Radha Poovendran

research

∙ 04/04/2023

Risk-Aware Distributed Multi-Agent Reinforcement Learning

Autonomous cyber and cyber-physical systems need to perform decision-mak...

0 Abdullah Al Maruf, et al. ∙

research

∙ 01/11/2023

Electric Vehicles Security and Privacy: Challenges, Solutions, and Future Needs

Electric Vehicles (EVs) share common technologies with classical fossil-...

0 Alessandro Brighente, et al. ∙

research

∙ 12/03/2022

LDL: A Defense for Label-Based Membership Inference Attacks

The data used to train deep neural network (DNN) models in applications ...

0 Arezoo Rajabi, et al. ∙

research

∙ 08/04/2022

Identity-Based Authentication for On-Demand Charging of Electric Vehicles

Dynamic wireless power transfer provides means for charging Electric Veh...

0 Surudhi Asokraj, et al. ∙

research

∙ 07/13/2022

Game of Trojans: A Submodular Byzantine Approach

Machine learning models in the wild have been shown to be vulnerable to ...

0 Dinuka Sahabandu, et al. ∙

research

∙ 05/20/2022

Vulnerability Analysis and Performance Enhancement of Authentication Protocol in Dynamic Wireless Power Transfer Systems

Recent advancements in wireless charging technology, as well as the poss...

0 Tommaso Bianchi, et al. ∙

research

∙ 04/13/2022

A Natural Language Processing Approach for Instruction Set Architecture Identification

Binary analysis of software is a critical step in cyber forensics applic...

0 Dinuka Sahabandu, et al. ∙

research

∙ 03/25/2022

Trojan Horse Training for Breaking Defenses against Backdoor Attacks in Deep Learning

Machine learning (ML) models that use deep neural networks are vulnerabl...

0 Arezoo Rajabi, et al. ∙

research

∙ 03/18/2022

Privacy-Preserving Reinforcement Learning Beyond Expectation

Cyber and cyber-physical systems equipped with machine learning algorith...

0 Arezoo Rajabi, et al. ∙

research

∙ 03/10/2022

EVExchange: A Relay Attack on Electric Vehicle Charging System

To support the increasing spread of Electric Vehicles (EVs), Charging St...

0 Mauro Conti, et al. ∙

research

∙ 02/19/2022

Shaping Advice in Deep Reinforcement Learning

Reinforcement learning involves agents interacting with an environment t...

0 Baicen Xiao, et al. ∙

research

∙ 01/12/2022

Agent-Temporal Attention for Reward Redistribution in Episodic Multi-Agent Reinforcement Learning

This paper considers multi-agent reinforcement learning (MARL) tasks whe...

0 Baicen Xiao, et al. ∙

research

∙ 03/29/2021

Reinforcement Learning Beyond Expectation

The inputs and preferences of human users are important considerations i...

0 Bhaskar Ramasubramanian, et al. ∙

research

∙ 03/29/2021

Shaping Advice in Deep Multi-Agent Reinforcement Learning

Multi-agent reinforcement learning involves multiple agents interacting ...

0 Baicen Xiao, et al. ∙

research

∙ 03/29/2021

Scalable Planning in Multi-Agent MDPs

Multi-agent Markov Decision Processes (MMDPs) arise in a variety of appl...

0 Dinuka Sahabandu, et al. ∙

research

∙ 01/08/2021

Adaptive Learning in Two-Player Stackelberg Games with Application to Network Security

We study a two-player Stackelberg game with incomplete information such ...

0 Guosong Yang, et al. ∙

research

∙ 09/20/2020

Safety-Critical Online Control with Adversarial Disturbances

This paper studies the control of safety-critical dynamical systems in t...

0 Bhaskar Ramasubramanian, et al. ∙

research

∙ 07/27/2020

Privacy-Preserving Resilience of Cyber-Physical Systems to Adversaries

A cyber-physical system (CPS) is expected to be resilient to more than o...

0 Bhaskar Ramasubramanian, et al. ∙

research

∙ 07/24/2020

Stochastic Dynamic Information Flow Tracking Game using Supervised Learning for Detecting Advanced Persistent Threats

Advanced persistent threats (APTs) are organized prolonged cyberattacks ...

0 Shana Moothedath, et al. ∙

research

∙ 07/22/2020

Secure Control in Partially Observable Environments to Satisfy LTL Specifications

This paper studies the synthesis of control policies for an agent that h...

