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Riley Spahn
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{XRay}: Enhancing the {Web’s} Transparency with Differential Correlation
M Lécuyer, G Ducoffe, F Lan, A Papancea, T Petsios, R Spahn, ...
23rd USENIX Security Symposium (USENIX Security 14), 49-64, 2014
1462014
Sunlight: Fine-grained targeting detection at scale with statistical confidence
M Lecuyer, R Spahn, Y Spiliopolous, A Chaintreau, R Geambasu, D Hsu
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications …, 2015
752015
Pebbles:{Fine-Grained} Data Management Abstractions for Modern Operating Systems
R Spahn, J Bell, M Lee, S Bhamidipati, R Geambasu, G Kaiser
11th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2014
392014
Nv: Nessus vulnerability visualization for the web
L Harrison, R Spahn, M Iannacone, E Downing, JR Goodall
Proceedings of the ninth international symposium on visualization for cyber …, 2012
392012
Privacy accounting and quality control in the sage differentially private ML platform
M Lécuyer, R Spahn, K Vodrahalli, R Geambasu, D Hsu
Proceedings of the 27th ACM Symposium on Operating Systems Principles, 181-195, 2019
172019
situ: Situational understanding and discovery for cyber attacks
L Harrison, J Laska, R Spahn, M Iannacone, E Downing, EM Ferragut, ...
2012 IEEE Conference on Visual Analytics Science and Technology (VAST), 307-308, 2012
122012
Enhancing selectivity in big data
M Lecuyer, R Spahn, R Geambasu, TK Huang, S Sen
IEEE Security & Privacy 16 (1), 34-42, 2018
92018
Pyramid: Enhancing selectivity in big data protection with count featurization
M Lecuyer, R Spahn, R Geambasu, TK Huang, S Sen
2017 IEEE Symposium on Security and Privacy (SP), 78-95, 2017
92017
New Data Protection Abstractions for Emerging Mobile and Big Data Workloads
R Spahn
Columbia University, 2020
2020
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Articles 1–9