Shana Moothedath

Postdoctoral Research Scholar, Network Security Lab

Shana Moothedath 

I am a postdoctoral research scholar in Network Security Lab at University of Washington, Seattle supervised by Prof. Radha Poovendran & Prof. Linda Bushnell. I obtained my Ph.D. from Department of Electrical Engineering at Indian Institute of Technology Bombay where I was supervised by Prof. Prasanna Chaporkar & Prof. Madhu N. Belur. My current research is in the intersection of security, control, machine learning, and game theory.

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Curriculum Vitae

Contact

Network Security Lab (Room No. 437),
Department of Electrical and Computer Engineering,
University of Washington,
Seattle, Washington-98195, USA.

Email: sm15@uw.edu
          

Starting in January 2021, I will be an Assistant Professor at Iowa State University, Electrical and Computer Engineering (ECpE) department. I am currently looking for motivated students to work in the areas of control, game theory, security, and learning. If you are interested to join my lab, please send me an email explaining why you are interested and include an updated CV.

Research Interests

  • Control and security of cyber-physical systems

  • Analysis and control of networked systems

  • Game theory

  • Learning and control for secure systems

  • Control and optimization

Educational Background

Instructor for:

  • Autumn 2019: EE 418 Network Security and Cryptography

    The goal of this course is to develop an understanding of the fundamental principles of cryptography and its application to network and communication security. This course will serve as an introduction to the fundamental tools in cryptography and the protocols that enable its application to network and communication security. In details this course serves an introduction to the basic theory and practice of cryptographic techniques used in computer security. We will cover topics such as encryption (secret-key and public-key), digital signatures, authentication of entities, key management, cryptographic hashing, wireless security. The course projects are used to introduce emerging topics such as RFID security, sensor network security, modeling and mitigation of attacks, privacy in social networks.
  • Prerequisites: MATH 308 (linear algebra, matrix) or MATH 390, STAT 390 or IND E 315 (prob. and stats.), or permission from the instructor.

  • List of topics:

    • Introduction to classical Cryptography and Cryptanalysis

    • Motivation and introduction to hash functions

    • The public key cryptography based on discrete logarithms and factorization

    • Digital signature schemes

    • Key distribution

    • Advanced topics including trust establishment in social networks, authentication systems and vulnerability analysis in mutual authentication protocols

    • Security metrics and their usage

Teaching assistant for:

  • 2017-18

    • Autumn: (EE 640) Multivariable Control Systems

    • Spring: (EE 636) Matrix Computations

  • 2016-17

    • Autumn: (EE 640) Multivariable Control Systems

    • Spring: (EE 613) Nonlinear Dynamical Systems

  • 2015-16

    • Autumn: (EE 640) Multivariable Control Systems

    • Spring: (EE 636) Matrix Computations

  • 2014-15

    • Autumn: (EE 101) Introduction to Electrical and Electronics Circuits

    • Spring: (EE 302) Control Systems

Work Experience

  • Research Intern (July 2013 - July 2014) at ISRO, VSSC, Trivandrum.

  • Teaching Assistant (July 2014 - July 2018) at Indian Institute of Technology Bombay.

Publications

Journal Papers

  • Shana Moothedath, Dinuka Sahabandu, Joey Allen, Linda Bushnell, Wenke Lee, and Radha Poovendran, “Stochastic Dynamic Information Flow Tracking Game using Supervised Learning for Detecting Advanced Persistent Threats”, Submitted. [arxiv preprint]

  • Dinuka Sahabandu, Shana Moothedath, Joey Allen, Linda Bushnell, Wenke Lee, and Radha Poovendran, “A Multi-Agent Reinforcement Learning Approach for Dynamic Information Flow Tracking Games for Advanced Persistent Threats”, Submitted. [arxiv preprint]

  • Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran, “Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach”, Submitted. [arxiv preprint]

  • Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran, “A Game-Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats”, IEEE Transactions on Automatic Control. [pdf]

  • Kumar Yashashwi, Shana Moothedath, and Prasanna Chaporkar, “ Minimum Cost Input Selection for Strong Structural Controllability”, Submitted.

