Networks and Security - MSc

The module will cover a mixture of theoretical and practical topics in the area of mobile devices and the Internet of Things (IoT), that is, the use of Internet technologies to access and interact with objects in the physical world. This will include coverage of the range of sensor and actuator devices available, ways in which they communicate and compute, methods for getting information to and from IoT-enabled devices, ways of visualising and processing data gained from the IoT, and associated privacy and security issues. A practical component will consist of building the hardware and software for a sensor network and a system to visualise data from that network. Application development for mobile devices such as smartphones will also be introduced using a popular mobile platform.

A synopsis of the curriculumIntroduction, including a review of network techniques, switching and multiple access.High speed local area networks.Network protocols, including data link, network, transport and application layers.Real time data transmission and quality of service.Naming and addressing, including material on the domain name system, dynamic IP address allocation and address translation systems.Routing in data networksNetwork services.Firewalls and layer 3 network security.Recent developments. Topic will change from year to year and will be addressed prinicipally by research seminars and student centred research.

• A study of cryptographic algorithms including symmetric and asymmetric techniques and the distinction between encryption and signatures.

• Security mechanisms used with operating systems, including: access control lists and capabilities. Trusted operating systems and common criteria for evaluation.

• Problems of network security including wiretap, replay, masquerade and denial of service. Mechanisms to provide security such as firewalls and VPNs.

• Viruses and worms.

• Distributed Mechanisms, including client authentication (Needham-Schroeder, Kerberos and others); public key infrastructures and certification, with treatment of chains and authority, and the problem of revocation.

• Digital rights management systems: CSS, OMA DRM. Using digital watermarking techniques for digital rights management.

• Security of IEEE 802.11 networks (aka Wi-Fi), presentation and discussion of their security protocols: WEP, WPA, WPA2, IEEE 802.11i and RSN.

Students choose their project near the end of term 1 in coordination with the Project Research module (CO885). Projects are normally selected from a list of suggestions proposed by the school, a number of which may involve external collaboration. Alternatively, students may propose a project of their own if a suitable member of academic staff is available to act as the supervisor. In all cases the particular project must be appropriate for, and relevant to, the student's programme of study.

The project consists of an extended period during which students work on a specific piece of project work and a report on this work in the form of a dissertation. The project can be carried out individually or in groups, but the dissertation will always be individual. The project examines the student's ability to research the literature and related technologies, to understand and expand on a specific technical problem commensurate with their programme of study and relate it to other work, to carry out investigations and practical work generally including programming to describe results and draw conclusions from them and to write a coherent and well organised dissertation.

Email security. Spam: why? ; spam 'click through' rates; targeted spam; spam filtering systems. Phishing attacks; blocking fake sites; browser based defences. Email based malware and defences against this.

Intrusion detection and prevention systems; honey pots.

Denial of service; distributed denial of service; bot-nets; methods to detect complex denial of service attacks and defences against them.

Problems of eavesdropping; security in wireless networks.

Use of router based firewalls as a method to protect intranets: de-militarized zones, bastion hosts; internal intranet firewalls; personal firewalls.

Proxy based firewall systems: control over which parts of the Internet are accessible; black-lists and white-lists; key-word based filtering; time based controls.

The crowning piece of most Masters degrees is the Project and Dissertation in which you apply a wide range of skills learned in the taught modules to an interesting research problem or practical application of your choice. The Project Research module provides useful transferable skills for doing the project, and supports you in some preparatory tasks such as literature study and project planning.

Training in research methods is provided through a series of workshops, covering the following topics:

• Introduction to research

• Project selection

• Topic analysis

• Information gathering

• Simulation, experimentation and data analysis

• Writing about research

• Presenting research

• Intellectual property

• The publication process

• The review process

The module culminates in a mini-conference where students present their research.

This module builds on CO871 Advanced Java for Programmers and extends your knowledge to cover the language C++ which is widely used by professional programmers.

Syllabus

Introduction to the C and C++ languages, relating to their previous knowledge of Java, including interfaces, classes, abstract classes, inheritance, interfaces, overloading and templates;

Review of command-line based development, including compiling, debugging and makefiles;

C++ specific items, including multiple inheritance, namespaces, friend classes, virtual methods, pointers, casting operators and explicit memory management;

Low-level programming in C++, covering considerations for inline assembly, linkage with other languages and mobile platform development;

High-level programming in C++, covering large scale applications, efficient programming (e.g. games) and design patterns;

Coverage of standard libraries, where to look for these, and how to use them;

• Introduction to software development environments and the facilities they provide.

• Development of simple applications in these environments, using a broad range of the facilities provided.

• Software libraries and frameworks, and their use in developing and testing software systems.

• Use of development frameworks' facilities for project and source-code management, automated testing, refactoring and profiling.

