World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
86
Citations
36093
World Ranking
760
National Ranking
406

Research.com Recognitions

  • 2015 - IEEE Fellow For contributions to scalable Internet data management and decentralized trust management

Overview

Ling Liu is affiliated with the Georgia Institute of Technology in the United States and has contributed extensively to the field of Computer Science, with a focus on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems, and Electrical and Electronic Engineering.

Their recent research includes publications in various reputable venues, reflecting a diverse range of topics. Notable recent papers include:

  • Security and Privacy for Healthcare Blockchains, 2021, IEEE Transactions on Services Computing
  • A Framework for Evaluating Gradient Leakage Attacks in Federated Learning, 2020, arXiv (Cornell University)
  • Machine learning the nuclear mass, 2021, Nuclear Science and Techniques
  • De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks, 2021, IEEE Transactions on Information Forensics and Security
  • Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding, 2022, ACM Computing Surveys

Their frequent co-authors include Wenqi Wei, Yanzhao Wu, Ka-Ho Chow, Sihao Hu, and Tiansheng Huang.

Ling Liu often publishes in venues such as arXiv (Cornell University), IEEE Transactions on Services Computing, IEEE Transactions on Information Forensics and Security, ACM Transactions on Intelligent Systems and Technology, and IEEE Access.

Their work covers several main topics, including:

  • Adversarial Robustness in Machine Learning
  • IoT and Edge/Fog Computing
  • Privacy-Preserving Technologies in Data
  • Anomaly Detection Techniques and Applications
  • Cryptography and Data Security
  • Advanced Neural Network Applications
  • Cloud Computing and Resource Management

In 2015, Ling Liu was recognized as an IEEE Fellow for contributions to scalable Internet data management and decentralized trust management.

Best Publications

  • PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities

    Li Xiong;Ling Liu

  • Encyclopedia of Database Systems

    Ling Liu;M. Tamer Zsu

  • Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms

    B. Gedik;Ling Liu

  • Location Privacy in Mobile Systems: A Personalized Anonymization Model

    B. Gedik;Ling Liu

  • Security and Privacy on Blockchain

    Rui Zhang;Rui Xue;Ling Liu

  • XWRAP: an XML-enabled wrapper construction system for Web information sources

    L. Liu;C. Pu;W. Han

  • A reputation-based trust model for peer-to-peer e-commerce communities

    Li Xiong;Ling Liu

  • Data Poisoning Attacks Against Federated Learning Systems

    Vale Tolpegin;Stacey Truex;Mehmet Emre Gursoy;Ling Liu

  • Supporting anonymous location queries in mobile environments with privacygrid

    Bhuvan Bamba;Ling Liu;Peter Pesti;Ting Wang

  • Continual queries for Internet scale event-driven information delivery

    Ling Liu;C. Pu;Wei Tang

  • Security Models and Requirements for Healthcare Application Clouds

    Rui Zhang;Ling Liu

  • A reputation-based trust model for peer-to-peer ecommerce communities.

    Li Xiong;Ling Liu

  • TrustGuard: countering vulnerabilities in reputation management for decentralized overlay networks

    Mudhakar Srivatsa;Li Xiong;Ling Liu

  • TrustMe: anonymous management of trust relationships in decentralized P2P systems

    Aameek Singh;Ling Liu

  • Privacy preserving data classification with rotation perturbation

    Keke Chen;Ling Liu

  • LDP-Fed: federated learning with local differential privacy

    Stacey Truex;Ling Liu;Ka-Ho Chow;Mehmet Emre Gursoy

  • Encyclopedia of database systems

    Unknown

  • A fully automated object extraction system for the World Wide Web

    D. Buttler;Ling Liu;C. Pu

  • MobiMix: Protecting location privacy with mix-zones over road networks

    Balaji Palanisamy;Ling Liu

  • Differentially Private Model Publishing for Deep Learning

    Lei Yu;Ling Liu;Calton Pu;Mehmet Emre Gursoy

  • Purlieus: locality-aware resource allocation for MapReduce in a cloud

    Balaji Palanisamy;Aameek Singh;Ling Liu;Bhushan Jain

  • ASAP: An Adaptive Sampling Approach to Data Collection in Sensor Networks

    B. Gedik;Ling Liu;P.S. Yu

  • A reputation-based trust model for peer-to-peer ecommerce communities [Extended Abstract]

    Li Xiong;Ling Liu

Frequent Co-Authors

Calton Pu
Calton Pu Georgia Institute of Technology
Mudhakar Srivatsa
Mudhakar Srivatsa IBM (United States)
Bugra Gedik
Bugra Gedik Royal Caribbean Cruises (United States)
James Caverlee
James Caverlee Texas A&M University
Joshua D. Rabinowitz
Joshua D. Rabinowitz Princeton University
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Li Xiong
Li Xiong Emory University
Hai Jin
Hai Jin Huazhong University of Science and Technology
Kun-Lung Wu
Kun-Lung Wu IBM (United States)

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