupled with further development of these assets. In the case where an external client is involved, both the Client and Student will be required to sign a learning agreement that clearly outlines scope, responsibilities and ownership of the project and its products or other deliverables. The Project will be student-driven, with the clear onus on you to negotiate agreement, and communicate effectively, with all parties involved at each stage of the Project.