arXiv AI

Secure AI Watermarking Framework for IP Protection in Multi-Tenant Cloud Platforms

arXiv:2608. 02656v1 Announce Type: cross Abstract: The Secured data safe guard transaction with multi-tenant environments run on private-protected authenticate platforms runs by secured handed environments that emerges with the expansion of cloud-based AI services.

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.

By Md. Arifur Rahman, B. M. Taslimul Haque, Md. Iqbal Hossan, Md. Serajul Kabir Chowdhury Rubel
Hugging Face Trending Papers
Jun 1

SECUREVENT: Hybrid AI/ML Security Monitoring for Distributed Event-Based Systems

Distributed event-based systems have become a common substrate for Internet-scale publish/subscribe services, IoT telemetry, cloud-native microservices, and security operations pipelines. Their loose coupling and asynchronous delivery improve scalability, but they also expand the attack surface: publishers, brokers, subscribers, topics, schemas, and temporal ordering can each be abused without a single component observing the whole behavior.

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.

By Diego Cajaraville-Aboy, Ana Fern\'andez-Vilas, Rebeca P. D\'iaz-Redondo, Manuel Fern\'andez-Veiga, Pablo Picallo-L\'opez
arXiv Machine Learning
Jun 29

CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat Detection

arXiv:2504. 01882v2 Announce Type: replace Abstract: The use of DNS over HTTPS (DoH) tunneling by an attacker to hide malicious activity within encrypted DNS traffic poses a serious threat to network security, as it allows malicious actors to bypass traditional monitoring and intrusion detection systems while evading detection by conventional traffic analysis techniques.

By Diego Cajaraville-Aboy, Marta Moure-Garrido, Carlos Beis-Penedo, Carlos Garcia-Rubio, Rebeca P. D\'iaz-Redondo, Celeste Campo, Ana Fern\'andez-Vilas, Manuel Fern\'andez-Veiga