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Advanced Computer Networks & Security

Rationale: With the growing trend of heavy reliance on computer communication networks for

critical research and enterprise services, such as, biology, finance, agriculture, and healthcare, there

is a need to understand such networks for next generation systems design. At the same time, criticality

of the services using these network resources necessitates adoption of sophisticated security

and privacy measures in order to protect both services and networks from cyber-security threats.

Thus, for graduate students, knowledge in advanced computer communications networks and cyber

security is essential for both academic and professional success.
 

Course description: This graduate level course is designed for Computer Science students with

basic knowledge in Digital Communications and Computer Networks, Algorithms, and Statistical

Probability Theory. The students will learn advanced topics in computer networks, such as, wireless

networks, cloud and Big Data networks. Students will gather knowledge on the vulnerabilities

in different types of networks, detection methods, and “state-of-the-art” techniques to prevent

them. The course materials will heavily rely on literature survey which will train the students

on how to search, read, decipher, and evaluate research articles. As part of laboratory exercises,

students will learn how to design simple network simulations, and use distributed testbeds to design

and perform experiments. Finally the students will be expected to take part in group projects

which will exercise their critical thinking and problem solving skills that they gathered through

this course.
 

List of topics: The topics may include but are not limited to:

  • Wireless networks: Mobile communications, WiFi, 4G, Dynamic spectrum access.
  • Cloud and Big Data networks: Network virtualization, Software-defined networking, ScienceDMZ.
  • Security threats: Wireless and cloud network vulnerabilities, Types of threats threats, Risk and impacts, Detection methods (Honeypots, Snort).
  • Defense techniques: Cryptography, Firewalls, Authentication and authorization, DDoS defense,  Trust and reputation.
  • Standard approaches: Moving target defense, Access control schemes (RBAC/ABAC), NIST standards.


Learning objectives: The objectives of the course are:

  • Introduce advance topics of computer networks and security to the students with an eye on future trends.
  • Train the students to develop ‘hands-on’ skills on using various tools and testbeds in order to design network and security experiments/simulations.
  • Engage the students to develop key skills for scientific research, such as, analytical modeling and problem solving, literature survey, scientific writing, and technical presentation.
  • Prepare the students to perform critical thinking, idea generation and implementation, and integration with existing systems when solving real research problems.
  • Foster opportunities for future exploration of open research problems and publications.
     

Assessment: The students’ performance will be assessed based on: a) Homework assignments

(15%) that will test the analytical and problem solving skills, b) Laboratory exercises (20%) that

will introduce large scale distributed network testbeds and teach how to implement their theoretical

research and perform experiments; and c) Two mid-term tests (30%), and d) A course project (35%)

that will engage students to perform original research with the theoretical/experimental knowledge

gathered from the course.