A
Atul Prakash
Researcher at University of Michigan
Publications - 200
Citations - 8953
Atul Prakash is an academic researcher from University of Michigan. The author has contributed to research in topics: Security policy & The Internet. The author has an hindex of 46, co-authored 192 publications receiving 7535 citations. Previous affiliations of Atul Prakash include IBM & University of California, Berkeley.
Papers
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Proceedings ArticleDOI
Robust Physical-World Attacks on Deep Learning Visual Classification
Kevin Eykholt,Ivan Evtimov,Earlence Fernandes,Bo Li,Amir Rahmati,Chaowei Xiao,Atul Prakash,Tadayoshi Kohno,Dawn Song +8 more
TL;DR: This work proposes a general attack algorithm, Robust Physical Perturbations (RP2), to generate robust visual adversarial perturbations under different physical conditions and shows that adversarial examples generated using RP2 achieve high targeted misclassification rates against standard-architecture road sign classifiers in the physical world under various environmental conditions, including viewpoints.
Proceedings ArticleDOI
Security Analysis of Emerging Smart Home Applications
TL;DR: This paper analyzed Samsung-owned SmartThings, which has the largest number of apps among currently available smart home platforms, and supports a broad range of devices including motion sensors, fire alarms, and door locks, and discovered two intrinsic design flaws that lead to significant overprivilege in SmartApps.
Posted Content
Robust Physical-World Attacks on Deep Learning Models
Ivan Evtimov,Kevin Eykholt,Earlence Fernandes,Tadayoshi Kohno,Bo Li,Atul Prakash,Amir Rahmati,Dawn Song +7 more
TL;DR: This work proposes a general attack algorithm,Robust Physical Perturbations (RP2), to generate robust visual adversarial perturbations under different physical conditions and shows that adversarial examples generated using RP2 achieve high targeted misclassification rates against standard-architecture road sign classifiers in the physical world under various environmental conditions, including viewpoints.
Posted Content
Robust Physical-World Attacks on Machine Learning Models.
Ivan Evtimov,Kevin Eykholt,Earlence Fernandes,Tadayoshi Kohno,Bo Li,Atul Prakash,Amir Rahmati,Dawn Song +7 more
TL;DR: This paper proposes a new attack algorithm--Robust Physical Perturbations (RP2)-- that generates perturbations by taking images under different conditions into account and can create spatially-constrained perturbation that mimic vandalism or art to reduce the likelihood of detection by a casual observer.
Proceedings ArticleDOI
ContexIoT: Towards Providing Contextual Integrity to Appified IoT Platforms
Yunhan Jia,Qi Alfred Chen,Shiqi Wang,Amir Rahmati,Earlence Fernandes,Z. Morley Mao,Atul Prakash +6 more
TL;DR: ContexIoT is proposed, a context-based permission system for appified IoT platforms that provides contextual integrity by supporting fine-grained context identification for sensitive actions, and runtime prompts with rich context information to help users perform effective access control.