491 citations · 693 across the 15 of their papers we have counts for
5 papers · 1 filter
Note on Attacking Object Detectors with Adversarial Stickers
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes +6
Deep learning has proven to be a powerful tool for computer vision and has seen widespread adoption for numerous tasks. However, deep learning algorithms are known to be vulnerable…
IFTTT vs. Zapier: A Comparative Study of Trigger-Action Programming Frameworks
Amir Rahmati, Earlence Fernandes, Jaeyeon Jung +1
The growing popularity of online services and IoT platforms along with increased developer's access to devices and services through RESTful APIs is giving rise to a new class of fr…
Decoupled-IFTTT: Constraining Privilege in Trigger-Action Platforms for the Internet of Things
Earlence Fernandes, Amir Rahmati, Jaeyeon Jung +1
Trigger-Action platforms are an emerging class of web-based systems that enable users to create automation rules (or recipes) of the form, "If there is a smoke alarm, then turn off…
Robust Physical-World Attacks on Deep Learning Models
Kevin Eykholt, Ivan Evtimov, Earlence Fernandes +6
Recent studies show that the state-of-the-art deep neural networks (DNNs) are vulnerable to adversarial examples, resulting from small-magnitude perturbations added to the input. G…
Internet of Things Security Research: A Rehash of Old Ideas or New Intellectual Challenges?
Earlence Fernandes, Amir Rahmati, Kevin Eykholt +1
The Internet of Things (IoT) is a new computing paradigm that spans wearable devices, homes, hospitals, cities, transportation, and critical infrastructure. Building security into…