Gradient-Based Attacks

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4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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LogiC-Diff: Embedding Security Properties Into AI-Enabled Cyber-Physical Systems
Sep 29, 2026Ziyan An, John Stankovic, Meiyi MaCyber-Physical System Cybersecurity
Department of Computer Science Vanderbilt University Nashville, TN · Department of Computer Science University of Virginia Charlottesville, VA
A Sharp Transition in Data Reconstruction under Differential Privacy
Sep 29, 2026Max Cairney-Leeming, Simone Bombari, Marco MondelliGradient-Based Attacks Distributional Fidelity
Institute of Science and Technology Austria
Stealth Is a Relation, Not a Property: How Event Representations Create Blind Spots for Timing Attacks in Event-Based Perception
Sep 28, 2026Shoaib Ahmed Dipu, Md. Shaown Miah, Kamrul Hasan +1Attack Stealthiness Video Surveillance
Indiana University Indianapolis · Bangladesh University of Engineering and Technology · Tennessee State University
Temporal Gradient Inversion for Private Trajectory Reconstruction in Embodied Reinforcement Learning
Sep 24, 2026Sudip Bhujel, Shanghao Shi, Ruiquan Huang +2Gradient-Based Attacks Offline Reinforcement Learning
Department of Computer Science, University of Kentucky · Department of Computer Science and Engineering, Washington University in St. Louis
Component-Aware Differential Privacy for Federated Multilingual Speech-LLMs
Sep 11, 2026Jordi Luque, Fernando López, Aleix SantStandard Differential-Privacy Gradient-Based Attacks
Scientific Research Telef´onica Innovaci´on Digital Barcelona, Spain · Telef´onica Innovaci´on Digital Universidad Aut´onoma de Madrid Madrid, Spain · Scientific Research Telef´onica Innovaci´on Digital Universitat Polit`ecnica de Catalunya Barcelona, Spain
Cascading Gradient Inversion via LT-Code Inspired Peeling in Federated Learning
Sep 10, 2026Saeed Shariati, Mohsen Alambardar MeybodiFederated Learning Gradient-Based Attacks
Department of Applied Mathematics and Computer Science, Faculty of Mathematics and Statistics, University of Isfahan, Isfahan 81746-73441, Iran
DRIFT: Removing Diffusion Watermarks by Deflecting the Generative Trajectory
Sep 8, 2026Rui Bao, Zheng Gao, Xiaoyu Li +3Watermarks Gradient-Based Attacks
University of New South Wales · Griffith University
TACS: Trajectory-Aware Candidate Selection for LLM Jailbreak Suffix Optimization
Aug 30, 2026Shiliang XiaoJailbreak Attacks Jailbreaks
GENADA: efficient generative time series adversarial attack framework
Aug 12, 2026Michael Baronov, Denis Vorobev, Margarita Rusanova +2Black-Box Adversarial Attacks Gradient-Based Attacks
Moscow Independent Research Institute of Artificial Intelligence · HSE University
MineGrad: Gradient Inversion Attacks on LoRA Fine-Tuning
Aug 2, 2026Hasin Us Sami, Swapneel Sen, Basak GulerGradient-Based Attacks Federated Learning
University of California, Riverside, CA
When cheap gradients fail: the measurement cost of attacking quantum classifiers
Jul 13, 2026Bacui Li, Chandra Thapa, Tansu Alpcan +1Gradient-Based Attacks Gradient
Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, Victoria 3010, Australia · CSIRO Data61, Marsfield, NSW 2122, Australia · School of Computing and Information Systems, University of Melbourne, Parkville, Victoria 3010, Australia
When Certificates Fail: A Unified Safety Framework for Embedded Neural Interface Models
Jul 7, 2026Jasmeet Singh BindraNeural Network Verification Brain-Computer Interface
IKSMHA Center, IIT Mandi
Safety Targeted Embedding Exploit via Refinement
Jul 2, 2026Joshua Adrian CahyonoMultilingual Safety Large Language Model Safety
Nanyang Technological University, Singapore.
Beyond Gradient-Based Attacks: Adversarial Robustness and Explainability Stability in Cybersecurity Classifiers
Jul 2, 2026Mona Rajhans, Vishal KhawareyGradient-Based Attacks Robustness Verification
Palo Alto Networks, Santa Clara, CA, USA · Quicken Inc., Menlo Park, CA, USA
Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks
Jun 24, 2026Rupesh Raj Karn, Johann Knechtel, Ozgur SinanogluGradient-Based Attacks Graph Neural Networks
Center for Cyber Security, New York University, Abu Dhabi, UAE.
TIGER: Inverting Transformer Gradients via Embedding-Subspace Distance Optimization
Jun 16, 2026William Kalikman, Ivo Petrov, Dimitar I. Dimitrov +1Gradient-Based Attacks Federated Learning
ETH Zürich · INSAIT, Sofia University "St. Kliment Ohridski"
S-GBT: Smooth Growth Bound Tensor for Certified Robustness Against Word Substitution Attacks in NLP
Jun 11, 2026Mohammed Bouri, Mohammed Erradi, Adnane SaoudGradient-Based Attacks Robustness Verification
College of Computing, Mohammed VI Polytechnic University, Morocco · CID Development, Morocco · ENSIAS, University Mohamed V of Rabat, Morocco
Reinforcement Learning Disrupts Gradient-Based Adversarial Optimization
Jun 10, 2026Xinhai Zou, Chang Zhao, Alireza Aghabagherloo +3Gradient-Based Attacks Adversarial Training
COSIC, KU Leuven · Leuven, Belgium · Imec +1
CEAR: Certified Ensemble Adversarial Robustness in DNNs
May 31, 2026Daniel Sadig, Mohammadreza Maleki, Hamed Karimi +1Adversarial Training Model-Agnostic Defense
Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada · Vector Institute, Toronto, ON, Canada
Profiling Privacy Preservation Against Gradient Inversion Attacks in Tabular Federated Learning
May 31, 2026Ivo Osterberg Nilsson, Maximilian Birr Engvall, Viktor Valadi +1Federated Learning Gradient-Based Attacks
Department of Computing, Jönköping University, Jönköping, Sweden · Scaleout Systems, Uppsala, Sweden · Department of Information Systems, University of Haifa, Haifa, Israel
EnCAgg: Enhanced Clustering Aggregation for Robust Federated Learning against Dynamic Model Poisoning
May 21, 2026Tianyun Zhang, Zhen Yang, Haozhao Wang +2Federated Learning Gradient-Based Attacks
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China · School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China · Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
SDM: A Powerful Tool for Evaluating Model Robustness
May 19, 2026Xinlei Liu, Tao Hu, Jichao Xie +3Gradient-Based Attacks Adversarial Examples
Information Engineering University, Zhengzhou, China · Key Laboratory of Cyberspace Endogenous Safety & Security of Henan Province, Zhengzhou, China · Key Laboratory of Cyberspace Security Ministry of Education of China, Zhengzhou, China +1
Compositional Adversarial Training for Robust Visual Watermarking
May 16, 2026Anirudh Satheesh, Michael-Andrei Panaitescu-Liess, Andrew Xu +4Watermarks Watermarking
University of Maryland
Fast Adversarial Attacks with Gradient Prediction
May 14, 2026Kamil Ciosek, Aleksandr V. Petrov, Nicolò Felicioni +1Gradient-Based Attacks Black-Box Adversarial Attacks
Spotify
Memory Efficient Full-gradient Attacks (MEFA) Framework for Adversarial Defense Evaluations
May 7, 2026Yuan Du, Mitchel Hill, HanQin CaiGradient-Based Attacks
Department of Statistics and Data Science University of Central Florida Orlando, FL 32816, USA · InnoPeak Technology Palo Alto, CA 94303, USA · Department of Statistics and Data Science Department of Computer Science University of Central Florida Orlando, FL 32816, USA
Sparse Tokens Suffice: Jailbreaking Audio Language Models via Token-Aware Gradient Optimization
May 6, 2026Zheng Fang, Xiaosen Wang, Shenyi Zhang +2Large Language Model Jailbreaks Gradient-Based Attacks
1Wuhan University · 2Huazhong University of Science and Tech · Institute for Math & AI, Wuhan University +2
Graph Reconstruction from Differentially Private GNN Explanations
May 5, 2026Rishi Raj Sahoo, Jyotirmaya Shivottam, Subhankar MishraGraph Neural Networks Gradient-Based Attacks
National Institute of Science Education and Research (NISER), Bhubaneswar, India · Homi Bhabha National Institute, Mumbai, India
Tracing the Dynamics of Refusal: Exploiting Latent Refusal Trajectories for Robust Jailbreak Detection
May 2, 2026Xulin Hu, Che Wang, Wei Yang Bryan Lim +2Refusals Jailbreak Attacks
1Peking University · 2Nanyang Technological University · 3Beijing Jiaotong University
Dynamic Adversarial Fine-Tuning Reorganizes Refusal Geometry
Apr 29, 2026Wenhao Lan, Shan Li, Xinhua Lai +4Refusals Large Language Model Safety
University of Chinese Academy of Sciences, Beijing, China · Inner Mongolia University of Technology, Inner Mongolia, China · Tsinghua University, Beijing, China +1
No More Guessing: a Verifiable Gradient Inversion Attack in Federated Learning
Apr 16, 2026Francesco Diana, Chuan Xu, André Nusser +1Gradient-Based Attacks Federated Learning
Université Côte d’Azur, France · Inria, France · CNRS, France +1
Temperature Scaling Attack Disrupting Model Confidence in Federated Learning
Feb 6, 2026Kichang Lee, Jaeho Jin, JaeYeon Park +2Federated Learning Gradient-Based Attacks
Yonsei University · Dankook University
HyperNet-Adaptation for Diffusion-Based Test Case Generation
Jan 21, 2026Oliver Weißl, Vincenzo Riccio, Severin Kacianka +1Test Generation Gradient-Based Attacks
Technical University of Munich, Germany · University of Udine, Italy · Independent Researcher, Germany +1
Auditing Information Disclosure During Large-Scale Gradient-Based Training via Gradient Uniqueness
Oct 13, 2025Sleem Abdelghafar, Maryam Aliakbarpour, Christopher JermaineGradient-Based Attacks Membership Inference Attacks
Rice University Houston, USA
NonTextual Target Attack
Oct 3, 2025Xinzhe Huang, Wenjing Hu, Tianhang Zheng +6Attacker Large Language Model Gradient-Based Attacks
State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou 310007, China · Hangzhou High-Tech Zone, Binjiang Institute of Blockchain and Data Security, Hangzhou 310053, China · School of Cyberspace Security, Nanjing University of Science and Technology, Nanjing 210094, China +3
Meta-SecAlign: Training LLMs against Prompt Injection for Robust Agents
Jul 3, 2025Sizhe Chen, Arman Zharmagambetov, David Wagner +1Indirect Prompt Injection Gradient-Based Attacks
FAIR at Meta · UC Berkeley
GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning
Dec 17, 2024Rui Zhang, Ka-Ho ChowFederated Learning Gradient-Based Attacks
HKU Musketeers Foundation Institute of Data Science · The University of Hong Kong · Hong Kong SAR, China +1
Privacy-Preserving Logistic Regression Training with A Faster Gradient Variant
Jan 26, 2022John ChiangPrivacy-Preserving Machine Learning Gradient-Based Attacks

