Predoctoral Ph.D. Student Researcher
This opportunity is to host one Ph.D. student for few (3-6) months to join our Mobile CPS research group at Texas State.
Project Description:
Cyber-Physical Systems (CPSs) with mobile nodes are emerging as critical systems with tremendous
potentials in impacting our daily lives. As these systems integrate into our physical world, ensuring their
safe and secure operations become crucial goals. This project aims to identify new classes of attacks specially stealthy ones that are likely to appear in the near future, and to develop the proper defense mechanisms to prevent, detect and mitigate them. To achieve this goal, the proposed work falls along two main thrusts: (1) identifying attacks and (2) developing defense mechanisms. Along the first thrust, attackers solve Markovian Decision Processes (MDP) problems, through reinforcement learning algorithms, to identify optimal and suboptimal attack policies. Attacks are assessed through different instantiations of damage and cost metrics. Along the second thrust, novel randomization controllers and randomization-aware anomaly detection methods will be developed to defend against attacks that are mounted based on the state of the system. The project is focused on autonomous vehicles (e.g., robots) and intelligent transportation systems.
Eligibility:
- A Ph.D. student in Computer Science, Electric Engineering or a closely related field.
- Strong AI background with research activities involving MDP and POMDP problems.
- Networking background is a plus.
Benefits:
- Compensation is $4,000 per month.
- Explore new areas and methodologies for finding optimal/suboptimal solutions to a wide range of problems in the Mobile CPS area.
- Ability to mentor a number of undergraduate students.
To apply, please submit your resume by email to msg@txstate.edu. Selection will be based on academic achievements and research alignment with ongoing research projects. Priority will be given to those who have completed their Ph.D. course work.