• Deploying applications across multiple platforms using installers and build-systems; continuous integration and deployment

From Wikipedia

"Cloud computing is Internet-based computing, whereby shared servers provide resources, software, and data to computers and other devices on demand, as with the electricity grid. Cloud computing is a natural evolution of the widespread adoption of virtualization, service-oriented architecture and utility computing. Details are abstracted from consumers, who no longer have need for expertise in, or control over, the technology infrastructure "in the cloud" that supports them.

Cloud computing describes a new supplement, consumption, and delivery model for IT services based on the Internet, and it typically involves over-the-Internet provision of dynamically scalable and often virtualized resources. It is a byproduct and consequence of the ease-of-access to remote computing sites provided by the Internet. This frequently takes the form of web-based tools or applications that users can access and use through a web browser as if it were a program installed locally on their own computer."

The curriculum will include:

• Overview of web services and their use in grid/cloud computing;

• Review grid computing technologies and the relations and differences between grid computing and cloud computing;

• Virtualisation technologies, tools for cloud computing (Xen or KVM);

• Open source cloud infrastructures and applications, including Hadoop,Eucalyptus etc;

• Cutting edge commercial cloud infrastructure and applications.

Building upon CO881 Introduction to Object-Oriented Programming, this module covers the design and implementation of high-quality software using OO techniques. Systems are modelled as configurations of objects communicating with one another. Techniques (e.g. inheritance) are introduced which allow objects to play different roles within a system. These two concepts are key to the support for adaptation and reuse that OOP provides. Much emphasis will be placed on gaining a deep understanding of these concepts and applying them in practice by developing programs in Java. The remainder of the module will explore software component frameworks, specifically those that come packaged with Java, placing most emphasis on the frameworks to support the structuring and manipulation of data (data structures and algorithms).

A computer system's architecture describes the underlying combination of software and hardware that needs to be provided before the system can be used; an understanding of the basic principles of computer architecture is essential if computer systems are to be used effectively.

Fundamental ideas of computer hardware:

Boolean algebra.

Binary and hexadecimal numbers, two's complement, and binary arithmetic.

Data representation: bits, bytes, and words; character codes.

The von Neumann architecture: processor, memory, and peripherals; registers, RAM and ROM, data and address buses; the fetch-execute cycle.

Processor microarchitecture: CISC v RISC, superscalar, pipelined, out-of-order execution, branch prediction, multiprocessing.

Cache architectures.

Buses.

Practical introduction to the use of a UNIX-like operating system:

The structure of the filing system.

Syntax of operating system commands: options, files, etc.

Input/output, redirection and pipes.

Operating system tools and their use in building pipelines.

The principles and mechanisms of operating systems:

Function and historical development of operating systems.

Processes: states, communication, mutual exclusion, synchronisation, semaphores, monitors, avoidance of deadlock, high-level scheduling, process security.

The kernel: hardware requirements, interrupt handlers, low-level scheduling.

Memory management: swapping, virtual memory, paging.

Input/output; blocking and non-blocking transfers; privileged I/O processes.

File systems: functions, storage media, layout and organisation of files, file security.

The loading process; libraries; relocation.

Resource allocation; resource management.

Local and remote file access.

Introduction to cognitive neural networks.

Neural networks will be placed into a historical perspective related to symbolic approaches and in the context of the artificial intelligence hypothesis. Students will familiarise themselves with the Leabra environment.

The individual neuron.

The idea of the components of a neuron as a 'detector' will be developed. Neural networks will be explained in terms of the biology of the brain at a cellular electro-transmission level. The neurobiology will be abstracted into an initial neural network framework, i.e. a set of mathematical equations. Single neuron simulations.

Networks of Neurons.

A general framework will be provided for neural network architectures both at an abstract level and in terms of networks in the cortex. Unidirectional (feedforward) and bi-directional (recurrent) interactions will be explained together with inhibitory mechanisms.

Model Learning.

A simple Hebbian model of learning will be outlined, pertaining to neurobiology and neural networks. Other models of unsupervised learning will be introduced.

Task Learning.

Error-driven task learning will be outlined; the delta rule and back propagation will be presented. A discussion of the biological implausibility of back propagation networks will follow. Motivated by this implausibility, the generalised recirculation algorithm will be introduced and its mathematical formulation and properties discussed.

There is an increasing use of nature-inspired computational techniques in computer science. These include the use of biology as a source of inspiration for solving computational problems, such as developments in evolutionary algorithms and swarm intelligence. It is therefore proposed to allow students the opportunity to become exposed to these types of methods for use in their late careers.

The amount of data generated worldwide is more than doubling every year. Traditional data analysis techniques are inadequate for dealing with the vast ocean of data. This module introduces modern techniques, platforms and tools for analysing large data sets efficiently, along with key applications, to equip students to join the new generation of data scientists sought after by industry and academia.

• Information theory and information entropy

• More: it's all data rather than samples

• Messy: it’s disorder/uncertainty rather than accuracy (Chua’s local activity)

• Correlation: it’s correlation rather than causation

• Open Data

• Data ethics: algorithmic transparency, bias, and discrimination.

