Security Papers from the 2020s

This webpage is an attempt to assemble a ranking of top-cited security papers from the 2020s. The ranking has been created based on citations of papers published at top security conferences. More details are available here.

Top-cited papers from 2022 ⌄

  1. 1
    Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, and Yang Zhang:
    Dynamic Backdoor Attacks Against Machine Learning Models.
    IEEE European Symposium on Security and Privacy, 2022
    84 cites at Google Scholar
    3418% above average of year
    Last visited: Jul-2022
    Paper: DOI
  2. 2
    Théo Ryffel, Pierre Tholoniat, David Pointcheval, and Francis R. Bach:
    AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing.
    Proceedings on Privacy Enhancing Technologies, 2022
    19 cites at Google Scholar
    696% above average of year
    Last visited: Jul-2022
    Paper: DOI
  3. 3
    Jiafan Wang and Sherman S. M. Chow:
    Forward and Backward-Secure Range-Searchable Symmetric Encryption.
    Proceedings on Privacy Enhancing Technologies, 2022
    16 cites at Google Scholar
    570% above average of year
    Last visited: Jul-2022
    Paper: DOI
  4. 4
    Konrad Kollnig, Anastasia Shuba, Reuben Binns, Max Van Kleek, and Nigel Shadbolt:
    Are iPhones Really Better for Privacy? A Comparative Study of iOS and Android Apps.
    Proceedings on Privacy Enhancing Technologies, 2022
    14 cites at Google Scholar
    486% above average of year
    Last visited: Jul-2022
    Paper: DOI
  5. 5
    Daniel Alabi, Audra McMillan, Jayshree Sarathy, Adam D. Smith, and Salil P. Vadhan:
    Differentially Private Simple Linear Regression.
    Proceedings on Privacy Enhancing Technologies, 2022
    13 cites at Google Scholar
    444% above average of year
    Last visited: Jul-2022
    Paper: DOI
  6. 6
    Aidmar Wainakh, Fabrizio Ventola, Till Müßig, Jens Keim, Carlos Garcia Cordero, Ephraim Zimmer, Tim Grube, Kristian Kersting, and Max Mühlhäuser:
    User-Level Label Leakage from Gradients in Federated Learning.
    Proceedings on Privacy Enhancing Technologies, 2022
    10 cites at Google Scholar
    319% above average of year
    Last visited: Jul-2022
    Paper: DOI
  7. 7
    Nishanth Chandran, Divya Gupta, and Akash Shah:
    Circuit-PSI With Linear Complexity via Relaxed Batch OPPRF.
    Proceedings on Privacy Enhancing Technologies, 2022
    9 cites at Google Scholar
    277% above average of year
    Last visited: Jul-2022
    Paper: DOI
  8. 8
    Samuel Adams, Chaitali Choudhary, Martine De Cock, Rafael Dowsley, David Melanson, Anderson C. A. Nascimento, Davis Railsback, and Jianwei Shen:
    Privacy-preserving training of tree ensembles over continuous data.
    Proceedings on Privacy Enhancing Technologies, 2022
    8 cites at Google Scholar
    235% above average of year
    Last visited: Jul-2022
    Paper: DOI
  9. 9
    Darion Cassel, Su-Chin Lin, Alessio Buraggina, William Wang, Andrew Zhang, Lujo Bauer, Hsu-Chun Hsiao, Limin Jia, and Timothy Libert:
    OmniCrawl: Comprehensive Measurement of Web Tracking With Real Desktop and Mobile Browsers.
    Proceedings on Privacy Enhancing Technologies, 2022
    5 cites at Google Scholar
    109% above average of year
    Last visited: Jul-2022
    Paper: DOI
  10. 10
    Jacob Leon Kröger, Leon Gellrich, Sebastian Pape, Saba Rebecca Brause, and Stefan Ullrich:
    Personal information inference from voice recordings: User awareness and privacy concerns.
    Proceedings on Privacy Enhancing Technologies, 2022
    5 cites at Google Scholar
    109% above average of year
    Last visited: Jul-2022
    Paper: DOI

