17 papers
Transparent Identity Verification Approach Using MPC and Efficient Credential Status Handling
Istiaque Ahmed, Shoji Kasahara, Kentaroh Toyoda +2
A secure and privacy-preserving identity verification process is essential for digital ecosys- tems. Current eKYC frameworks that rely on Zero-Knowledge Proofs (ZKPs) face high com…
Revoked but Still Authoritative: An Empirical Study of Revocation Enforcement in Agent-Memory Systems
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
Long-running language-model agents depend on persistent memory. Many agent-memory systems preserve history through soft revocation: a contradicted fact is marked invalid and retain…
ACEA: An Adversarial Co-Evolution Arena for Head-to-Head Red-Team and Blue-Team LLM Testing
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
Automated red-team attacks and blue-team defenses for large language models (LLMs) are advancing quickly. However, attackers and defenders are built and tested in isolation, and th…
Claim-Level Confidence Calibration for Reliable Decision Making with Large Language Models
Toghrul Abbasli, Kentaroh Toyoda, Yuan Wang +1
Large Language Models (LLMs) increasingly support decision-making in high-stakes domains, but they often hallucinate and express confidence that is misaligned with factual correctn…
AMT-X: Phase-Structured Multi-Turn Red-Teaming with Checklist-Gated Evaluation
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
Safety evaluation of large language models (LLMs) relies largely on single-turn attack datasets and single-judge scoring, underestimating risk from adaptive multi-turn adversaries…
The Insurability Frontier of AI Risk: Mapping Threats to Affirmative Coverage, Silent Exposures, and Exclusions
Alex Leung, Rex Zhang, Ervin Ling +2
The rapid diffusion of agentic AI has created a new coverage problem for commercial insurance: some AI-mediated losses are now affirmatively insured, some create silent-AI exposure…
From Control Boundary to Insurance Claim: Reconstructing AI-Mediated Losses Through the CER Framework
Alex Leung, Rex Zhang, Kentaroh Toyoda +1
AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, because the relevant state cha…
Bastet: A Fine-Grained Expert-Labeled Dataset for DeFi Smart Contract Vulnerability Detection
Wan-Hsuan Hsu, Wei-Hsin Wang, Cheng-Yu Liou +2
Smart contract vulnerabilities in Decentralized Finance (DeFi) protocols resulted in over 1.49 billion USD in confirmed losses in 2024 alone, across 192 incidents [1]. As LLM-based…
IPI-proxy: An Intercepting Proxy for Red-Teaming Web-Browsing AI Agents Against Indirect Prompt Injection
Chia-Pei, Chen, Kentaroh Toyoda +2
Web-browsing AI agents are increasingly deployed in enterprise settings under strict whitelists of approved domains, yet adversaries can still influence them by embedding hidden in…
Knowledge-Free Correlated Agreement for Incentivizing Federated Learning
Leon Witt, Togrul Abbasli, Kentaroh Toyoda +2
We introduce Knowledge-Free Correlated Agreement (KFCA) to reward client contributions in federated learning (FL) without relying on ground truth, a public test set, or distributio…
AI Identity: Standards, Gaps, and Research Directions for AI Agents
Takumi Otsuka, Kentaroh Toyoda, Alex Leung
AI agents are now running real transactions, workflows, and sub-agent chains across organizational boundaries without continuous human supervision. This creates a problem no curren…
MCPThreatHive: Automated Threat Intelligence for Model Context Protocol Ecosystems
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
The rapid proliferation of Model Context Protocol (MCP)-based agentic systems has introduced a new category of security threats that existing frameworks are inadequately equipped t…
Democratizing Federated Learning with Blockchain and Multi-Task Peer Prediction
Leon Witt, Kentaroh Toyoda, Wojciech Samek +1
The synergy between Federated Learning and blockchain has been considered promising; however, the computationally intensive nature of contribution measurement conflicts with the st…
MCP-38: A Comprehensive Threat Taxonomy for Model Context Protocol Systems (v1.0)
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
The Model Context Protocol (MCP) introduces a structurally distinct attack surface that existing threat frameworks, designed for traditional software systems or generic LLM deploym…
Quasi-Orthogonality and Polysemy: The Limits of Quantum Analogy in Large Language Models
Karl Svozil
We analyze two geometric aspects of meaning-sensitive behavior in next-token models. First, high-dimensional geometry permits exponentially many nearly orthogonal feature direction…
Blockchain Data Analysis in the Era of Large-Language Models
Kentaroh Toyoda, Xiao Wang, Mingzhe Li +3
Blockchain data analysis is essential for deriving insights, tracking transactions, identifying patterns, and ensuring the integrity and security of decentralized networks. It play…
MStableChain: Towards Multi-Native Stablecoins in EVM-Compatible Blockchain for Stable Fee and Mass Adoption
Mingzhe Li, Bo Gao, Kentaroh Toyoda +9
Traditional blockchain systems, such as Ethereum, typically rely on a \emph{single volatile cryptocurrency for transaction fees}. This leads to fluctuating transaction fee prices a…