• Big personal data and data protection

• Linear programming

• Data civilisation: creating tools for pervasive understanding of publicly available data

• Deep learning

• Predictive analytics of sensor/mobile/social networks

• Digital/personal healthcare systems

• Next generation data scientists

This module covers the basic principles of machine learning and the kinds of problems that can be solved by such techniques. You learn about the philosophy of AI, how knowledge is represented and algorithms to search state spaces. The module also provides an introduction to both machine learning and biologically inspired computation.

This module will introduce students to fundamental concepts of functional and concurrent programming, using a suitable language (e.g. Erlang) as a vehicle to put these concepts into practice. The first part of the module will cover basic ideas in functional programming, such as expressions, types, values, lists, pattern-matching and recursion, together with the specific language concurrency model, including process creation, message sending and receiving. Good concurrent design practices will be considered, based on networks of communicating processes (e.g. Actor and CSP models), and avoiding problems such as deadlock, livelock and starvation.

The later part of the module will cover more advanced topics (higher-order functions) and look at alternative concurrency models (e.g. synchronous, channel-based, join-based and shared-memory) and their relationship to the model described in the first part of the module. Alongside this, consideration will be given to the relevance and applicability of functional and concurrent programming for use in real applications.

Students taking this module will undertake one or (typically) more assignments for the Kent IT Clinic (KITC). Each assignment will be of one of three types:

Work on one of KITC’s contracts with an external client. To the extent that client-funded work allows, every student will be given at least one assignment of this type. Wherever practical, a student will be encouraged to participate in the negotiation and pricing of contracts, under the ultimate supervision of KITC management. For each assignment, the student may work on the assignment individually or as part of a group, as directed by KITC. A contribution to the infrastructure of KITC itself.

A contribution to the infrastructure of KITC itself. These assignments work in a similar way to external assignments, but with KITC as the client.

Formulating a costed proposal for the future development of KITC, and presenting reasoned argument in support of the proposal to KITC management, as a candidate for inclusion in KITC’s strategic plan for the following academic year.

This module explores a range of different data mining and knowledge discovery techniques and algorithms. You learn about the strengths and weaknesses of different techniques and how to choose the most appropriate for any particular task. You use a state-of-the-art data-mining tool, and learn to evaluate the quality of discovered knowledge.

This module investigates the whole process of security management. A holistic view of security management is taken, starting with risk management and the formulation of security policies. Technical subjects include a description of the various security models, and showing how authorisation policies can be automatically enforced. The legal and privacy issues associated with information management are also addressed, as are the usability issues of security technologies. Finally, the module concludes by investigating how security has already been inbuilt into some existing applications, and how security issues will effect the uptake of ubiquitous computing systems

Syllabus

Federated identity management: OpenID, SAML, Liberty Alliance, ...

Privacy protection

Viruses and worms

Hacking

Secure architectures

Formal verification methods

E-mail security: SMTP-MIME, S/MIME

Secure software development methods and tools, common criteria, code inspections, code coverage tools, code evaluation tools etc.

Concurrent design and programming skills are of growing importance as multi-core processor technology advances. A sound understanding of fundamental concurrency concepts and obstacles is essential. This module introduces fundamental theories of concurrency. It discusses how designs can be made parallel and identifies the common faults in concurrent programs and how to avoid them. It introduces a range of widely used programming paradigms and techniques for writing concurrent programmes.

Syllabus

Concurrency and parallelism, and their applications to software design.

Identifying parallelisable problems and parallelisation techniques.

Parallel algorithms and how to design them.

Common faults in concurrent and parallel programs.

Complexity, performance measurement and scheduling techniques.

Multi-core and emerging architectures.

Multi-core programming paradigms:

Data-parallel techniques: SIMD, MIMD, vector processing and GPGPUs.

Shared-memory techniques: conventional threads-and-locks, structured parallelism, transactional memory.

Message-passing techniques: process-oriented programming, mailboxes, tuplespaces.

This module provides for well-qualified computer science students entering the MSc programme from a range of backgrounds. These students will have good programming skills but will not necessarily have used Java or another object-oriented language extensively. This module seeks to ensure that students have the Java and object-oriented design skills necessary for the rest of their programme.

This module provides an introduction to object-oriented programming using the popular Java language. It is designed for beginners who have not studied computer programming before. By the end students will be able to develop simple programmes using Java. (Note that students with substantial prior experience of programming take module CO871 Advanced Java for Programmers[1] instead.)

. Computer architecture, operating systems and application software.

•Software development tools (editors, compilers, etc)

•The wider software development process

•Programming paradigms and languages

•The concept of algorithms

•Sequences of statements and order of execution

•Classes, objects and packages (what they are and how to use them)

•Primitive data types, variables and expressions

•Methods and parameters

•Control structures (selection, repetition)

•Input and output

•Coding style and inline documentation

•Online documentation