Related papers: Stateless Snowflake: A Cloud-Agnostic Distributed …

Swarms of autonomous devices are increasing in ubiquity and size, making the need for rethinking their hardware-software system stack critical. We present HiveMind, the first swarm coordination platform that enables programmable execution…

As organizations move toward production deployments of AI agents, which execute non-deterministic workflows, maintain stateful sessions, and often operate with privileged access to internal services, the engineering challenge shifts from…

This paper offers a prototype of a Hyperledger Fabric-IPFS based network architecture including a smart contract based encryption scheme that meant to improve the security of user's data that is being uploaded to the distributed ledger. A…

Federated learning (FL) is proving to be one of the most promising paradigms for leveraging distributed resources, enabling a set of clients to collaboratively train a machine learning model while keeping the data decentralized. The…

Operating a scalable and reliable server application, such as publish/subscribe (pub/sub) systems, requires tremendous development efforts and resources. The emerging serverless paradigm simplifies the development and deployment of highly…

Enterprise adoption of cloud-based AI agents faces a fundamental privacy dilemma: leveraging powerful cloud models requires sharing sensitive data, while local processing limits capability. Current agent frameworks like MCP and A2A assume…

With the ever-increasing usage of serverless computing in both industry and academia, it is essential to understand the mechanisms that power the underlying platforms. As serverless is more than ten years old, there are different platforms…

Technologies for composition of loosely-coupled web services in a modular and flexible way are in high demand today. On the one hand, the services must be flexible enough to be reused in a variety of contexts. On the other hand, they must…

This paper represents "Cloudlab", a comprehensive, cloud - native laboratory designed to support network security research and training. Built on Google Cloud and adhering to GitOps methodologies, Cloudlab facilitates the the creation,…

Presented study introduces a novel distributed cloud-edge framework for autonomous multi-UAV systems that combines the computational efficiency of neuromorphic computing with nature-inspired control strategies. The proposed architecture…

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the Multiscale…

Cloud-native is an approach to building and running scalable applications in modern cloud infrastructures, with the Kubernetes container orchestration platform being often considered as a fundamental cloud-native building block. In this…

This paper introduces a novel and fully unsupervised framework for conditional GAN training in which labels are automatically obtained from data. We incorporate a clustering network into the standard conditional GAN framework that plays…

Device-independent quantum key distribution (QKD) can permit the superior security even with unknown devices. In practice, however, the realization of device-independent QKD is technically challenging because of its low noise tolerance. In…

With the ubiquitous computing of providing services and applications at anywhere and anytime, cloud computing is the best option as it offers flexible and pay-per-use based services to its customers. Nevertheless, security and privacy are…

Verifiable delegation in digital identity systems remains unresolved across centralized, federated, and self-sovereign identity (SSI) environments, particularly where both human users and autonomous AI agents must exercise and transfer…

FaaS (Function-as-a-Service) revolutionized cloud computing by replacing persistent virtual machines with dynamically allocated resources. This shift trades locality and statefulness for a pay-as-you-go model more suited to variable and…

Limited resources (such as energy, computing power, storage, and so on) make it impractical for wireless sensor networks (WSNs) to deploy traditional security schemes. In this paper, a hierarchical key management scheme is proposed on the…

Creation of a synthetic dataset that faithfully represents the data distribution and simultaneously preserves privacy is a major research challenge. Many space partitioning based approaches have emerged in recent years for answering…

Using public cloud services for storing and sharing confidential data requires end users to cryptographically protect both the data and the access to the data. In some cases, the identity of end users needs to remain confidential against…