  • RaviTeja Gundeti, Shana Moothedath, and Prasanna Chaporkar, “Feedback Robustness in Structured Closed-loop System ”, European Journal of Control. [pdf]

  • Aishwary Joshi, Shana Moothedath, and Prasanna Chaporkar, “Minimum Cost Feedback Selection in Structured Systems: Hardness and Approximation Algorithm ”, IEEE Transactions on Automatic Control. [pdf]

  • Shana Moohedath, Prasanna Chaporkar, and Madhu N. Belur, “Optimal Selection of Interconnections in Composite Systems for Structural Controllability ”, To appear in IEEE Transaction on Control of Network Systems. [arxiv preprint]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “Approximating Constrained Minimum Cost Input-Output Selection for Generic Arbitrary Pole Placement in Structured Systems”, Automatica, vol. 107, pages 200-210, 2019. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “Optimal Selection of Essential Interconnections for Structural Controllability in Heterogeneous Subsystems”, Automatica, vol. 103, pages 424-434, 2019. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “ Sparsest Feedback Selection for Structurally Cyclic Systems with Dedicated Actuators and Sensors in Polynomial Time”, IEEE Transactions on Automatic Control, 2019. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “Minimum Cost Feedback Selection for Arbitrary Pole Placement in Structured Systems”, IEEE Transactions on Automatic Control, vol. 63, no. 11, pages 3881-3888, 2018. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “A Flow-Network Based Polynomial-Time Approximation Algorithm for the Minimum Constrained Input Structural Controllability Problem”, IEEE Transactions on Automatic Control, vol. 63, no. 9, pages 3151-3158, 2018. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “Rapidly Mixing Markov Chain Monte Carlo Technique for Matching Problems with Global Utility Function”. [arxiv preprint]

  • Shana Moothedath , Prasanna Chaporkar, and Madhu N. Belur, “A Maximum Likelihood Based Offline Estimation of Student Capabilities and Question Difficulties with Guessing ”, Perspectives in Education, vol. 34, no. 4, pages 99-115, 2016. [pdf]

Conference Papers

  • Dinuka Sahabandu, Shana Moothedath, Joey Allen, Linda Bushnell, Wenke Lee, and Radha Poovendran, “ Quickest Detection of Advanced Persistent Threats: A Semi-Markov Game Approach”, International Conference on Cyber-Physical Systems (ICCPS), Sydney, Australia, April, 2020.

  • Shana Moothedath, Maryam Fazel, Wenke Lee, and Radha Poovendran, “ Interdiction Games for Advanced Persistent Threats using Dynamic Information Flow Tracking”, Submitted.

  • Dinuka Sahabandu, Shana Moothedath, Joey Allen, Linda Bushnell, Wenke Lee, and Radha Poovendran, “ Stochastic Dynamic Information Flow Tracking Game with Reinforcement Learning”, To appear in the Springer proceedings of Conference on Decision and Game Theory for Security (GameSec), Stockholm, Sweden, October 30-November 1, 2019.

  • Dinuka Sahabandu, Shana Moothedath, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran, “ Dynamic Information Flow Tracking Games for Simultaneous Detection of Multiple Attackers”, To appear in the proceedings of the IEEE Conference on Decision and Control (CDC), 2019.

  • Shruti Misra, Shana Moothedath, Hossein Hosseini, Joey Allen, Linda Bushnell, Wenke Lee, and Radha Poovendran, “ Learning Equilibria in Stochastic Information Flow Tracking Games with Partial Knowledge ”, To appear in the proceedings of the IEEE Conference on Decision and Control (CDC), 2019.

