arXiv AI
Aug 11
Defining Decentralization: An Ontological Perspective
arXiv:2608. 09748v1 Announce Type: cross Abstract: Decentralization as a concept in computer science has existed for over half a century.
Trustworthy, Explainable, and Sustainable Decentralized Intelligence for 6G Networks
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arXiv AI
Jun 6
Cognitive Threat Intelligence and Explainable Federated Security Analytics for distributed Infrastructure Systems
arXiv:2606. 05701v1 Announce Type: cross Abstract: The increasing adoption of distributed infrastructure systems, cloud computing, Internet of Things (IoT) technologies, and edge-based architectures has significantly expanded the cybersecurity attack surface and introduced increasingly sophisticated cyber threats.
arXiv AI
2d ago
Blockchain-Enabled Artificial Intelligence and AI Agents for Secure Data Sharing and Cybersecurity Applications
The paper reviews four studies that combine blockchain and AI to secure data sharing, model integrity, and autonomous decision-making in distributed systems. It highlights how blockchain’s immutability, decentralized consensus, and verifiable provenance can address trust gaps in training data, real‑time monitoring, and automated code remediation. The authors propose a layered architecture integrating hardened models, blockchain‑anchored provenance, AI anomaly detection, and smart‑contract‑governed multi‑agent remediation, and outline open challenges in scalability, privacy‑transparency trade‑offs, and governance.
arXiv Machine Learning
Jun 9
AI-Native Closed-Loop Security for 6G-Enabled Cyber-Physical Systems: From Edge Detection to Network-Wide Mitigation
arXiv:2606. 08173v1 Announce Type: cross Abstract: In sixth-generation (6G) networks, billions of cyber-physical systems (CPSs) - autonomous vehicles, smart grids, industrial robots, and remote-surgical equipment - will run over ultra-reliable low-latency slices, collapsing the gap between a remote breach and physical harm to milliseconds, a budget perimeter firewalls and centralised security operations centres cannot meet.
arXiv Machine Learning
Jun 29
Decentralized Orchestration Architecture for Fluid Computing: A Secure Distributed AI Use Case
arXiv:2603. 12001v2 Announce Type: replace-cross Abstract: Distributed AI and IoT applications increasingly execute across heterogeneous resources spanning end devices, edge/fog infrastructure, and cloud platforms, often under different administrative domains.
arXiv AI
Jul 16
Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges
arXiv:2607. 13045v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a key paradigm for privacy-preserving collaborative model training across distributed and heterogeneous data sources.
arXiv AI
Aug 7
When Agentic AI Meets Integrated Sensing and Communication
arXiv:2608. 05792v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) is transforming Integrated Sensing and Communication (ISAC) from a function-oriented physical-layer technology into a goal-driven, closed-loop intelligent system, a paradigm we term AISAC.
arXiv AI
Jul 22
The Economics of Autonomy: Real-Time Risk Indexing for Insurable AI-Driven 6G Systems
arXiv:2607. 18267v1 Announce Type: cross Abstract: The transition to sixth-generation (6G) networks transforms wireless infrastructure into a cognitive substrate supporting Vehicle-to-Everything (V2X), Industrial IoT (IIoT), and Integrated Sensing and Communication (ISAC).
arXiv Machine Learning
Jun 18
Automated Byzantine-Resilient Clustered Decentralized Federated Learning for Battery Intelligence in Connected EVs
arXiv:2605. 21115v2 Announce Type: replace-cross Abstract: Federated learning (FL) has emerged as a promising paradigm for managing electric vehicle (EV) battery data in intelligent transportation systems (ITS), enabling privacy-preserving tasks such as anomaly detection and capacity estimation.
arXiv AI
Jul 28
Decentralized Granular Access Control for Agentic AI Systems in Critical Infrastructure
arXiv:2607. 22611v1 Announce Type: new Abstract: The deployment of autonomous AI agents in production infrastructure introduces fundamental security challenges that traditional role-based access control (RBAC) models cannot address.
arXiv Machine Learning
Jul 22
Decentralized Multi-agent Reinforcement Learning for Resilient Critical Infrastructures
arXiv:2607. 18359v1 Announce Type: cross Abstract: Critical infrastructures are increasingly distributed, interdependent, and exposed to evolving disruptions, making resilience a central requirement for their operation and control.
arXiv AI
Jun 6
Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework
arXiv:2606. 05710v1 Announce Type: cross Abstract: The increasing penetrations of the critical infrastructure sector in the United States with intelligent digital technologies have greatly increased exposure to advanced cyber adversaries and operational vulnerabilities.