Top-cited papers from 2021 ⌄

  1. 1
    Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel:
    Extracting Training Data from Large Language Models.
    USENIX Security Symposium, 2021
    283 cites at Google Scholar
    3424% above average of year
    Last visited: Jul-2022
    Paper: DOI
  2. 2
    Ellis Fenske, Dane Brown, Jeremy Martin, Travis Mayberry, Peter Ryan, and Erik C. Rye:
    Three Years Later: A Study of MAC Address Randomization In Mobile Devices And When It Succeeds.
    Proceedings on Privacy Enhancing Technologies, 2021
    216 cites at Google Scholar
    2590% above average of year
    Last visited: Jul-2022
    Paper: DOI
  3. 3
    Lucas Bourtoule, Varun Chandrasekaran, Christopher A. Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot:
    Machine Unlearning.
    IEEE Symposium on Security and Privacy, 2021
    118 cites at Google Scholar
    1369% above average of year
    Last visited: Jul-2022
    Paper: DOI
  4. 4
    Liwei Song and Prateek Mittal:
    Systematic Evaluation of Privacy Risks of Machine Learning Models.
    USENIX Security Symposium, 2021
    85 cites at Google Scholar
    958% above average of year
    Last visited: Jul-2022
    Paper: DOI
  5. 5
    Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, and Bo Li:
    Detecting AI Trojans Using Meta Neural Analysis.
    IEEE Symposium on Security and Privacy, 2021
    83 cites at Google Scholar
    933% above average of year
    Last visited: Jul-2022
    Paper: DOI
  6. 6
    Leixiao Cheng and Fei Meng:
    Server-Aided Revocable Attribute-Based Encryption Revised: Multi-User Setting and Fully Secure.
    European Symposium on Research in Computer Security (ESORICS), 2021
    78 cites at Google Scholar
    871% above average of year
    Last visited: Jul-2022
    Paper: DOI
  7. 7
    Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, and Tal Rabin:
    Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning.
    Proceedings on Privacy Enhancing Technologies, 2021
    77 cites at Google Scholar
    859% above average of year
    Last visited: Jul-2022
    Paper: DOI
  8. 8
    Eugene Bagdasaryan and Vitaly Shmatikov:
    Blind Backdoors in Deep Learning Models.
    USENIX Security Symposium, 2021
    71 cites at Google Scholar
    784% above average of year
    Last visited: Jul-2022
    Paper: DOI
  9. 9
    Manuel Barbosa, Gilles Barthe, Karthik Bhargavan, Bruno Blanchet, Cas Cremers, Kevin Liao, and Bryan Parno:
    SoK: Computer-Aided Cryptography.
    IEEE Symposium on Security and Privacy, 2021
    71 cites at Google Scholar
    784% above average of year
    Last visited: Jul-2022
    Paper: DOI
  10. 10
    Guangke Chen, Sen Chen, Lingling Fan, Xiaoning Du, Zhe Zhao, Fu Song, and Yang Liu:
    Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems.
    IEEE Symposium on Security and Privacy, 2021
    69 cites at Google Scholar
    759% above average of year
    Last visited: Jul-2022
    Paper: DOI

Top-cited papers from 2020 ⌄

  1. 1
    Minghong Fang, Xiaoyu Cao, Jinyuan Jia, and Neil Zhenqiang Gong:
    Local Model Poisoning Attacks to Byzantine-Robust Federated Learning.
    USENIX Security Symposium, 2020
    285 cites at Google Scholar
    1209% above average of year
    Last visited: Jul-2022
    Paper: DOI
  2. 2
    Jianbo Chen, Michael I. Jordan, and Martin J. Wainwright:
    HopSkipJumpAttack: A Query-Efficient Decision-Based Attack.
    IEEE Symposium on Security and Privacy, 2020
    258 cites at Google Scholar
    1085% above average of year
    Last visited: Jul-2022
    Paper: DOI
  3. 3
    Harry A. Kalodner, Malte Möser, Kevin Lee, Steven Goldfeder, Martin Plattner, Alishah Chator, and Arvind Narayanan:
    BlockSci: Design and applications of a blockchain analysis platform.
    USENIX Security Symposium, 2020
    156 cites at Google Scholar
    616% above average of year
    Last visited: Jul-2022
    Paper: DOI
  4. 4
    Pratyush Mishra, Ryan Lehmkuhl, Akshayaram Srinivasan, Wenting Zheng, and Raluca Ada Popa:
    Delphi: A Cryptographic Inference Service for Neural Networks.
    USENIX Security Symposium, 2020
    153 cites at Google Scholar
    603% above average of year
    Last visited: Jul-2022
    Paper: DOI
  5. 5
    Jo Van Bulck, Daniel Moghimi, Michael Schwarz, Moritz Lipp, Marina Minkin, Daniel Genkin, Yuval Yarom, Berk Sunar, Daniel Gruss, and Frank Piessens:
    LVI: Hijacking Transient Execution through Microarchitectural Load Value Injection.
    IEEE Symposium on Security and Privacy, 2020
    145 cites at Google Scholar
    566% above average of year
    Last visited: Jul-2022
    Paper: DOI
  6. 6
    Vale Tolpegin, Stacey Truex, Mehmet Emre Gursoy, and Ling Liu:
    Data Poisoning Attacks Against Federated Learning Systems.
    European Symposium on Research in Computer Security (ESORICS), 2020
    141 cites at Google Scholar
    547% above average of year
    Last visited: Jul-2022
    Paper: DOI
  7. 7
    Marcel Keller:
    MP-SPDZ: A Versatile Framework for Multi-Party Computation.
    ACM Conference on Computer and Communications Security (CCS), 2020
    139 cites at Google Scholar
    538% above average of year
    Last visited: Jul-2022
    Paper: DOI
  8. 8
    Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, and Nicolas Papernot:
    High Accuracy and High Fidelity Extraction of Neural Networks.
    USENIX Security Symposium, 2020
    139 cites at Google Scholar
    538% above average of year
    Last visited: Jul-2022
    Paper: DOI
  9. 9
    Mengjia Yan, Christopher W. Fletcher, and Josep Torrellas:
    Cache Telepathy: Leveraging Shared Resource Attacks to Learn DNN Architectures.
    USENIX Security Symposium, 2020
    135 cites at Google Scholar
    520% above average of year
    Last visited: Jul-2022
    Paper: DOI
  10. 10
    Anton Permenev, Dimitar K. Dimitrov, Petar Tsankov, Dana Drachsler-Cohen, and Martin T. Vechev:
    VerX: Safety Verification of Smart Contracts.
    IEEE Symposium on Security and Privacy, 2020
    131 cites at Google Scholar
    502% above average of year
    Last visited: Jul-2022
    Paper: DOI