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Pre Requisite Comment

N/A

Co Requisite Comment

N/A

Aims

All computer scientist graduates should have a fundamental understanding of security when designing and implementing modern day software applications. This module explores key security challenges faced by these applications and the security techniques commonly used to manage them. Students will gain first-hand experience in employing secure software practices and implementing security mechanisms to help address those challenges, including the critical evaluation of code produced using modern development tools such as generative AI.

Outline Of Syllabus

•       Security Foundations and Secure Programming
•       Flask Web Application Developments
•       Web Application Security Principles
•       User Registration, Authentication, and Authorisation
•       Input Validation, Injection Attacks, and XXS
•       Session Management and CSRF Protection
•       Error Handling, Logging, and Secure Management
•       Threat Modelling and Secure Design
•       Secure Development Workflows, including AI-assisted code review and AI-related software security risks

Intended Knowledge Outcomes

To be able to:

• Understand the fundamental principles of security.
• Understand the key security challenges faced by software applications.
• Reason about appropriate security techniques used to manage those security challenges.
• Select suitable programming practices when implementing security mechanisms.

Intended Skill Outcomes

To be able to:

• Implement solutions to key security issues using appropriate programming practices, including critically evaluating and correcting flaws in AI-assisted or AI generated code.
• Read and understand code written using different programming languages.
• Expand and extend existing software applications.
• Understand and problem solve programming errors.

Teaching Rationale And Relationship

Lectures present the fundamental theoretical material underpinning secure software development, supporting the intended knowledge outcomes. Substantial practical sessions enable students to develop the intended skills outcomes through hands-on implementation of secure programming techniques within realistic software scenarios. The combination of teaching activities ensures that both conceptual understanding and applied secure programming skills are developed and can be reliably demonstrated.

Assessment Rationale And Relationship

The summative assessment combines coursework (60%) and a controlled digital examination (40%) to assess both applied secure programming skills and individual understanding of core security principles, while maintaining academic integrity in a context where generative AI tools are widely available.

The case study coursework assesses students’ ability to design, implement, analyse, and improve secure software solutions within a realistic application context. It primarily supports the intended skills outcomes by requiring appropriate programming practices, code reading and reasoning, and the identification and resolution of security issues. Students are expected to critically evaluate any AI assisted or AI generated code and remain responsible for the security of their submissions.

The digital exam assesses foundational security concepts and reasoning about secure programming decisions. It supports the intended knowledge outcomes and provides individual verification of learning, ensuring that achievement of the learning outcomes is reliably evidenced even where coursework development may have been assisted by modern tools.

Together, these components provide a balanced and reliable measurement of the learning outcomes, strengthening assessment integrity and AI resilience without altering delivery hours or module scope.

General Notes

N/A