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Advancing Computer Security and Biomolecular Network Research at GWU

Dr. Rahul Simha from the Department of Computer Science at The George Washington University leads innovative research in computer security and biomolecular networks. His work addresses the threats posed by hackers through code understanding, tampering, and various attack methods. Dr. Simha explores the potential of compilers and reconfigurable FPGA hardware to enhance software protection. Additionally, his studies on hypoxia networks aim to model gene regulation using mathematics. Collaborating with experts in various fields, he investigates complex systems, embedded technologies, and their real-world applications.

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Advancing Computer Security and Biomolecular Network Research at GWU

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  1. Research Areas: Computer Systems, Complexity, Biomolecular Networks RAHUL SIMHA Department of Computer Science The George Washington University Washington, DC 20052 simha@gwu.edu 202-994-7181

  2. Motivation: Computer Security What hackers do: Code understanding: to duplicate, steal ideas, prepare attacks Code tampering: to circumvent checks, cause attacks Others: data tampering, authorization attacks, buffer-overflow I can understand the code Now I can modify the code

  3. Software Security/Protection • Computer security research • Crypto, protocols, policy, intrusion detection • Related areas: data mining, signal processing, networking … • Our approach: • How can compilers be used to protect software? • Exploit reconfigurable (FPGA) hardware • Tools to manage security/performance tradeoff. • Collaboration with: Bhagi Narahari (CS) Secure compiler Source code Secure executable

  4. Biomolecular Networks • Hypoxia network • 23 molecules (e.g., HIF, PH, VHL) • Unusual effect: sharp response to oxygen • Our goal: explain using mathematical (ODE) models • Boolean network models: • Gene-regulation network • Explore fundamental properties • Collaboration with: Frank Turano (Bio), Chen Zeng (Physics)

  5. Other research interests • Complex Systems • Phase transitions in complex systems • How and why does complexity arise? • Embedded Systems • Sensor networks, databases • Energy consumption (low power applications) • Smart-home medical applications • Patient monitoring • Robotics for in-home care

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