AI Threat Alert
Defense MEDIUM
The Autonomy Tax: Defense Training Breaks LLM Agents
Shawn Li, Yue Zhao
Large language model (LLM) agents increasingly rely on external tools (file operations, API calls, database transactions) to autonomously complete...
AI Security Research
2,583+ academic papers on AI security, attacks, and defenses
Total
2,583
Attack
994
Benchmark
740
Defense
355
Tool
275
Survey
146
Showing 541–560 of 1,930 papers
Clear filters Attack HIGH
Automated Membership Inference Attacks: Discovering MIA Signal Computations using LLM Agents
Toan Tran, Olivera Kotevska, Li Xiong
Membership inference attacks (MIAs), which enable adversaries to determine whether specific data points were part of a model's training dataset, have...
Defense LOW
kRAIG: A Natural Language-Driven Agent for Automated DataOps Pipeline Generation
Rohan Siva, Kai Cheung, Lichi Li +1 more
Modern machine learning systems rely on complex data engineering workflows to extract, transform, and load (ELT) data into production pipelines....
Benchmark LOW
Box Maze: A Process-Control Architecture for Reliable LLM Reasoning
Zou Qiang
Large language models (LLMs) demonstrate strong generative capabilities but remain vulnerable to hallucination and unreliable reasoning under...
Attack HIGH
On Optimizing Multimodal Jailbreaks for Spoken Language Models
Aravind Krishnan, Karolina Stańczak, Dietrich Klakow
As Spoken Language Models (SLMs) integrate speech and text modalities, they inherit the safety vulnerabilities of their LLM backbone and an expanded...
Attack HIGH
FedTrident: Resilient Road Condition Classification Against Poisoning Attacks in Federated Learning
Sheng Liu, Panos Papadimitratos
FL has emerged as a transformative paradigm for ITS, notably camera-based Road Condition Classification (RCC). However, by enabling collaboration,...
Defense MEDIUM
SAVeS: Steering Safety Judgments in Vision-Language Models via Semantic Cues
Carlos Hinojosa, Clemens Grange, Bernard Ghanem
Vision-language models (VLMs) are increasingly deployed in real-world and embodied settings where safety decisions depend on visual context. However,...
Attack LOW
Towards Verifiable AI with Lightweight Cryptographic Proofs of Inference
Pranay Anchuri, Matteo Campanelli, Paul Cesaretti +4 more
When large AI models are deployed as cloud-based services, clients have no guarantee that responses are correct or were produced by the intended...
Benchmark MEDIUM
Functional Subspace Watermarking for Large Language Models
Zikang Ding, Junhao Li, Suling Wu +3 more
Model watermarking utilizes internal representations to protect the ownership of large language models (LLMs). However, these features inevitably...
Survey HIGH
Measuring and Exploiting Confirmation Bias in LLM-Assisted Security Code Review
Dimitris Mitropoulos, Nikolaos Alexopoulos, Georgios Alexopoulos +1 more
Security code reviews increasingly rely on systems integrating Large Language Models (LLMs), ranging from interactive assistants to autonomous agents...
Attack HIGH
Cyber-Resilient Digital Twins: Discriminating Attacks for Safe Critical Infrastructure Control
Mohammadhossein Homaei, Iman Khazrak, Rubén Molano +2 more
Industrial Cyber-Physical Systems (ICPS) face growing threats from cyber-attacks that exploit sensor and control vulnerabilities. Digital Twin (DT)...
Attack HIGH
Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
Jiahao Zhang, Yilong Wang, Suhang Wang
Graph neural networks (GNNs) are widely used for learning from graph-structured data in domains such as social networks, recommender systems, and...
Tool HIGH
Prompt Control-Flow Integrity: A Priority-Aware Runtime Defense Against Prompt Injection in LLM Systems
Md Takrim Ul Alam, Akif Islam, Mohd Ruhul Ameen +2 more
Large language models (LLMs) deployed behind APIs and retrieval-augmented generation (RAG) stacks are vulnerable to prompt injection attacks that may...
Benchmark LOW
The Validity Gap in Health AI Evaluation: A Cross-Sectional Analysis of Benchmark Composition
Alvin Rajkomar, Pavan Sudarshan, Angela Lai +1 more
Background: Clinical trials rely on transparent inclusion criteria to ensure generalizability. In contrast, benchmarks validating health-related...
Survey MEDIUM
Toward Reliable, Safe, and Secure LLMs for Scientific Applications
Saket Sanjeev Chaturvedi, Joshua Bergerson, Tanwi Mallick
As large language models (LLMs) evolve into autonomous "AI scientists," they promise transformative advances but introduce novel vulnerabilities,...
Attack MEDIUM
Retrieval-Augmented LLMs for Security Incident Analysis
Xavier Cadet, Aditya Vikram Singh, Harsh Mamania +6 more
Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts,...
Attack MEDIUM
Retrieval-Augmented LLMs for Security Incident Analysis
Xavier Cadet, Aditya Vikram Singh, Harsh Mamania +6 more
Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts,...
Benchmark HIGH
Machine Learning for Network Attacks Classification and Statistical Evaluation of Machine Learning for Network Attacks Classification and Adversarial Learning Methodologies for Synthetic Data Generation
Iakovos-Christos Zarkadis, Christos Douligeris
Supervised detection of network attacks has always been a critical part of network intrusion detection systems (NIDS). Nowadays, in a pivotal time...
Benchmark MEDIUM
Parameter-Efficient Modality-Balanced Symmetric Fusion for Multimodal Remote Sensing Semantic Segmentation
Haocheng Li, Juepeng Zheng, Shuangxi Miao +4 more
Multimodal remote sensing semantic segmentation enhances scene interpretation by exploiting complementary physical cues from heterogeneous data....
Benchmark MEDIUM
WeatherReasonSeg: A Benchmark for Weather-Aware Reasoning Segmentation in Visual Language Models
Wanjun Du, Zifeng Yuan, Tingting Chen +3 more
Existing vision-language models (VLMs) have demonstrated impressive performance in reasoning-based segmentation. However, current benchmarks are...
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