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Module Descriptor School of Computer Science and Statistics

Module CodeCS4407
Module NameSecurity and Privacy
Module Short Title
ECTS5
Semester TaughtHT
Contact Hours

3 lecture hours per week

Module PersonnelDr Stephen Farrell
Learning Outcomes

On successful completion of this module a student will be able to:

NS5LO1 discuss information security and demonstrate an understanding of the context in which information security operates in terms of safety, environmental, social and economic aspects;

NS5LO2 analyse, assess and choose among techniques for mitigating important privacy threats through appropriate security controls, namely the application of cryptographic primitives;

NS5LO3 assess both the risks and threats associated with data security, and assess how the relevant legislative and regulatory frameworks apply;

NS5LO4 reason about issues of privacy with respect to data release.

Learning Aims

The objectives of this module are: to develop an in-depth understanding of risk, data privacy, threats and risks of security breaches, an awareness of computer security (cryptographic) and protocol techniques, and an ability to make appropriate decisions about securing data.

Module Content

Specific topics addressed in this module include

  • Cryptography
    • Symmetric Key Crypto - DES and AES
    • Asymmetric Key Crypto - RSA, DLP, ECC
  • Privacy
    • Privacy Laws Around the World
    • US and EU Data Protection Laws
    • Machine readable terms and conditions
    • User control over privacy settings
  • Internet Security and security standards
    • X.509 Certificates and Public Key Infrastructure
    • Transport Layer Security (TLS)
  • Authentication
    • Two-Factor Authentication
    • Biometrics
  • System and Network  Security
  • Social Networks and Privacy
  • Threats
    • Malware, SQL Injection and Cross-Side Scripting Attacks
    • Buffer Overflows
    • Botnets
Recommended Reading List
Module Prerequisites
Assessment Details

Coursework 20%

Examination 80%

Assessment in the Supplemental session will be based on 100% exam.

Module Website
Academic Year of Data2017/18