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Computer Science

D-Index
53
Citations
16111
World Ranking
4718
National Ranking
2191

Research.com Recognitions

  • 2017 - ACM Senior Member

Overview

Prateek Mittal is affiliated with Princeton University in the United States and has a research focus primarily in the field of Computer Science, with a significant number of publications totaling 178. Their work spans various subfields including Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computer Vision and Pattern Recognition, and Hardware and Architecture.

The main topics covered in Mittal's research include:

  • Adversarial Robustness in Machine Learning
  • Privacy-Preserving Technologies in Data
  • Internet Traffic Analysis and Secure E-voting
  • Anomaly Detection Techniques and Applications
  • Advanced Malware Detection Techniques
  • Network Security and Intrusion Detection
  • Cryptography and Data Security

Mittal's recent scholarly outputs include the following papers:

  • Advances and Open Problems in Federated Learning, 2020, published in Foundations and Trends® in Machine Learning
  • Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning, 2021, published in DOAJ (Directory of Open Access Journals)
  • RobustBench: a standardized adversarial robustness benchmark, 2020, published in arXiv (Cornell University)
  • Systematic Evaluation of Privacy Risks of Machine Learning Models, 2020, published in arXiv (Cornell University)
  • Visual Adversarial Examples Jailbreak Aligned Large Language Models, 2024, published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators in Mittal's research include:

  • Vikash Sehwag
  • Saeed Mahloujifar
  • Chong Xiang
  • Ashwinee Panda
  • Jiachen T. Wang

The venues where Mittal has most commonly published are:

  • arXiv (Cornell University), with 67 publications
  • Proceedings on Privacy Enhancing Technologies, with 5 publications
  • Communications of the ACM, with 2 publications
  • Zenodo (CERN European Organization for Nuclear Research), with 2 publications
  • Foundations and Trends® in Machine Learning, with 1 publication

Mittal was awarded the ACM Senior Member distinction in 2017. The recognition highlights standing within the professional computing community.

Best Publications

  • Advances and Open Problems in Federated Learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • Advances and open problems in federated learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • SybilInfer: Detecting Sybil Nodes using Social Networks.

    George Danezis;Prateek Mittal

  • EASiER: encryption-based access control in social networks with efficient revocation

    Sonia Jahid;Prateek Mittal;Nikita Borisov

  • Analyzing Federated Learning through an Adversarial Lens

    Arjun Nitin Bhagoji;Supriyo Chakraborty;Prateek Mittal;Seraphin B. Calo

  • BotGrep: finding P2P bots with structured graph analysis

    Shishir Nagaraja;Prateek Mittal;Chi-Yao Hong;Matthew Caesar

  • Privacy Risks of Securing Machine Learning Models against Adversarial Examples

    Liwei Song;Reza Shokri;Prateek Mittal

  • Evolution of social-attribute networks: measurements, modeling, and implications using google+

    Neil Zhenqiang Gong;Wenchang Xu;Ling Huang;Prateek Mittal

  • BlackIoT: IoT botnet of high wattage devices can disrupt the power grid

    Saleh Soltan;Prateek Mittal;H. Vincent Poor

  • DARTS: Deceiving Autonomous Cars with Toxic Signs

    Chawin Sitawarin;Arjun Nitin Bhagoji;Arsalan Mosenia;Mung Chiang

  • SybilBelief: A Semi-Supervised Learning Approach for Structure-Based Sybil Detection

    Neil Zhenqiang Gong;Mario Frank;Prateek Mittal

  • Enhancing robustness of machine learning systems via data transformations

    Arjun Nitin Bhagoji;Daniel Cullina;Chawin Sitawarin;Prateek Mittal

  • Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning

    Sameer Wagh;Shruti Tople;Fabrice Benhamouda;Eyal Kushilevitz

  • Denial of service or denial of security

    Nikita Borisov;George Danezis;Prateek Mittal;Parisa Tabriz

  • Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples.

    Changchang Liu;Supriyo Chakraborty;Prateek Mittal

  • RAPTOR: routing attacks on privacy in tor

    Yixin Sun;Anne Edmundson;Laurent Vanbever;Oscar Li

  • Towards a Timely Causality Analysis for Enterprise Security.

    Yushan Liu;Mu Zhang;Ding Li;Kangkook Jee

  • DECENT: A decentralized architecture for enforcing privacy in online social networks

    S. Jahid;S. Nilizadeh;P. Mittal;N. Borisov

  • Dimensionality Reduction as a Defense against Evasion Attacks on Machine Learning Classifiers.

    Arjun Nitin Bhagoji;Daniel Cullina;Prateek Mittal

  • Cachet: a decentralized architecture for privacy preserving social networking with caching

    Shirin Nilizadeh;Sonia Jahid;Prateek Mittal;Nikita Borisov

  • RobustBench: a standardized adversarial robustness benchmark.

    Francesco Croce;Maksym Andriushchenko;Vikash Sehwag;Edoardo Debenedetti

  • HYDRA: Pruning adversarially robust neural networks

    Vikash Sehwag;Shiqi Wang;Prateek Mittal;Suman Jana

Frequent Co-Authors

Mung Chiang
Mung Chiang Purdue University West Lafayette
Nikita Borisov
Nikita Borisov University of Illinois at Urbana-Champaign
Sanjeev R. Kulkarni
Sanjeev R. Kulkarni Princeton University
Shouling Ji
Shouling Ji Zhejiang University
Dawn Song
Dawn Song University of California, Berkeley
Nick Feamster
Nick Feamster University of Chicago
H. Vincent Poor
H. Vincent Poor Princeton University
Jennifer Rexford
Jennifer Rexford Princeton University
Neil Zhenqiang Gong
Neil Zhenqiang Gong Duke University
Matthew Caesar
Matthew Caesar University of Illinois at Urbana-Champaign

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