MS1S462 - Mathematical Tools for Computer Forensics and Security 01 Sep 2022 - 31 Aug 2028 | Version 3

Associated Module Information

Module Code: MS1S462
Module Title: Mathematical Tools for Computer Forensics and Security
Faculty: Faculty of Computing, Engineering and Science
Faculty Group: Computing and Mathematical Sciences
Faculty Sub Group: Mathematical Sciences
Module Leader: John Wyburn
Module Team: Stephanie Perkins, Eric Llewellyn
First Intended Intake: SEP 2016 Final Year of Intake:
Date Closed:
Credit Value: 20 Credit Level: 4
Language: English
Percentage of Module Taught in Welsh: 0
Equivalent Module:
HECOS codes: 100403 - mathematics
HECOS Code Weighting: 100

Document Version Information

Version 3
Valid From 01 Sep 2022
Valid To 31 Aug 2028

Module Aims

To provide a knowledge of basic mathematical and statistical concepts in order to underpin the work of parallel and succeeding modules throughout Computer Forensics and Security.

To enable students to solve problems and appreciate differences in problem solving techniques.

To enable students to apply the theory to problems in computing and understand the limitations of the solutions found.

Threats to data security and integrity are quantitative— occurring at discernible frequencies and threatening various specific systems to different degrees. Assessments of threat are statistical. They therefore require quantitative methods to be understood and for counter-measures to be determined. Moreover, cryptography and cryptanalysis are applied mathematics, demanding a practical knowledge of number theory and problem solving. Therefore, a student needs a substantial repertoire of mathematical knowledge and tools in order to address issues of cybersecurity. The module is a prerequisite of Cryptography MS2S562.

Content Summary

Sets: basic concepts, power sets, set operations, basic laws, number sets.

Number theory: Properties of number, integers, primes, Mersenne primes, primality testing. Divisors and multiples. Modular arithmetic. Fast exponentiation. Euler’s totient function, Euclid's algorithm, Euclid's extended algorithm.

Complexity: Landau notation (big-O), hard problems.

Matrices and determinants; use in cryptography and problem-solving: solution of linear equations, application in 2 and 3 dimensions.

Random and pseudo-random numbers: generation of random numbers, methods of pseudo-random number generation, testing randomness.

Statistics: Presentation of data, measures of location and dispersion, cumulative frequency, inter-quartile range. Regression and correlation. T-test for difference in mean independent samples, and paired data and chi squared tests.

Probability: Introduction to probability theory; the normal, binomial and Poisson distributions.

Risk: Definitions (generic vs security risk), quantitative risk, risk leverage.

Excel: applications of spreadsheet techniques to address statistical analyses and problems.

Complex Numbers: the imaginary operator, complex solutions to quadratic equations, arithmetical operations on complex numbers, the Argand Diagram. Introduction to quantum computing applications of complex numbers.

Learning and Teaching Methods

Activity Type Hours
Lecture 24
Practical classes and workshops 24
Independent Study 80
Directed Study 72
Total Hours Selected 200

Learning Outcomes

# Learning Outcome
LO1 To provide a knowledge of basic mathematical and statistical concepts in order to underpin the work of parallel and succeeding modules throughout Computer Forensics and Security.Apply a range of mathematical and statistical problem solving techniques, and interpret the solutions appropriately.

Module Requisites

N/A

Assessment Criteria

Assessment Category Assessment Type Description Duration Word Count Weight (%) Best of? Pass Mark
Asynchronous Assessment Practical Coursework 1 (Asynch) Coursework 0 N/A 50 No 40
Synchronous Online Assessment Classroom Test - Time Constrained (Online) 1 Open Book Test 70 N/A 50 No 40

Assessment Matrix

Assessment Type Learning Outcomes
LO1
Practical Coursework 1 (Asynch)
Classroom Test - Time Constrained (Online) 1

Reading List

Makinson, D. (2012) Sets, Logic and Maths for Computing. London: Springer-Verlag. ISBN-10:1447124995

Witte, R.S. and Witte, J.S. (2021) Statistics. 11th edn. New York: Wiley. ISBN-10:1119254515

Jarvis, F. (2014) Algebraic Number Theory. London: Springer Undergraduate Mathematics Series ISBN-10:9783319075440