Applied Cryptography and Trust
(
CSN11131
)
The focus of this module is to provide a core understanding of the fundamental areas of cryptography, identity, and trust. A key feature is to cover both the theoretical areas, while often demonstrating practical applications including key protocols. The module key areas are:• Privacy, and Cryptography Fundamentals (Confidentiality, Sec Models, Cipher types) • Asymmetric Key Encryption. Including RSA and Elliptic Curve Cryptography (ECC).• Symmetric Key Encryption. Including AES and associated modes.• Hashing and MAC Methods. Including MD5, SHA-1, SHA-256, SHA-3 and PBKDF2.• Security Protocols: HTTPS, SSL/TLS, DNSSec, IPSec, WPA • Key Exchange. Diffie-Hellman Method, ECDH.• Trust Infrastructures. Digital Certificates, Signatures, Key Distribution Centres (Kerberos), OAuth • Identity and Authentication (Passwords, Authentication tokens, Key pair identity, Multi-factor, Biometric Authentication).• Distributed Systems: Blockchain, Distributed Ledgers and Cryptocurrency. Smart Contracts, Data Tokenization, and Transactions.• Future Cryptography: Zero Knowledge Proof, Homomorphic Encryption, Light-weight cryptography, and Quantum robust methods.• Host and Domains: Trust systems. Authentication with Active Directory Authorisation: Log integration and rights.
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Computer Penetration Testing
(
CSN11127
)
This module will cover a range of elements concerned with digital penetration testing and security testing. Initial lectures consider important soft skills such as documentation techniques, reporting, the law, and risk assessment and management. The practical skills and their related theoretical knowledge include operating system weaknesses, information gathering (both passive and active), and various ethical hacking techniques and processes. Considerable practical focus is made on available tools to assist in auditing and penetration testing. Aspects targeted include operating systems, common network services, and network-based applications.
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Host-Based Forensics (DL)
(
CSN11126
)
This module will cover elements of operating system disk-level architectures, such as Windows and Linux. This will allow students to study how operating systems store system and user data, and thus students will gain an understanding as to what information could technically be held on such systems. This data could include user files, as well as user activities such as login session data, browsing histories, operating system manipulation, and general user interactions with a variety of operating system tools. This understanding will be expanded through theoretical knowledge and practical exercises in extracting information from systems, using a variety of open source and commercial forensic analysis tools, and documenting the results of such a process using consistent and thorough evidential procedures. This includes the production of event timelines, as well as the analysis of system logs, operating system state, file systems, and application data. The module will also consider the ethical and professional issues related to digital forensics.
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Incident Response and Malware Analysis
(
CSN11129
)
The aim of the module is to develop a deep understanding of advanced areas related to security and live/network forensics, with a strong focus on virtualised and Cloud-based environments that will allow graduates to act professionally within incident response and in malware/threat analysis. An outline of the main areas includes:• Threat Analysis. This involves an in-depth analysis of a range of current threats, such as DDoS, Botnets, trojans, and so on.• System Architectures, Services and Devices. Networked infrastructures (Servers/Firewall/IDS/ Syslog). • Network Forensics. Advanced Network Protocol Analysis, Advanced Trace Analysis, IDS Signature Detection, and Security Threat Network Traces.• Live Forensics. Code Analysis, Host/Network Analysis, Reverse Engineering. Mobile/x86 architecture, Machine Code Analysis, Vulnerability Analysis, Sandboxed Analysis.• Log Capture/Analysis, and Time-lining. Creating large-scale data infrastructure and analysis methods such as Big Data, SIEM and cross-log analysis (such as Splunk).• Malware Analysis. Static/Dynamic Analysis. Disassembly. Obfuscation. Behaviour Analysis. Encoding methods.• Data Hiding and Data Loss Detection/Prevention. Data hiding methods, detection methods, tunnelling, and disk encryption.• Host Investigation Evidence Gathering: Windows, Linux, Android and Mac OS.• Current Related Research.
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Masters Dissertation
(
SOC11101
)
The work for this module comprises the completion of an individual research project. Each student is assigned a personal Supervisor, and an Internal Examiner who monitors progress and feedback, inputs advice, examines the dissertation and takes the lead at the viva. There are two preliminary deliverables prior to the submission of the final dissertation: (1) Project proposal (2) Initial Report including time plan and dissertation outline
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Network Security (D/L)
(
CSN11118
)
The aim of this module is to develop a deep understanding and provide with hands-on implementation experience of network security concepts. A focus has been made on discussing networking fundamentals and implementation in first half of the module. Considerable content in second part of the module has been focused on Artificial Intelligence (AI) and Machine Learning (ML)-based solutions in the cybersecurity domain. Developing exemplar AI models in practical for achieving security measures allow students to professionally design, implement, and analyse AI-based cybersecurity strategies. An outline of the main areas includes:• Introduction to network security and challenges: It focuses on discussing various network threats and attacks that can compromise the network security. Discussion then diverts to network defence strategies, for example, perimeter and defence-in-depth.• Access Control and Authentication: This lecture focuses on introducing and discussing various types of traditional centre of gravity of computer security, the “Access Control”. The list of concepts in this lecture covers trust and identity, attacks, models – access control models, network device access control, AAA, Layer 2, device hardening.• Firewalls: In this part of module, a discussion around different types and existing technologies of firewall is presented. Students get an opportunity to implement and deploy the concepts, such as host-based or network-based firewall, static packet filtering, stateful packet filtering, and multilayer firewall in the lab environment. • Fundamentals of Cryptography and Remote Access VPN: Fundamentals of encryption, decryption, and authentication are touched before diving deeper in developing remote access and Virtual Private Networks (VPNs) for network security, while also covering types (L2, L3 and L4/5) and technologies (IPSec and SSL).• Artificial Intelligence and Machine Learning: Discussion here covers introduction to various learning techniques including supervised, unsupervised and reinforcement learning in terms of various application domains, i.e., classification, regression and clustering.• Introduction to machine learning models: Various AI models are introduced and implemented including neural network, linear regression, k-means clustering, support vector machine, random forest, decision tree, deep neural network.• Data-Driven Cybersecurity: Intrusion Detection Systems (IDS) vs Intrusion Detection and Prevention Systems (IDPS) are introduced in terms of types, alert monitoring and sensor tuning; behavioural analysis, in-line vs out-of-line IDS/IDPS. Practical provides an opportunity to applying AI techniques to real-world intrusion detection problems. • Relevant state-of-the-art research in the domain: Discussions around recent research advances in the fields of network security and cybersecurity.
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Security Audit & Compliance
(
INF11109
)
The aim of the module is to let you develop a deep understanding of the framework that information security operates in, and to give you an opportunity to express this in the form of professional written reports. Topics covered include: • The relation between governance models and frameworks including: ISACA’s COBIT and ISO Standards (ISO27000 in particular) • Overview of relevant laws and regulations: national and international, covering privacy, computer misuse and other legal issues. • The role of organisation and human factors in ensuring a secure environment• The role of the professions; difference between audit, forensics and security management. Professional ethics and codes of practice• Information security risk management and controls including, contingency and continuity planning
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* These are indicative only and reflect the course structure in the current academic year. Some changes may occur between now and the time that you study.