Computer and Digital Forensics BSc (Hons)

In this module you will engage with knowledge to professionally, systematically and impartially approach the preservation, extraction and interpretation of all relevant digital evidence. Further you will develop analytical and evaluative skills in the appropriate use of digital forensic tools for solving problems in a variety of environments and problem situations

You will aquire knowledge of the legal and evidentiary processes involved in digital forensic investigations, both civil and criminal. You will be taught about the legal processes involved with acting as an expert witness and the admissibility of evidence. Further, you will acquire knowledge of the requirements for corporate investigations and the implications of e-disclosure. You will also learn evidence processing techniques for dealing with large volumes of digital data, a prominent feature of many cases given the availability of large capacity digital storage media.

Through the analysis and examination of digital forensic case studies, you will develop a critical appreciation of the legal and regulatory aspects of a digital forensic investigation. You will also apply the theory and skills derived from the relevant taught modules on this programme to an advanced level by undertaking a detailed digital forensics investigation. You will develop analytical and evaluative skills in the appropriate use of digital forensic tools for solving problems in a variety of environments and situations

Academic skills when studying away from your home country can differ due to cultural and language differences in teaching and assessment practices. This module is designed to support your transition in the use and practice of technical language and subject specific skills around assessments and teaching provision in your chosen subject. The overall aim of this module is to develop your abilities to read and study effectively for academic purposes; to develop your skills in analysing and using source material in seminars and academic writing and to develop your use and application of language and communications skills to a higher level.

The topics you will cover on the module include:

• Understanding assignment briefs and exam questions.
• Developing academic writing skills, including citation, paraphrasing, and summarising.
• Practising ‘critical reading’ and ‘critical writing’
• Planning and structuring academic assignments (e.g. essays, reports and presentations).
• Avoiding academic misconduct and gaining credit by using academic sources and referencing effectively.
• Listening skills for lectures.
• Speaking in seminar presentations.
• Presenting your ideas
• Giving discipline-related academic presentations, experiencing peer observation, and receiving formative feedback.
• Speed reading techniques.
• Developing self-reflection skills.

This module will introduce the key elements of business intelligence and organisational decision making. Drawing on business analytics, decision science and systems thinking, you will explore how organisations are able to leverage data and information to formulate a complete understanding of complex problems and to identify and implement optimal solutions. Employers are looking for data-literate graduates with the ability to explore and solve novel business problems, and as such, this module will cover topics such as organisational process modelling, business performance management, data analytics in a business context, and the use of data visualisation as a tool for exploration and communication. You will have to the opportunity to work with others in collaborative problem-solving scenarios, to investigate how businesses can use effective decision making to achieve optimal, sustainable solutions, and to explore the ethical, legal, and societal issues present when using data-driven technologies.

This is your major final year project module where you will undertake a substantial individual practical computing project related to your programme of study. You will become knowledgeable in your chosen topic including important concepts and literature. You will use and further develop skills learnt elsewhere in your programme and acquire new skills and expertise to carry out the practical computing work. These could be technical skills such as a new programming language, experimental methods, and/or the use of statistical techniques to analyse your results. You will also acquire or further develop your professional skills including communication skills (both oral presentation and report writing), literature searching and review, research methods and design, project management and personal time management. Both the technical and professional skills developed through the project module will enhance your career and employability competencies.

You will have the freedom to choose a topic of your interest or select one provided by academic staff. Your project must include you undertaking practical work of some sort using computing/IT technology. This is most frequently achieved by the creation of an artefact as the focus for covering all or part of an implementation lifecycle. However, there are a diversity of approaches you can take. For example, you could choose to conduct a more product-focused project where the main deliverable is a product of some kind such as a piece of software, a game, a computer network, an information strategy. Or it could be a more investigative and/or research-focused project such as a digital forensics investigation, a comparison analysis of AI algorithms, a user experience investigation. Or your project could be a mix of both such as building a simulated network to investigate security vulnerabilities and mitigation schemes, creating a prototype to test the effectiveness of a digital technology. Projects based solely on literature review activity and/or user/market surveys are not acceptable. You could also work with an external enterprise client to create a product in terms of their business requirements.