  • Shana Moothedath, Kumar Yashashwi, Prasanna Chaporkar, and Madhu N. Belur, “Target Controllability for Structured Systems”, Proceedings of the European Control Conference (ECC), Naples, Italy, June 25-28, 2019. [pdf]

  • Dinuka Sahabandu, Shana Moothedath, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran, “A Game Theoretic Approach for Dynamic Information Flow Tracking with Conditional Branching”, Proceedings of the American Control Conference (ACC), Philadelphia, USA, July 10-12, 2019. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Aishwary Joshi, “Optimal Network Topology Design in Composite Systems with Constrained Neighbors for Structural Controllability”, Proceedings of the American Control Conference (ACC), Philadelphia, USA, July 10-12, 2019. [pdf]

  • Kumar Yashashwi, Shana Moothedath, and Prasanna Chaporkar, “Minimizing Inputs for Strong Structural Controllability”, Proceedings of the American Control Conference (ACC), Philadelphia, USA, July 10-12, 2019. [pdf]

  • Shana Moothedath, Dinuka Sahabandu, Andrew Clark, Sangho Lee, Wenke Lee, and Radha Poovendran, “Multi-Stage Dynamic Information Flow Tracking Game”, Springer Proceedings of Conference on Decision and Game Theory for Security (GameSec), Seattle, USA, October 29-31, 2018. [pdf]

  • Shana Moothedath, Prasanna Chaporkar, and Madhu N. Belur, “A Randomized Algorithm for the Minimum Cost Constrained Input Selection for State Space Structural Controllability ”, Proceedings of the IEEE European Control Conference (ECC), Limassol, Cyprus, June 12-15, 2018. [pdf]

  • Saurabh Kumar, Shana Moothedath , Prasanna Chaporkar, and Madhu N. Belur, “An MCMC based Course to Teaching Assistant Allocation”, Proceedings of the International Conference on Network, Communication and Computing (ICNCC), Kyoto, Japan, December 17-21, 2016. [pdf]

  • Shana Moothedath , Prasanna Chaporkar, and Madhu N. Belur, “A Maximum Likelihood Based Offline Estimation of Student Capabilities and Question Difficulties”, Proceedings of the 42nd International Association for Educational Assessment (IAEA) Conference, Cape Town, South Africa, August 21-26, 2016. [pdf]

  • Shana Moothedath, Renju Gangadharan and R. Letha Kumari, “On Board Trajectory Optimization of a Launch Vehicle with Splash Down Constraint”, Proceedings of the IEEE International Conference on Magnetics, Machines & Drives (AICERA/iCMMD), Kottayam, India, July 24-26, 2014. [pdf]

Posters

  • Shana Moothedath,Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran “Multi-Stage Dynamic Information Flow Tracking Game for Advanced Persistent Threats”, ONR-MURI Mid-Review Meeting, Washington DC, USA, 2019 and Workshop on Analysis and Control of Complex Networks: State of the Art and Research Directions, American Control Conference, Philadelphia, USA, 2019. [poster]

  • Dinuka Sahabandu, Shana Moothedath,Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran “A Game Theoretic APproach for Resource Efficient Dynamic Information Flow Tracking”, ONR-MURI Mid-Review Meeting, Washington DC, USA, 2019. [poster]

  • Shruti Misra, Shana Moothedath,Hossein Hosseini, Joey Allen, Linda Bushnell, Wenke Lee, and Radha Poovendran “Learning Equilibria in Stochastic Information Flow Tracking Games with Partial Knowledge”, ONR-MURI Mid-Review Meeting, Washington DC, USA, 2019. [poster]

  • Shana Moothedath,Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran “Multi-Stage Dynamic Information Flow Tracking Game for Advanced Persistent Threats”, iREDEFINE Workshop,ECEDHA, Arizona, USA, 2019. [poster]

  • Shana Moothedath,Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, and Radha Poovendran “Multi-Stage Dynamic Information Flow Tracking Game”, Western USA ECE Departments Heads Association (WECEDHA), Seattle, USA, 2018, and Conference on Decision and Control (CDC), Florida, USA, 2018. [poster]

  • Shana Moothedath,Saurabh Kumar, Prasanna Chaporkar, and Madhu N. Belur, “Solving Allocation Problems using Markov Chain Monte Carlo Technique”, Indian Control Conference (ICC), Hyderabad, India, 2016. [poster]

Thesis

  • Shana Moothedath, “Optimizing Structured Linear Time Invariant Systems: Complexity and Algorithms”, PhD Thesis, Dept. of Electrical and Electronics Engineering, Indian Institute of Technology Bombay, 2018. [pdf]