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An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense QSignAI: Quantum-Randomness-Seeded Identity Signatures at the Intersection of AI for Science and Science for AI A Standardized Ontology for Intent-Based Security Management in Autonomous Networks Code as a Weapon: A Consensus-Labeled Prompt Bank for Measuring Coding-Model Compliance with Malicious-Code Requests Cordyceps: Covert Control Attacks on LLMs via Data Poisoning SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness Mechanistic origins of catastrophic forgetting: why RL preserves circuits better than SFT? Red-Teaming Agent Execution Contexts: Open-World Security Evaluation on OpenClaw From Specification to Deployment: Empirical Evidence from a W3C VC + DID Trust Infrastructure for Autonomous Agents PLAGUE: Plug-and-play framework for Lifelong Adaptive Generation of Multi-turn Exploits VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks Feedback Lunch: Learned Feedback Codes for Secure Communications Noise Aggregation Analysis Driven by Small-Noise Injection: Efficient Membership Inference for Diffusion Models A First Look at the Security Issues in the Model Context Protocol Ecosystem Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems CTIConnect: A Benchmark for Retrieval-Augmented LLMs over Heterogeneous Cyber Threat Intelligence RAG-Pull: Turning Retrieval into a Code-Injection Channel via Invisible Unicode Perturbations MEASER: Malware embedding attacks on open-source LLMs ADMIT: Few-shot Knowledge Poisoning Attacks on RAG-based Fact Checking Fall into a Pit, Gain in a Wit: Cognitive-Guided Harmful Meme Detection via Misjudgment Risk Pattern Retrieval When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models A2AS: Agentic AI Runtime Security and Self-Defense Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG) Correcting Prompt Dependence in LLM Benchmarks: A Bayesian Hierarchical Model with Embedding-Space Clustering From surveillance to signalling: escalation channels as environmental controls for agentic AI Quantitative Certification of Agentic Tool Selection Bypassing Prompt Guards in Production with Controlled-Release Prompting Where Do Backdoors Live? 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Benchmarking Overestimation under the One-Time-Pad-Based Framework ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation From Multi-Agent Systems and the Semantic Web to Agentic AI: A Unified Narrative of the Web of Agents White-Basilisk: A Hybrid Model for Code Vulnerability Detection Taming Data Challenges in ML-based Security Tasks Using Generative AI Optimus: A Robust Defense Framework for Mitigating Toxicity while Fine-Tuning Conversational AI Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model! InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy Logit-Gap Steering: A Forward-Pass Diagnostic for Alignment Robustness VERA: Variational Inference Framework for Jailbreaking Large Language Models Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem Exploring the Secondary Risks of Large Language Models SHIELD: Secure Hypernetworks for Incremental Expansion Learning Defense Benchmarking Misuse Mitigation Against Covert Adversaries Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG Mitigating Disparate Impact of Differentially Private Learning through Bounded Adaptive Clipping Organizational Adaptation to Generative AI in Cybersecurity Efficient Preimage Approximation for Neural Network Certification Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs \texttt{Range-Arithmetic}: Verifiable Deep Learning Inference on an Untrusted Party PARASITE: Conditional System Prompt Poisoning to Hijack LLMs Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs Secure LLM Fine-Tuning via Safety-Aware Probing Can Large Language Models Really Recognize Your Name? PoLO: Proof-of-Learning and Proof-of-Ownership at Once with Chained Watermarking Towards Efficient and Exact Forgetting Services in Pre-Trained-Model-based Continual Learning Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents Think Twice Before You Act: Enhancing Agent Behavioral Safety with Thought Correction A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron? AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents Erased but Not Forgotten: How Backdoors Compromise Concept Erasure DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion Quantum Autoencoder for Multivariate Time Series Anomaly Detection
Accumulate: An identity-based blockchain protocol with cross-chain support, human-readable addresses, and key management capabilities
Kyle Michelson, Anjali Sridharan, Umut Can Cabuk, Ethan Reesor, · 2022-04-14 · via cs.CR updates on arXiv.org

The Accumulate Protocol ("Accumulate") is an identity-based, Delegated Proof of Stake (DPoS) blockchain designed to power the digital economy through interoperability with Layer-1 blockchains, integration with enterprise tech stacks, and interfacing with the World Wide Web. Accumulate bypasses the trilemma of security, scalability, and decentralization by implementing a chain-of-chains architecture in which digital identities with the ability to manage keys, tokens, data, and other identities are treated as their own independent blockchains. This architecture allows these identities, known as Accumulate Digital Identifiers (ADIs), to be processed and validated in parallel over the Accumulate network. Each ADI also possesses a hierarchical set of keys with different priority levels that allow users to manage their security over time and create complex signature authorization schemes that expand the utility of multi-signature transactions. A two token system provides predictable costs for enterprise users, while anchoring all transactions to Layer-1 blockchains provides enterprise-grade security to everyone.

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