Modules

Module title: Scripting for Cybersecurity and Networks
SCQF level: 08:
SCQF credit value: 20.00
ECTS credit value: 10
Module code: CSN08114
Module leader: Petra Leimich
School School of Computing
Subject area group: Cyber Security and Networking
Prerequisites

Module Code SET07102
Module Title Software Development 1
Examples of Equivalent Learning Good understanding of fundamental programming concepts
2019/0, Trimester 1, Face-to-Face,
Occurrence: 001
Primary mode of delivery: Face-to-Face
Location of delivery: MERCHISTON
Partner:
Member of staff responsible for delivering module: Petra Leimich
Module Organiser:


Learning, Teaching and Assessment (LTA) Approach:
Key concepts will be explained in lectures, where the subject matter will be illustrated with examples and interactive demonstrations (LO1,2,3). Where possible, students should bring to the lectures a laptop, tablet or mobile phone with Python installed so that they can try out small examples themselves. A key feature is to present the principles behind the applications (LO1,2,3), discuss the concepts with the students (LO1,2,3) and, for each case study, discuss a starting solution and suitable approaches (LO2).
Practical labs focus on problem solving and case studies to provide practice in the application of theory (LO1,2,3). Students develop their own applications, initially often by extendinga starting solution provided. As the module progresses, this will gradually require more independent work and research of advanced concepts. Throughout the labs, students will be encouraged to interact with staff and peers to explore concepts in depth and receive feedback on their progress and understanding.
In addition to timetabled classes, students should undertake private study to work through the learning materials and gain further practice at solving conceptual and technical problems (LO1,3).
To provide an integrated understanding of the subject matter, each topic area will centre on a case study relevant to the students' subject area. topics will reuse and integrate functions and modules developed earlier and emphasise exception handling (LO2).
Mathematical and statistical concepts will be the focus of several weeks of delivery and aspects of this will be woven into the delivery throughout the module, particularly in case studies (LO3). Moodle will be used to distribute course materials including starting solutions and to point the students to selected third party resources.
Formative Assessment:
Interactive elements of lectures encourage students to test their understanding continuously. There will be additional formative challenges such as quizzes. Continuous feedback is given by staff through discussions in the labs.
To support the first summative assessment, a practice test will be available with immediate, automated feedback.
The second assessment will be based partly on earlier lab exercises, for which feedback is available during the practicals.
Summative Assessment:
The first assessment is a class test designed to cover most of the fundamental theory of the module. This focusses on understanding and application of knowledge rather than fact-based recollection. The test will include 20 questions, using short answer and related styles. As understanding is the key measure, the test is open-book. The test is carried out in a supervised lab using Moodle. LO1-3.

The practical skills assessment requires the students to submit their scripts as solutions to a case study and requires the students to apply and integrate many of the concepts learned. The assessment is marked during a one-to-one demo with staff (15-20 minutes). This ensures that the student has a good understanding of their code; it also allows them to highlight notable features and provides a setting where detailed specific feedback is discussed. A summary of the feedback is recorded in moodle using a set of rubrics tailored to emphasise the specific skills assessed. LO1,2,3.
Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)
Face To Face Lecture 24
Face To Face Practical classes and workshops 24
Face To Face Demonstration 0.5
Independent Learning Guided independent study 151.5
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words
Class Test 50 1,2,3 8 HOURS= 1.5, WORDS= 0
Practical Skills Assessment 50 1,2,3 14 HOURS= 30, WORDS= 0
Component 1 subtotal: 100
Component 2 subtotal: 0
Module subtotal: 100

Description of module content:

12. Module Content

The aim of the module is to deepen the students' understanding of fundamental programming concepts and introduce more advanced concepts for applications development. Throughout the module, the concepts will be contextualised through case studies relevant to the students' programmes of study, namely cybersecurity, digital forensics and networking. Additionally, the module integrates some fundamental aspects of mathematics, particularly discrete maths, which are important in Computing and Cybersecurity. Python is used throughout as this is a general purpose programming and scripting language which is used extensively in computer security and related fields.
The syllabus includes topics such as:
• Introduction to Python and Building Applications using a general purpose scripting language
• Functions, Modules, packages and libraries
• Coding and scripting techniques including Exception handling, Testing and Debugging
• • Working with external data and applications (e.g. text files, databases, network traces)
• Algorithms, including examples such as searching and sorting
• Measuring the efficiency of algorithms - theoretically (Big-O) and practically (e.g. by timing code)
• Mathematical and stochastic concepts including permutations, sampling and randomness, and generation of random numbers and assessment of their suitability in cryptography

Example case studies:
• Encryption and Decryption using a simple algorithm such as Caesar cipher;
• Cracking passwords with the use of rainbow tables;
• Web reconnaissance – e.g. scraping email addresses and links from websites;
• Network traffic analysis – working with network logs to extract traffic patterns, mapping the geolocation of IP addresses.
•Comparison of the performance of several algorithms, e.g. spell-checking.
Learning Outcomes for module:

Upon completion of this module you will be able to
LO1: Design, implement and test substantial Python scripts to solve problems in Computer Security, Networking and Digital Forensics.
LO2: Employ good practice programming and scripting techniques to develop well-written modular code which is reusable, well documented and uses comprehensive error handling techniques.
LO3: Demonstrate the application of discrete mathematics concepts to problem solving in Computing.
Indicative References and Reading List - URL:
Scripting For Cybersecurity and Networks
 

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