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A curated list of academic events on AI Security & Privacy
License: MIT License
ai-security-and-privacy-events's Introduction
A curated list of AI Security & Privacy academic events
Artificial Intelligence and Security (CCS 2008- )Deep Learning Security and Privacy (S&P 2018- )Dependable and Secure Machine Learning (DSN 2018- )Security Architectures for Generative-AI Systems (S&P 2024 )AI System with Confidential Computing (NDSS 2024 )
Machine Learning & Artificial Intelligence
Red Teaming GenAI: What Can We Learn from Adversaries? (NeurIPS 2024 )Safe Generative AI (NeurIPS 2024 )Towards Safe & Trustworthy Agents (NeurIPS 2024 )Socially Responsible Language Modelling Research (NeurIPS 2024 )Next Generation of AI Safety (ICML 2024 )Trustworthy Multi-modal Foundation Models and AI Agents (ICML 2024 )Secure and Trustworthy Large Language Models (ICLR 2024 )Reliable and Responsible Foundation Models (ICLR 2024 )Privacy Regulation and Protection in Machine Learning (ICLR 2024 )Responsible Language Models (AAAI 2024 )Privacy-Preserving Artificial Intelligence (AAAI 2020-2024 )Practical Deep Learning in the Wild (CAI 2024, AAAI 2022-2023 )Backdoors in Deep Learning: The Good, the Bad, and the Ugly (NeurIPS 2023 )Trustworthy and Reliable Large-Scale Machine Learning Models (ICLR 2023 )Backdoor Attacks and Defenses in Machine Learning (ICLR 2023 )Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data (ICLR 2022 )Security and Safety in Machine Learning Systems (ICLR 2021 )Robust and Reliable Machine Learning in the Real World (ICLR 2021 )Towards Trustworthy ML: Rethinking Security and Privacy for ML (ICLR 2020 )Safe Machine Learning: Specification, Robustness and Assurance (ICLR 2019 )New Frontiers in Adversarial Machine Learning (ICML 2022-2023 )Theory and Practice of Differential Privacy (ICML 2021-2022 )Uncertainty & Robustness in Deep Learning (ICML 2020-2021 )A Blessing in Disguise: The Prospects and Perils of Adversarial Machine Learning (ICML 2021 )Security and Privacy of Machine Learning (ICML 2019 )Socially Responsible Machine Learning (NeurIPS 2022 , ICLR 2022 , ICML 2021 )ML Safety (NeurIPS 2022 )Privacy in Machine Learning (NeurIPS 2021 )Dataset Curation and Security (NeurIPS 2020 )Security in Machine Learning (NeurIPS 2018 )Machine Learning and Computer Security (NeurIPS 2017 )Adversarial Training (NeurIPS 2016 )Reliable Machine Learning in the Wild (NeurIPS 2016 )Adversarial Learning Methods for Machine Learning and Data Mining (KDD 2019-2022 )Privacy Preserving Machine Learning (FOCS 2022, CCS 2021, NeurIPS 2020, CCS 2019, NeurIPS 2018 )SafeAI (AAAI 2019-2022 )Adversarial Machine Learning and Beyond (AAAI 2022 )Towards Robust, Secure and Efficient Machine Learning (AAAI2021 )AISafety (IJCAI 2019-2022 )
The Dark Side of Generative AIs and Beyond (ECCV 2024 )Trust What You learN (ECCV 2024 )Privacy for Vision & Imaging (ECCV 2024 )Adversarial Machine Learning on Computer Vision (CVPR 2024 , CVPR 2023 , CVPR 2022 , CVPR 2020 )Secure and Safe Autonomous Driving (CVPR 2023 )Adversarial Robustness in the Real World (ICCV 2023 , ECCV 2022 , ICCV 2021 , CVPR 2021 , ECCV 2020 , CVPR 2020 , CVPR 2019 )The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security (CVPR 2021 , ECCV 2020 , CVPR 2019 , CVPR 2018 , CVPR 2017 )Responsible Computer Vision (ECCV 2022 )Safe Artificial Intelligence for Automated Driving (ECCV 2022 )Adversarial Learning for Multimedia (ACMMM 2021 )Adversarial Machine Learning towards Advanced Vision Systems (ACCV 2022 )
Natural Language Processing
Online Misinformation- and Harm-Aware Recommender Systems (RecSys 2021 , RecSys 2020 )Adversarial Machine Learning for Recommendation and Search (CIKM 2021 )
Machine Learning & Artificial Intelligence
Quantitative Reasoning About Data Privacy in Machine Learning (ICML 2022 )Foundational Robustness of Foundation Models (NeurIPS 2022 )Adversarial Robustness - Theory and Practice (NeurIPS 2018 )Towards Adversarial Learning: from Evasion Attacks to Poisoning Attacks (KDD 2022 )Adversarial Robustness in Deep Learning: From Practices to Theories (KDD 2021 )Adversarial Attacks and Defenses: Frontiers, Advances and Practice (KDD 2020 )Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications (ICDM 2020 )Adversarial Machine Learning for Good (AAAI 2022 )Adversarial Machine Learning (AAAI 2018 )
Adversarial Machine Learning in Computer Vision (CVPR 2021 )Practical Adversarial Robustness in Deep Learning: Problems and Solutions (CVPR 2021 )Adversarial Robustness of Deep Learning Models (ECCV 2020 )Deep Learning for Privacy in Multimedia (ACMMM 2020 )
Natural Language Processing
Vulnerabilities of Large Language Models to Adversarial Attacks (ACL 2024 )Robustness and Adversarial Examples in Natural Language Processing (EMNLP 2021 )Deep Adversarial Learning for NLP (NAACL 2019 )
Special Track on Safe and Robust AI (AAAI 2023 )Special Session on Adversarial Learning for Multimedia Understanding and Retrieval (ICMR 2022 )Special Session on Adversarial Attack and Defense (APSIPA 2022 )Special Session on Information Security meets Adversarial Examples (WIFS 2019 )
ai-security-and-privacy-events's People
Contributors
ai-security-and-privacy-events's Issues
Hi Zhengyu,
Prof. Zhengyu Zhao -
Thank you for this curated list! It is very useful to track venues that focus on our niche, but growing combination of fields. I have otherwise had to use this list to select security venues, along with this deadline tracker for submissions.
I would like to add CAMLIS as a conference that specialises in ML and security. I will be attending this IEEE conference , which states its focus is AI in cyber security and might be a another addition for your list.
Hope this helps.
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