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Supervisor: Dr. Talha Ahmed Khan

 

DESIGN AND DEVELOPMENT OF COST-EFFECTIVE AI POWERED FIREWALL

 

Supervisor: Snr. Assoc. Prof. Dr. Talha Ahmed Khan

Campus/School/Dept: Computer Science-BUKC

RAC Approved Supervisor for Research Areas: AI/ML

Supervisory Record:

  • PhD Produced:
  • PhD Enrolled:
  • MS/MPhil Produced:
  • MS/MPhil Enrolled:

 

Topic Brief Description:

This research focuses on creating an affordable, intelligent firewall solution that leverages AI to enhance network security. By integrating machine learning algorithms, the firewall can detect and mitigate cyber threats in real-time, ensuring robust protection against evolving attack patterns. The design emphasizes cost efficiency, making it accessible to small and medium-sized enterprises while maintaining high performance and scalability.

 

Research Objectives/Deliverables:

  1. Develop a cost-effective architecture for an AI-powered firewall tailored for small to medium-sized enterprises.
  2. Design and implement machine learning models to detect and mitigate real-time cyber threats effectively.
  3. Ensure scalability and adaptability of the firewall to accommodate evolving network security challenges.
  4. Evaluate the firewall’s performance in terms of accuracy, speed, and cost-efficiency against existing solutions.
  5. Provide user-friendly configuration and management tools for seamless integration into diverse network environments.

 

Research Questions: 

  1. How can an AI-powered firewall be designed to balance cost-effectiveness and high performance?
  2. What machine learning techniques are most effective for real-time threat detection and mitigation in a firewall?
  3. How can the firewall be made scalable to handle varying network sizes and complexities?
  4. What metrics should be used to evaluate the performance and cost-efficiency of the AI-powered firewall?
  5. How can the firewall’s interface and functionality be optimized for ease of use by small to medium-sized enterprises?

 

Candidate’s Eligibility Profile:

  1. The applicant must have an MS/MPhil/Equivalent degree in electrical engineering with CGPA >0. Besides, applicants must have a strong background in mathematics, optimization theory and related fields.
  2. Experience with programming languages such as Fortran, C/C++, MATLAB, or Python is advantageous. Candidates should thrive in an international environment and have excellent communication skills to actively contribute to team research efforts.
  3. Proficiency in spoken and written English is essential. We value independence and responsibility while promoting teamwork and collaboration among colleagues.
  4. The candidate should have a background in Computer Science, Cybersecurity, or related fields. Proficiency in machine learning, network security concepts, and firewall technologies is essential.
  5. Hands-on experience with programming languages like Python and tools such as TensorFlow or PyTorch is preferred. Knowledge of cost-efficient system design and implementation is an added advantage.