This module will give you an essential foundation to focus on how to conduct statistical analysis and interpret various measures correctly. You will learn to think about the process of examining data from the “ground up”, adopting pragmatic approaches e.g., how to investigate and explore data, data structures and visualisations.

‘Data Analytics’ will prepare you for the study of the computational principles, methods, and systems for extracting and structuring knowledge from data. It will also prepare you for the application and use of those principles. For example, large data sets are now generated by almost every activity in science, society, and commerce - ranging from molecular biology to social media, from sustainable energy to health care. You will explore methods to conduct efficient and pragmatic approaches to ensure you have translational skills.

During ‘Data Analytics’ you will work through a series of exercises, making use of Northumbria’s state-of-the-art computer labs. Your learning will be research-rich by providing you opportunities to link with active research groups tackling real world problems to prepare you for life beyond Northumbria. The main element in assessment (100%) will be a final assignment that will bring together all your new skills and techniques.

This module will provide you with a detailed examination of Enterprise and Wide Area Networks (WANs) and their secure implementations. You will learn the theory and practical implementation of relevant protocols and security strategies. A particular feature of the module is the incorporation of subject areas from the final module of Cisco’s Networking Academy programme CCNA. The incorporation of Cisco’s Networking Academy programme is designed to strengthen your skills relevant for future graduate employment by giving you the opportunity to demonstrate the application of appropriate digital technologies in an Enterprise and WAN context, and by encouraging you to strengthen your self-management when completing your CCNA learning.

The main topics you will engage with on this module include:

1. Introduction to Enterprise and Wide Area Networks (WANs): Theory and practice of relevant protocols and technologies, including: PPP, OSPF, MPLS, GRE, VPN, IPSec.
2. Topics related to Enterprise and WANs including NAT, PAT, DHCP.
3. Network performance and security in an Enterprise and WAN context.

There is an emphasis on practical work in the delivery of the module, and you will have an opportunity to work directly with industry standard networking hardware and software. You will also make extensive use of appropriate network simulation software which will aid the accessibility of the module content.

You will be introduced to the fundamental theoretical concepts of Enterprise Networks and WANs during the lectures. The lab classes will give you an opportunity to apply and extend your understanding through a series of challenging problem-solving exercises.

Evolutionary algorithms (EAs) are a class of optimisation techniques that are inspired by natural evolution. They are well-suited to problems for which no specific solution method exists, or where other methods perform badly, and they have been used very successfully in areas as diverse as finance, engineering, architecture and logistics. In this module, you will learn about the fundamental principles of EAs, understand how (and why) they are used, and develop your own EA for a specific problem.

EAs are used extensively in business, industry, and scientific research, and the ability to analyse a problem and develop an EA to solve it demonstrates a number of sought-after key skills.

This module is research-driven, and is taught by academics who have published extensively in the field of evolutionary computation. You will benefit from access to up-to-date knowledge, codebases and datasets.

The main component of assessment is a development assignment (70%), which will bring together the skills and techniques that you will acquire during the course of the module.

Indicative list of topics:

• Natural and artificial evolution
• Representation schemes and search operators for optimisation
• Constrained and multi-objective optimisation
• Evaluation of evolutionary algorithm performance
• Theoretical foundations
• State-of-the-art applications

This module will give you a deep understanding of the implementation and programming of robot technologie as autonomous systems. You will have practical experience with using the math underlying robot programming and design, including kinematics, probability and geometry. You will be taught about the components, sensor arrays and programming frameworks that make up a modern robotic system. You will research and develop a small robot that is designed for a specific industrial application, for example a warehouse stock and material transport robot, a localisation and mapping robot or a driverless vehicle. Each implementation of a robotic system will use main control architecture, state of the art sensor fusion techniques that enable localisation, obstacle avoidance, vision algorithms, path planning or navigation. The module will also cover emergent ethical and safety issues related to robotics and automation.