PENG9550 Cloud Computing and Security Emneplan

Biomedical engineering includes medical electronics, medical imaging systems, modeling of biological systems, analytical measurements methods, working mechanisms and applications of medical devices and equipment. This course aims to familiarize and expand the expertise of the students with the theoretical and practical considerations relevant to the design and development of most advanced and available methods, tools, and systems in medical diagnostics. It will also provide an overview of important applications for diagnostic procedures that will include modelling of organs and tissues, developing diagnostic applications, and the advanced medical equipment.

The course will be offered once a year, provided 3 or more students sign up for the course. If less than 3 students sign up for a course, the course will be cancelled for that year.

Pass or fail.

Students who complete the course are expected to have the following learning outcomes, defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of the course, the student:

• has a deep understanding of how cloud computing, large services and infrastructures play a crucial role in todays digitised society;
• has an interdisciplinary view on cloud computing due to its central role in the digitised society;
• understands the fundamental principles of distributed computing and particularly cloud computing;
• understands the importance of virtualisation in distributed computing and how this has enabled the development of cloud computing;
• understands the business models that underlie cloud computing;
• has an understanding of the architecture and concept of different cloud models: IaaS, PaaS, and SaaS;
• is knowledgeable in the various methods available to monitor and evaluate cloud infrastructure;
• has a deep knowledge of the common security issues in the field of cloud computing;
• has an understanding of the concept of threat intelligence in the field of cloud computing;
• understands the use of security policies as part of the overall security strategy of an organization;

Skills

On successful completion of the course, the student can:

• design highly distributed digital systems.
• create virtual machine images and deploy them on a cloud.
• design and develop scalable cloud-based applications by creating and configuring virtual machines in the cloud.
• analyse cloud infrastructures with regard to properties such as resilience, security, performance and manageability.
• identify cloud security weaknesses by recognising and discovering threats and vulnerabilities to cloud computing.
• implement cloud features to secure and harden the infrastructure.
• use tools to monitor and evaluate cloud infrastructure.
• use tools to analyse system logs to detect possible security or performance problems.

General competence

On successful completion of the course, the student:

• can discuss his/her area of expertise with a non-expert audience by combining insights across disciplines.
• can discuss and debate the impact of technological development on our society in the future

The course describes the important enabling technologies of cloud computing, explores state- of-the art platforms and existing services, and examines the challenges and opportunities of adopting cloud computing. Moreover, the course investigates how to protect the critical data increasingly being stored in the cloud. The students learn how to build a security strategy that keeps data safe and mitigates risk.

Admission requirements.

Students who complete the course are expected to have the following learning outcomes, defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of the course, the student in depth knowledge:

• Identify contemporary issues and challenges in healthcare delivery in particular diagnostics.
• Identify unmet biomedical and/or healthcare needs and apply engineering and life science principles for designing appropriate solutions.
• Apply appropriate engineering and analytical principles to decipher, understand, and describe situations and problems in living systems.
• Describe the key design considerations relevant to the development of diagnostics.
• Describe the experimental tools and techniques used in diagnostic applications.

Skills

On successful completion of the course, the student can:

• Solve quantitative problems in living systems using appropriate engineering and analytical concepts and calculations.
• Collect, analyze, and critically evaluate experimental data.
• Define the technical and practical factors that influence the performance of diagnosis.
• Design solutions to current unmet biomedical and healthcare needs, taking into account key technical and practical considerations.

General competence

On successful completion of the course, the student can:

• Communicate technical information clearly and concisely in oral and written form.
• Demonstrate effective technical and scientific communication skills through the execution of various laboratory modules and projects.
• Read scientific journal papers with a cross-disciplinary approach.

Oral exam, 30 minutes per student.

The oral exam cannot be appealed.

None.

Individual assignment (report) counts for 70% of the final grade, and oral presentation of selected material (30 minutes per candidate) that counts 30 % of the final grade. Review assignment of report on a chosen subject, maximum 10 pages. To be submitted no more than two weeks after the end of the course.

Both individual assignment (report) and oral presentation must be passed in order to pass the course. The oral presentation cannot be appealed.

None.