AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
The IoV BCFL+ framework promises scalability linked with self-evolution in security architecture, taking a big step in IoV intrusion detection state and strongly paving way for future intelligent transportation security systems.
A trust-based federated learning framework in which a smart contract enabled by blockchain oversees client registration, model update logging, hash-based integrity verification, trust score calculation, malicious node penalization, aggregation approval, and decentralised audit logging is proposed.
The proposed Blockchain-Fog Computing Collaborative Framework with Deep Attention-based Collusion Detection and Automated Accountability (BF3-ACDA) framework combines a hierarchical blockchain–fog architecture with an attention-based collusion graph neural network (AttnCol-GNN), whose reputation-aware attention coeffic...
An engineering framework for privacy-preserving federated threat intelligence sharing that integrates trust-aware robust aggregation with blockchain-based integrity anchoring is proposed that confirms the effectiveness of the proposed trust-aware aggregation mechanism in mitigating malicious updates while preserving st...
Results indicate that decentralized, interoperable, and energy-aware intrusion detection is feasible for large-scale IoT deployments, particularly in resource-constrained IoT environments.
The rapid evolution of decentralized finance (DeFi) has ushered in transformative opportunities for global financial inclusion, digital asset management, and permissionless transactions. However, the growth of DeFi also presents significant challenges related to data integrity, security, scalability, and regulatory com...
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
The effort aims to help U.S. learners from kindergarten to community college, with an emphasis on math, making, and the constructive use of AI.
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