Sep 29, 2026, cs.CRJ/K move · Enter open · S save

LogiC-Diff: Embedding Security Properties Into AI-Enabled Cyber-Physical Systems

Ziyan An, John Stankovic, Meiyi Ma

Department of Computer Science Vanderbilt University Nashville, TN · Department of Computer Science University of Virginia Charlottesville, VA

Cyber-Physical System Cybersecurity Gradient-Based Attacks Security Diffusion Models

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AI-enabled Cyber-Physical Systems (CPS) are highly vulnerable to adversarial and anomalous inputs, where small perturbations can induce cascading errors and unsafe control actions. Existing approaches, such as rule-based filtering, training-time regularization, or diffusion-based reconstruction, either operate outside the model or lack mechanisms to incorporate formal security specifications into the prediction process. In this paper, we take the first step toward embedding security properties directly into AI-enabled CPS, enabling predictive models to enforce system-level constraints during inference rather than relying on external defenses. We introduce a logic-conditioned bi-stage diffusion framework that integrates Signal Temporal Logic (STL) specifications into forecasting. STL serves as a first-class conditioning signal that guides both an input repair stage and an output refinement stage, allowing the model to jointly mitigate adversarial perturbations and enforce desired temporal behaviors to satisfy security-critical properties. We evaluate our approach on two real-world multivariate CPS forecasting datasets under a diverse set of physical sensor and cyber attacks. Across sensor faults, gradient-based attacks, adaptive attacks, and varying attack strengths, our method consistently improves robustness and specification compliance, degrades more gracefully as attack strength increases, and generalizes better to unseen attacks. Ablation studies on specification coverage and quality further show that embedding logical security properties yields gains unattainable by reconstruction-based methods alone, highlighting a new direction for integrating formal methods with generative models in secure CPS.

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