Sriharsha Etigowni

Sriharsha Etigowni

Post Doctoral Research Associate

Purdue University

I am a post doctoral research associate at Purdue computer science pursec lab. I earned a Ph.D. in Computer Engineering from the Rutgers University in 2020, where I was advised by Saman Zonouz.

My research investigates security problems that arise due to the interaction of cyber and physical systems. Through program analysis and physics invariants my research seeks to improve security of industrial control systems and drones.

Interests
  • Cyber Physical Security
  • Embedded Security
  • Industrial Control Systems
Education
  • PhD in Cyber Physical Security, 2020

    Rutgers University

Experience

 
 
 
 
 
Intern - Software Engineering for Cyber Security
Siemens Corporate Technology
May 2017 – Aug 2017 New Jersey, USA
Modelled and developed security aware communication between autonomous production machines. Implemented Automated Industrial control systems (smart plant) and dynamic security capability activation and deactivation in the context of authentication, integrity, confidentiality, and non-repudiation.
 
 
 
 
 
Software Engineer
Robert Bosch
Jun 2011 – Jul 2014 Bangalore,India and Stuggart,Germany
Developed device drivers for the ASIC used in NOx sensor control unit and developed plant software (End of Line) for NOx sensor control unit. Developed complete software for modeswitch, which was innovated to change the operating state of control devices using pulse amplitude modulation. Developed base and post production software for NOx sensor control unit according MISRA guidelines. Developed EEPROM drivers, EEPROM coordinator for STM8 microcontroller and SAE J1939 communication protocol drivers.

Publications

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(2021). Physics-Aware Security Monitoring against Structural Integrity Attacks in 3D Printers. In DSN.

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(2021). Analytic corrective control selection for online remedial action scheme design in a cyber adversarial environment. In IET CPS.

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(2020). Forensic Investigation of Industrial Control Systems Using Deterministic Replay. In CNS.

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(2019). Fast Generation Redispatch Techniques for Automated Remedial Action Schemes. In ISAP.

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