NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (27)

physics.app-ph2017

Feasibility of Direct Disposal of Salt Waste from Electochemical Processing of Spent Nuclear Fuel

Rob P Rechard, Teklu Hadgu, Yifeng Wang +6

cs.CR2016

Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks

Nicolas Papernot, Patrick McDaniel, Xi Wu +2

cs.CR2016

Towards Least Privilege Containers with Cimplifier

Vaibhav Rastogi, Drew Davidson, Lorenzo De Carli +2

cs.CR2016

Adversarial Perturbations Against Deep Neural Networks for Malware Classification

Kathrin Grosse, Nicolas Papernot, Praveen Manoharan +2

cs.CR2018

IoTSan: Fortifying the Safety of IoT Systems

Dang Tu Nguyen, Chengyu Song, Zhiyun Qian +3

cs.CR2016

On the Effectiveness of Defensive Distillation

Nicolas Papernot, Patrick McDaniel

cs.CR2016

Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Nicolas Papernot, Patrick McDaniel, Ian Goodfellow

cs.CR2017

Practical Black-Box Attacks against Machine Learning

Nicolas Papernot, Patrick McDaniel, Ian Goodfellow +3

cs.CR2019

Curie: Policy-based Secure Data Exchange

Z. Berkay Celik, Hidayet Aksu, Abbas Acar +3

cs.CR2016

Crafting Adversarial Input Sequences for Recurrent Neural Networks

Nicolas Papernot, Patrick McDaniel, Ananthram Swami +1

cs.CR2017

On the (Statistical) Detection of Adversarial Examples

Kathrin Grosse, Praveen Manoharan, Nicolas Papernot +2

cs.CR2018

Detection under Privileged Information

Z. Berkay Celik, Patrick McDaniel, Rauf Izmailov +4

cs.CR2015

The Limitations of Deep Learning in Adversarial Settings

Nicolas Papernot, Patrick McDaniel, Somesh Jha +3

cs.CR2018

Regulating Access to System Sensors in Cooperating Programs

Giuseppe Petracca, Jens Grossklags, Patrick McDaniel +1

cs.CR2018

Sensitive Information Tracking in Commodity IoT

Z. Berkay Celik, Leonardo Babun, Amit K. Sikder +4

stat.ML2017

The Space of Transferable Adversarial Examples

Florian Tramèr, Nicolas Papernot, Ian Goodfellow +2

cs.LG2017

Extending Defensive Distillation

Nicolas Papernot, Patrick McDaniel

cs.SI2018

Attacking Strategies and Temporal Analysis Involving Facebook Discussion Groups

Chun-Ming Lai, Xiaoyun Wang, Yunfeng Hong +4

cs.SE2014

I know what leaked in your pocket: uncovering privacy leaks on Android Apps with Static Taint Analysis

Li Li, Alexandre Bartel, Jacques Klein +6

cs.CR2017

Patient-Driven Privacy Control through Generalized Distillation

Z. Berkay Celik, David Lopez-Paz, Patrick McDaniel

cs.LG2018

Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning

Nicolas Papernot, Patrick McDaniel

cs.CR2017

Achieving Secure and Differentially Private Computations in Multiparty Settings

Abbas Acar, Z. Berkay Celik, Hidayet Aksu +2

cs.CR2015

Six Potential Game-Changers in Cyber Security: Towards Priorities in Cyber Science and Engineering

Alexander Kott, Ananthram Swami, Patrick McDaniel

cs.LG2018

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

Nicolas Papernot, Fartash Faghri, Nicholas Carlini +23

cs.CR2016

Towards the Science of Security and Privacy in Machine Learning

Nicolas Papernot, Patrick McDaniel, Arunesh Sinha +1

cs.CR2018

Program Analysis of Commodity IoT Applications for Security and Privacy: Challenges and Opportunities

Z. Berkay Celik, Earlence Fernandes, Eric Pauley +2

cs.SI2018

More or Less? Predict the Social Influence of Malicious URLs on Social Media

Chun-Ming Lai, Xiaoyun Wang, Jon W. Chapman +5