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Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
Requirement Analyses and Evaluations of Blockchain Platfo...
Kenji Saito, Akimitsu Shiseki, Mitsuyasu Takada, Hiroki Yamamoto · 2021-03-05 · via cs.CR updates on arXiv.org

It is said that blockchain will contribute to the digital transformation of society in a wide range of ways, from the management of public and private documents to the traceability in various industries, as well as digital currencies. A number of so-called blockchain platforms have been developed, and experiments and applications have been carried out on them. But are these platforms really conducive to practical use of the blockchain concept? To answer the question, we need to better understand what the technology called blockchain really is. We need to sort out the confusion we see in understanding what blockchain was invented for and what it means. We also need to clarify the structure of its applications. This document provides a generic model of understanding blockchain and its applications. We introduce design patterns to classify the platforms. We categorize possible use cases by identifying the structure among applications, and organize the functional, performance, operational and legal requirements for each such case. Based on the categorization and criteria, we evaluated and compared the following platforms: Hyperledger Fabric, Hyperledger Iroha, Hyperledger Indy, Ethereum, Quorum/Hyperledger Besu, Ethereum 2.0, Polkadot, Corda and BBc-1. We have tried to be fair in our evaluations and comparisons, but we also expect to provoke discussion. The intended readers for this document is anyone involved in development of application systems who wants to understand blockchain and their platforms, including non-engineers and non-technologists. The assessments in this document will allow readers to understand the technological requirements for the blockchain platforms, to question existing technologies, and to choose the appropriate platforms for the applications they envision. The comparisons hopefully will also be useful as a guide for designing new technologies.