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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
    104 cites at Google Scholar
    5492% above average of year
    Last visited: Oct-2022
    Paper: DOI
  2. 2
    Kaihua Qin, Liyi Zhou, and Arthur Gervais:
    Quantifying Blockchain Extractable Value: How dark is the forest?
    IEEE Symposium on Security and Privacy, 2022
    61 cites at Google Scholar
    3180% above average of year
    Last visited: Nov-2022
    Paper: DOI
  3. 3
    Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Fabio Pierazzi, Christian Wressnegger, Lorenzo Cavallaro, and Konrad Rieck:
    Dos and Don'ts of Machine Learning in Computer Security.
    USENIX Security Symposium, 2022
    60 cites at Google Scholar
    3126% above average of year
    Last visited: Oct-2022
    Paper: DOI
  4. 4
    Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, and Florian Tramèr:
    Membership Inference Attacks From First Principles.
    IEEE Symposium on Security and Privacy, 2022
    50 cites at Google Scholar
    2588% above average of year
    Last visited: Nov-2022
    Paper: DOI
  5. 5
    Virat Shejwalkar, Amir Houmansadr, Peter Kairouz, and Daniel Ramage:
    Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning.
    IEEE Symposium on Security and Privacy, 2022
    35 cites at Google Scholar
    1782% above average of year
    Last visited: Nov-2022
    Paper: DOI
  6. 6
    Jinyuan Jia, Yupei Liu, and Neil Zhenqiang Gong:
    BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning.
    IEEE Symposium on Security and Privacy, 2022
    33 cites at Google Scholar
    1674% above average of year
    Last visited: Oct-2022
    Paper: DOI
  7. 7
    Yugeng Liu, Rui Wen, Xinlei He, Ahmed Salem, Zhikun Zhang, Michael Backes, Emiliano De Cristofaro, Mario Fritz, and Yang Zhang:
    ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models.
    USENIX Security Symposium, 2022
    30 cites at Google Scholar
    1513% above average of year
    Last visited: Oct-2022
    Paper: DOI
  8. 8
    Theresa Stadler, Bristena Oprisanu, and Carmela Troncoso:
    Synthetic Data - Anonymisation Groundhog Day.
    USENIX Security Symposium, 2022
    27 cites at Google Scholar
    1352% above average of year
    Last visited: Oct-2022
    Paper: DOI
  9. 9
    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
    26 cites at Google Scholar
    1298% above average of year
    Last visited: Nov-2022
    Paper: DOI
  10. 10
    Nicholas Boucher, Ilia Shumailov, Ross Anderson, and Nicolas Papernot:
    Bad Characters: Imperceptible NLP Attacks.
    IEEE Symposium on Security and Privacy, 2022
    21 cites at Google Scholar
    1029% above average of year
    Last visited: Nov-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
    352 cites at Google Scholar
    2995% above average of year
    Last visited: Oct-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
    232 cites at Google Scholar
    1940% above average of year
    Last visited: Nov-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
    161 cites at Google Scholar
    1316% above average of year
    Last visited: Nov-2022
    Paper: DOI
  4. 4
    Liwei Song and Prateek Mittal:
    Systematic Evaluation of Privacy Risks of Machine Learning Models.
    USENIX Security Symposium, 2021
    114 cites at Google Scholar
    902% above average of year
    Last visited: Nov-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
    114 cites at Google Scholar
    902% above average of year
    Last visited: Nov-2022
    Paper: DOI
  6. 6
    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
    105 cites at Google Scholar
    823% above average of year
    Last visited: Nov-2022
    Paper: DOI
  7. 7
    Eugene Bagdasaryan and Vitaly Shmatikov:
    Blind Backdoors in Deep Learning Models.
    USENIX Security Symposium, 2021
    100 cites at Google Scholar
    779% above average of year
    Last visited: Nov-2022
    Paper: DOI
  8. 8
    Xiaoyu Cao, Minghong Fang, Jia Liu, and Neil Zhenqiang Gong:
    FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.
    Network and Distributed System Security Symposium (NDSS), 2021
    92 cites at Google Scholar
    709% above average of year
    Last visited: Nov-2022
    Paper: DOI
  9. 9
    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
    90 cites at Google Scholar
    691% above average of year
    Last visited: Nov-2022
    Paper: DOI
  10. 10
    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
    86 cites at Google Scholar
    656% above average of year
    Last visited: Nov-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
    372 cites at Google Scholar
    1282% above average of year
    Last visited: Nov-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
    320 cites at Google Scholar
    1088% above average of year
    Last visited: Nov-2022
    Paper: DOI
  3. 3
    Pratyush Mishra, Ryan Lehmkuhl, Akshayaram Srinivasan, Wenting Zheng, and Raluca Ada Popa:
    Delphi: A Cryptographic Inference Service for Neural Networks.
    USENIX Security Symposium, 2020
    204 cites at Google Scholar
    658% above average of year
    Last visited: Nov-2022
    Paper: DOI
  4. 4
    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
    203 cites at Google Scholar
    654% above average of year
    Last visited: Nov-2022
    Paper: DOI
  5. 5
    Marcel Keller:
    MP-SPDZ: A Versatile Framework for Multi-Party Computation.
    ACM Conference on Computer and Communications Security (CCS), 2020
    188 cites at Google Scholar
    598% above average of year
    Last visited: Nov-2022
    Paper: DOI
  6. 6
    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
    177 cites at Google Scholar
    557% above average of year
    Last visited: Nov-2022
    Paper: DOI
  7. 7
    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
    177 cites at Google Scholar
    557% above average of year
    Last visited: Oct-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
    170 cites at Google Scholar
    531% above average of year
    Last visited: Oct-2022
    Paper: DOI
  9. 9
    Philip Daian, Steven Goldfeder, Tyler Kell, Yunqi Li, Xueyuan Zhao, Iddo Bentov, Lorenz Breidenbach, and Ari Juels:
    Flash Boys 2.0: Frontrunning in Decentralized Exchanges, Miner Extractable Value, and Consensus Instability.
    IEEE Symposium on Security and Privacy, 2020
    164 cites at Google Scholar
    509% above average of year
    Last visited: Nov-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
    163 cites at Google Scholar
    505% above average of year
    Last visited: Nov-2022
    Paper: DOI