0 Bhaskar Ramasubramanian, et al. ∙

research

∙ 06/30/2020

A Multi-Agent Reinforcement Learning Approach for Dynamic Information Flow Tracking Games for Advanced Persistent Threats

Advanced Persistent Threats (APTs) are stealthy attacks that threaten th...

0 Dinuka Sahabandu, et al. ∙

research

∙ 06/22/2020

Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach

Advanced Persistent Threats (APTs) are stealthy customized attacks by in...

0 Shana Moothedath, et al. ∙

research

∙ 01/19/2020

FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback

Reinforcement learning has been successful in training autonomous agents...

6 Baicen Xiao, et al. ∙

research

∙ 12/08/2019

Covert Channel-Based Transmitter Authentication in Controller Area Networks

In recent years, the security of automotive Cyber-Physical Systems (CPSs...

0 Xuhang Ying, et al. ∙

research

∙ 10/27/2019

Linear Temporal Logic Satisfaction in Adversarial Environments using Secure Control Barrier Certificates

This paper studies the satisfaction of a class of temporal properties fo...

0 Bhaskar Ramasubramanian, et al. ∙

research

∙ 07/28/2019

Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples

Deep learning classifiers are known to be vulnerable to adversarial exam...

1 Hossein Hosseini, et al. ∙

research

∙ 07/25/2019

Mitigating Vulnerabilities of Voltage-based Intrusion Detection Systems in Controller Area Networks

Data for controlling a vehicle is exchanged among Electronic Control Uni...

0 Sang Uk Sagong, et al. ∙

research

∙ 07/20/2019

Potential-Based Advice for Stochastic Policy Learning

This paper augments the reward received by a reinforcement learning agen...

6 Baicen Xiao, et al. ∙

research

∙ 05/01/2019

Dropping Pixels for Adversarial Robustness

Deep neural networks are vulnerable against adversarial examples. In thi...

0 Hossein Hosseini, et al. ∙

research

∙ 04/22/2019

Detecting ADS-B Spoofing Attacks using Deep Neural Networks

The Automatic Dependent Surveillance-Broadcast (ADS-B) system is a key c...

0 Xuhang Ying, et al. ∙

research

∙ 03/16/2019

Secure Control under Partial Observability with Temporal Logic Constraints

This paper studies the synthesis of control policies for an agent that h...

0 Bhaskar Ramasubramanian, et al. ∙

research

∙ 03/12/2019

TACAN: Transmitter Authentication through Covert Channels in Controller Area Networks

Nowadays, the interconnection of automotive systems with modern digital ...

0 Xuhang Ying, et al. ∙

research

∙ 11/14/2018

A Game Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats

Advanced Persistent Threats (APTs) infiltrate cyber systems and compromi...

0 Shana Moothedath, et al. ∙

research

∙ 07/25/2018

Shape of the Cloak: Formal Analysis of Clock Skew-Based Intrusion Detection System in Controller Area Networks

This paper presents a new masquerade attack called the cloaking attack a...

0 Xuhang Ying, et al. ∙

research

∙ 03/21/2018

Assessing Shape Bias Property of Convolutional Neural Networks

It is known that humans display "shape bias" when classifying new items,...

0 Hossein Hosseini, et al. ∙

research

∙ 03/16/2018

Semantic Adversarial Examples

Deep neural networks are known to be vulnerable to adversarial examples,...

0 Hossein Hosseini, et al. ∙

research

∙ 08/14/2017

Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API

Due to the growth of video data on Internet, automatic video analysis ha...

0 Hossein Hosseini, et al. ∙

research

∙ 03/26/2017

Deceiving Google's Cloud Video Intelligence API Built for Summarizing Videos

Despite the rapid progress of the techniques for image classification, v...

0 Hossein Hosseini, et al. ∙

research

∙ 03/20/2017

On the Limitation of Convolutional Neural Networks in Recognizing Negative Images

Convolutional Neural Networks (CNNs) have achieved state-of-the-art perf...

0 Hossein Hosseini, et al. ∙

research

∙ 08/27/2016

Learning Temporal Dependence from Time-Series Data with Latent Variables

We consider the setting where a collection of time series, modeled as ra...

0 Hossein Hosseini, et al. ∙

research

∙ 02/28/2015

Group Event Detection with a Varying Number of Group Members for Video Surveillance

This paper presents a novel approach for automatic recognition of group ...

0 Weiyao Lin, et al. ∙

research

∙ 02/28/2015

Activity Recognition Using A Combination of Category Components And Local Models for Video Surveillance

This paper presents a novel approach for automatic recognition of human ...

0 Weiyao Lin, et al. ∙

Radha Poovendran

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