382 citations · 853 across the 32 of their papers we have counts for
5 papers · 1 filter
Analyzing Federated Learning through an Adversarial Lens
Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal +1
Federated learning distributes model training among a multitude of agents, who, guided by privacy concerns, perform training using their local data but share only model parameter u…
PAC-learning in the presence of evasion adversaries
Daniel Cullina, Arjun Nitin Bhagoji, Prateek Mittal
The existence of evasion attacks during the test phase of machine learning algorithms represents a significant challenge to both their deployment and understanding. These attacks c…
On the Local Equivalence of 2D Color Codes and Surface Codes with Applications
Arun B. Aloshious, Arjun Nitin Bhagoji, Pradeep Kiran Sarvepalli
In recent years, there have been many studies on local stabilizer codes. Under the assumption of translation and scale invariance Yoshida classified such codes. His result implies…
DARTS: Deceiving Autonomous Cars with Toxic Signs
Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia +2
Sign recognition is an integral part of autonomous cars. Any misclassification of traffic signs can potentially lead to a multitude of disastrous consequences, ranging from a life-…
Rogue Signs: Deceiving Traffic Sign Recognition with Malicious Ads and Logos
Chawin Sitawarin, Arjun Nitin Bhagoji, Arsalan Mosenia +2
We propose a new real-world attack against the computer vision based systems of autonomous vehicles (AVs). Our novel Sign Embedding attack exploits the concept of adversarial examp…