Cryptography is about communication in the presence of an adversary. It encompasses many problems such as encryption, authentication of the user, authentication of the message, key distribution. The field of modern cryptography provides a theoretical foundation based on which we may understand what exactly these problems are and how to deal with them. "Modern cryptography" is an introductory course on cryptographic primitives and algorithms to provide necessary security goals. This course focuses on a general introduction of classical cryptography, conventional cryptographic systems, mathematical background of cryptography, modern cryptographic primitives including block cipher, stream cipher, hash function, key management, public-key cryptography, digital signature. The course also includes a brief overview of public key infrastructure and contemporary aspects of cryptography such as lightweight cryptography and quantum cryptography. Through this course's learning, the students can obtain some basic knowledge of conventional and modern cryptography and get an in-depth understanding of the basic principles and algorithms of modern cryptography. At the end of this course, students are expected to identify and implement appropriate industry-standard cryptographic techniques to address different information security goals.
This course introduces students to the fundamentals of cybersecurity, including policies, security management, operations, and technical issues. Students will learn the basics of secure networks, software, and communication technologies, as well as the role of management, planning, and improvement strategies. By the end, students will be able to identify and assess vulnerabilities, and manage security risks using industry-standard policies and controls.
This course introduces students to the basic concepts and the methods of probability and statistics. It covers various topics on probability and statistics, including conditional probability, random variables and distributions, expectation, typical distributions, stochastic processes, estimation, testing hypotheses, categorical data and nonparametric methods, and linear statistical models. This course allows the students to solve the basic problems encountered in various fields and to acquire the mathematical knowledge and skills to follow more advanced course.
We look at the details of Hadoop, Storm and related tools that provide SQL-like access to unstructured data: Pig and Hive. We analyze so-called NoSQL storage solutions like HBase, Cassandra, and Oracle NoSQL, for their critical features: speed of reads and writes, data consistency, and ability to scale to extreme volumes. We will introduce the VM technique used in the data centres. We will also investigate the data deduplication and NVM techniques to reduce the data volume and speed up processing. A large section of the course is devoted to the methods of statistical analysis and case studies. We work with Open Source frameworks and other statistical tools. A part of the course is devoted to the public Cloud as a resource for big data analytics.
This course discusses common network attacks and defence technologies. It covers in-depth methodologies, techniques, and tools to identify vulnerabilities, exploit, and assess security risk to networks, systems, and applications. Various defence strategies and mechanisms for mitigating the security attacks are covered as well. Completion of this course will help the students to learn about methodologies and hands-on practices of conducting penetration tests. Students will also learn to identify existing solutions for security protections.
This course focuses on modern techniques and tools for collecting and analyzing network traffic workloads as traditional intrusion detection and logfile analysis are no longer enough to protect today's complex networks. The students will mainly learn to examine the process of collecting and organizing network data, utilize various tools for traffic analysis, and an exposition to the graphing techniques will be given in order to cover the gap between the security specialists and the graphing specialists.
This course requires the students to produce a Final Year Project. The supervisor will guide the student under his or her supervision in the process of completing the final year project. The students shall log their research activities accordingly and consult their respective supervisor regularly. The students are expected to be independent in completing their final year project at the end of the course.
Blockchain Technology
Monday 9.00am-12.00pm (A1#110)
Mahdi H. Miraz
Cryptanalysis is an essential part of cryptology. It is the study of analyzing crypto-systems to understand how they work and to determine any weaknesses in cryptographic algorithms that may leak information. This course focuses on basic mathematics involving cryptanalysis, basic theory and history of cryptanalysis, and typical cryptanalysis techniques for classical cryptography, symmetric cryptography, and public-key cryptography. Through the teaching and practice of this course, students will have a deeper understanding of the principles of some attack techniques that are commonly used for the security analysis. It lays the foundation of basic knowledge and implementation experience for students to engage in research and engineering related to cryptography and network security in the future.
Linear algebra is an indispensable course for any programmes in computing, mathematics, science, engineering, and business. It has wide applications in various disciplines. This course includes the study of systems of linear equations, matrices, determinants, vectors, vector spaces, linear transformations, inner products, eigenvalues, eigenvectors, symmetric matrices and quadratic forms. Students of this course will master properties of matrices and acquire the basic techniques of linear algebra which are useful for further study in various fields.
This course prepares cyber security students for a background in abstraction, notation and critical thinking for the mathematics most directly related to computer science. Topics covered include: logic, arguments, sets, functions, matrices, number theory, counting techniques, pigeonhole principle, permutations and combinations, relations, graphs, Euler paths, Hamiltonian paths, trees, spanning trees, Boolean algebra. Students will be able to discuss and apply the methods of discrete mathematics for various problems in computer science. Students will have the mathematical basis required in subsequent courses, such as design and analysis of algorithms, modern cryptography and so on.