Vahid Behzadan | DeepAI

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∙ 02/14/2023

A Theory of Mind Approach as Test-Time Mitigation Against Emergent Adversarial Communication

Multi-Agent Systems (MAS) is the study of multi-agent interactions in a ...

0 Nancirose Piazza, et al. ∙

∙ 11/18/2022

Adversarial Stimuli: Attacking Brain-Computer Interfaces via Perturbed Sensory Events

Machine learning models are known to be vulnerable to adversarial pertur...

0 Bibek Upadhayay, et al. ∙

∙ 09/29/2021

Mitigation of Adversarial Policy Imitation via Constrained Randomization of Policy (CRoP)

Deep reinforcement learning (DRL) policies are vulnerable to unauthorize...

0 Nancirose Piazza, et al. ∙

∙ 02/11/2021

Adversarial Poisoning Attacks and Defense for General Multi-Class Models Based On Synthetic Reduced Nearest Neighbors

State-of-the-art machine learning models are vulnerable to data poisonin...

0 Pooya Tavallali, et al. ∙

∙ 10/22/2020

Adversarial Attacks on Deep Algorithmic Trading Policies

Deep Reinforcement Learning (DRL) has become an appealing solution to al...

0 Yaser Faghan, et al. ∙

∙ 09/01/2020

Sentimental LIAR: Extended Corpus and Deep Learning Models for Fake Claim Classification

The rampant integration of social media in our every day lives and cultu...

0 Bibek Upadhayay, et al. ∙

∙ 12/11/2019

Founding The Domain of AI Forensics

With the widespread integration of AI in everyday and critical technolog...

0 Ibrahim Baggili, et al. ∙

∙ 07/12/2019

A Novel Approach for Detection and Ranking of Trendy and Emerging Cyber Threat Events in Twitter Streams

We present a new machine learning and text information extraction approa...

0 Avishek Bose, et al. ∙

∙ 06/03/2019

Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies

This paper proposes a novel scheme for the watermarking of Deep Reinforc...

0 Vahid Behzadan, et al. ∙

∙ 06/03/2019

Adversarial Exploitation of Policy Imitation

This paper investigates a class of attacks targeting the confidentiality...

0 Vahid Behzadan, et al. ∙

∙ 06/03/2019

Analysis and Improvement of Adversarial Training in DQN Agents With Adversarially-Guided Exploration (AGE)

This paper investigates the effectiveness of adversarial training in enh...

0 Vahid Behzadan, et al. ∙

∙ 06/03/2019

RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies

This paper investigates the resilience and robustness of Deep Reinforcem...

0 Vahid Behzadan, et al. ∙

∙ 11/14/2018

TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous Vehicles

This paper presents TrolleyMod v1.0, an open-source platform based on th...

0 Vahid Behzadan, et al. ∙

∙ 11/14/2018

Emergence of Addictive Behaviors in Reinforcement Learning Agents

This paper presents a novel approach to the technical analysis of wirehe...

3 Vahid Behzadan, et al. ∙

∙ 10/23/2018

The Faults in Our Pi Stars: Security Issues and Open Challenges in Deep Reinforcement Learning

Since the inception of Deep Reinforcement Learning (DRL) algorithms, the...

0 Vahid Behzadan, et al. ∙

∙ 06/04/2018

Mitigation of Policy Manipulation Attacks on Deep Q-Networks with Parameter-Space Noise

Recent developments have established the vulnerability of deep reinforce...

0 Vahid Behzadan, et al. ∙

∙ 06/04/2018

Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles

With the rapidly growing interest in autonomous navigation, the body of ...

0 Vahid Behzadan, et al. ∙

∙ 05/23/2018

A Psychopathological Approach to Safety Engineering in AI and AGI

The complexity of dynamics in AI techniques is already approaching that ...

13 Vahid Behzadan, et al. ∙

∙ 12/23/2017

Whatever Does Not Kill Deep Reinforcement Learning, Makes It Stronger

Recent developments have established the vulnerability of deep Reinforce...

0 Vahid Behzadan, et al. ∙

∙ 09/13/2017

Models and Framework for Adversarial Attacks on Complex Adaptive Systems

We introduce the paradigm of adversarial attacks that target the dynamic...

0 Vahid Behzadan, et al. ∙

∙ 01/16/2017

Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks

Deep learning classifiers are known to be inherently vulnerable to manip...

0 Vahid Behzadan, et al. ∙

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