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Computer Science

D-Index
51
Citations
9999
World Ranking
5360
National Ranking
2454

Overview

Nina Taft is a researcher affiliated with Google in the United States. Their body of work spans multiple fields including computer science and social sciences, with particular attention to subfields such as sociology and political science, signal processing, clinical psychology, and information systems.

Their research focuses on several key topics including privacy, security, and data protection, advanced malware detection techniques, sexuality, behavior, and technology, cybercrime and law enforcement studies, as well as mobile and web applications.

Nina Taft has contributed to a range of academic venues, with publications appearing notably in arXiv (Cornell University), the Proceedings of the 44th International Conference on Software Engineering, and the 2022 IEEE Symposium on Security and Privacy (SP).

Their recent papers include:

  • "Analyzing user perspectives on mobile app privacy at scale," 2022, Proceedings of the 44th International Conference on Software Engineering
  • "Hark: A Deep Learning System for Navigating Privacy Feedback at Scale," 2022, 2022 IEEE Symposium on Security and Privacy (SP)
  • "A Decade of Privacy-Relevant Android App Reviews: Large Scale Trends," 2024, arXiv (Cornell University)
  • "Beyond PII: How Users Attempt to Estimate and Mitigate Implicit LLM Inference," 2025, arXiv (Cornell University)

Frequent collaborators in their research include Sai Teja Peddinti, Hamza Harkous, Animesh Srivastava, Preksha Nema, and Pauline Anthonysamy. These coauthorships indicate interdisciplinary and collaborative approaches across various investigations related to privacy and security.

Best Publications

  • Traffic matrix estimation: existing techniques and new directions

    A. Medina;N. Taft;K. Salamatian;S. Bhattacharyya

  • Structural analysis of network traffic flows

    Anukool Lakhina;Konstantina Papagiannaki;Mark Crovella;Christophe Diot

  • Privacy-Preserving Ridge Regression on Hundreds of Millions of Records

    V. Nikolaenko;U. Weinsberg;S. Ioannidis;M. Joye

  • Combining filtering and statistical methods for anomaly detection

    Augustin Soule;Kavé Salamatian;Nina Taft

  • ANTIDOTE: understanding and defending against poisoning of anomaly detectors

    Benjamin I.P. Rubinstein;Blaine Nelson;Ling Huang;Anthony D. Joseph

  • Privacy-preserving matrix factorization

    Valeria Nikolaenko;Stratis Ioannidis;Udi Weinsberg;Marc Joye

  • Traffic matrices: balancing measurements, inference and modeling

    Augustin Soule;Anukool Lakhina;Nina Taft;Konstantina Papagiannaki

  • Learning in a large function space: Privacy-preserving mechanisms for SVM learning

    Benjamin I. P. Rubinstein;Peter L. Bartlett;Ling Huang;Nina Taft

  • Long-term forecasting of Internet backbone traffic: observations and initial models

    K. Papagiannaki;N. Taft;Z.-L. Zhang;C. Diot

  • In-Network PCA and Anomaly Detection

    Ling Huang;Long Nguyen;Minos Garofalakis;Michael I. Jordan

  • The problem of synthetically generating IP traffic matrices: initial recommendations

    Antonio Nucci;Ashwin Sridharan;Nina Taft

  • Skilled in the art of being idle: reducing energy waste in networked systems

    Sergiu Nedevschi;Jaideep Chandrashekar;Junda Liu;Bruce Nordman

  • An approach to alleviate link overload as observed on an IP backbone

    Sundar Iyer;Supratik Bhattacharyya;N. Taft;C. Diot

  • Communication-Efficient Online Detection of Network-Wide Anomalies

    Ling Huang;Xuan Long Nguyen;M. Garofalakis;J.M. Hellerstein

  • BlurMe: inferring and obfuscating user gender based on ratings

    Udi Weinsberg;Smriti Bhagat;Stratis Ioannidis;Nina Taft

  • Finding a needle in a haystack of reviews: cold start context-based hotel recommender system demo

    Asher Levi;Osnat Mokryn;Christophe Diot;Nina Taft

  • GraphSC: Parallel Secure Computation Made Easy

    Kartik Nayak;Xiao Shaun Wang;Stratis Ioannidis;Udi Weinsberg

  • IGP link weight assignment for transient link failures

    A. Nucci;B. Schroeder;S. Bhattacharyya;N. Taft

  • Long-term forecasting of Internet backbone traffic

    K. Papagiannaki;N. Taft;Zhi-Li Zhang;C. Diot

  • How to identify and estimate the largest traffic matrix elements in a dynamic environment

    Augustin Soule;Antonio Nucci;Rene Cruz;Emilio Leonardi

Frequent Co-Authors

Christophe Diot
Christophe Diot Google (United States)
Antonio Nucci
Antonio Nucci Cisco Systems (United States)
Ling Huang
Ling Huang Intel (United States)
Konstantina Papagiannaki
Konstantina Papagiannaki Google (United States)
Stratis Ioannidis
Stratis Ioannidis Northeastern University
Anthony D. Joseph
Anthony D. Joseph University of California, Berkeley
Patrick Thiran
Patrick Thiran École Polytechnique Fédérale de Lausanne
Minos Garofalakis
Minos Garofalakis Technical University of Crete
Mark Crovella
Mark Crovella Boston University

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