37 citations · 70 across the 9 of their papers we have counts for
17 papers
Adversarial Stimuli: Attacking Brain-Computer Interfaces via Perturbed Sensory Events
Bibek Upadhayay, Vahid Behzadan
Machine learning models are known to be vulnerable to adversarial perturbations in the input domain, causing incorrect predictions. Inspired by this phenomenon, we explore the feas…
Mitigation of Adversarial Policy Imitation via Constrained Randomization of Policy (CRoP)
Nancirose Piazza, Vahid Behzadan
Deep reinforcement learning (DRL) policies are vulnerable to unauthorized replication attacks, where an adversary exploits imitation learning to reproduce target policies from obse…
Adversarial Poisoning Attacks and Defense for General Multi-Class Models Based On Synthetic Reduced Nearest Neighbors
Pooya Tavallali, Vahid Behzadan, Peyman Tavallali +1
State-of-the-art machine learning models are vulnerable to data poisoning attacks whose purpose is to undermine the integrity of the model. However, the current literature on data…
Adversarial Attacks on Deep Algorithmic Trading Policies
Yaser Faghan, Nancirose Piazza, Vahid Behzadan +1
Deep Reinforcement Learning (DRL) has become an appealing solution to algorithmic trading such as high frequency trading of stocks and cyptocurrencies. However, DRL have been shown…
Sentimental LIAR: Extended Corpus and Deep Learning Models for Fake Claim Classification
Bibek Upadhayay, Vahid Behzadan
The rampant integration of social media in our every day lives and culture has given rise to fast and easier access to the flow of information than ever in human history. However,…
Founding The Domain of AI Forensics
Ibrahim Baggili, Vahid Behzadan
With the widespread integration of AI in everyday and critical technologies, it seems inevitable to witness increasing instances of failure in AI systems. In such cases, there aris…