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PhD_BITS_RMIT 2023__W12 X H16 cm_02 Sept 2023



Ph.D. position in Computer Science & Information Systems are currently available with a full scholarship for students enrolled in a Joint Ph.D. program at the BITS Pilani, and RMIT University, Australia.

Application Deadline: September 26, 2023, for January 2024 intake

How to Apply: Send in your complete application using the following link:

Desirable qualifications: B. Tech/ M.Tech in Computer Science,

Candidates having eagerness to research cyber security, good English writing skills, knowledge of computer networks and distributed systems, ML would be preferred.



For candidates enrolled in a Joint Ph.D. between RMIT University and BITS Pilani:

  • BITS Pilani Ph.D. fellowship:
    • INR 45,800/- per month for student with a higher degree of BITS Pilani or its equivalent
    • INR 42,800/- per month (during course work), INR 45,800/- per month (after coursework completion) for student with an integrated first degree of BITS Pilani or its equivalent
  • Receive a full RMIT tuition fee scholarship for the duration of your enrolment
  • Benefit from the world – class research facilities in India and Melbourne
  • Travel to Australia for up to one year of candidature and be supported by an Australian stipend for the duration of your time in Melbourne.
  • Candidates admitted to the program are jointly supervised by faculty from BITS and RMIT.



Project ID: BITSRMIT100043

Project title: Faster Threat Detection and Malware Analysis in Network Dataplane.

Project Team: Prof. Haribabu Kotakula, BITS Pilani |Prof. Iqbal Gondal, RMIT University, Australia| Prof. Mark Gregory, RMIT University, Australia


Description: The security models at present work on analyzing the packets in the control plane which is more time consuming and the network is compromised by the time the attack is recognized. The traffic could be malicious or non-malicious. The proposed security model analyzes network traffic within the dataplane at the line rate and therefore attack detection and prevention can happen in real-time. Research challenges include deploying ML models in the dataplane, establishing collaborative communication and computation models at the dataplane.  

For more information write to: