11 citations · 11 across the 4 of their papers we have counts for
6 papers
Adversarial Reinforcement Learning for Detecting False Data Injection Attacks in Vehicular Routing
Taha Eghtesad, Yevgeniy Vorobeychik, Aron Laszka
In modern transportation networks, adversaries can manipulate routing algorithms using false data injection attacks, such as simulating heavy traffic with multiple devices running…
Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks
Taha Eghtesad, Sirui Li, Yevgeniy Vorobeychik +1
The increasing reliance of drivers on navigation applications has made transportation networks more susceptible to data-manipulation attacks by malicious actors. Adversaries may ex…
Bug Hunters' Perspectives on the Challenges and Benefits of the Bug Bounty Ecosystem
Omer Akgul, Taha Eghtesad, Amit Elazari +5
Although researchers have characterized the bug-bounty ecosystem from the point of view of platforms and programs, minimal effort has been made to understand the perspectives of th…
Mechanisms for Outsourcing Computation via a Decentralized Market
Scott Eisele, Taha Eghtesad, Nicholas Troutman +2
As the number of personal computing and IoT devices grows rapidly, so does the amount of computational power that is available at the edge. Since many of these devices are often id…
Adversarial Deep Reinforcement Learning based Adaptive Moving Target Defense
Taha Eghtesad, Yevgeniy Vorobeychik, Aron Laszka
Moving target defense (MTD) is a proactive defense approach that aims to thwart attacks by continuously changing the attack surface of a system (e.g., changing host or network conf…
Safe and Private Forward-Trading Platform for Transactive Microgrids
Scott Eisele, Taha Eghtesad, Keegan Campanelli +3
Transactive microgrids have emerged as a transformative solution for the problems faced by distribution system operators due to an increase in the use of distributed energy resourc…