Related papers: A Multi-Server Information-Sharing Environment for…

We consider the critical problem of distributed learning over data while keeping it private from the computational servers. The state-of-the-art approaches to this problem rely on quantizing the data into a finite field, so that the…

Cloud computing is getting mature, and the interoperability and standardization of the clouds is still waiting to be solved. This paper discussed the interoperability among clouds about message transmission, data transmission and virtual…

A large amount of data and applications need to be shared with various parties and stakeholders in the cloud environment for storage, computation, and data utilization. Since a third party operates the cloud platform, owners cannot fully…

Unlike other industries in which intellectual property is patentable, the financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the…

Imagine a group of citizens willing to collectively contribute their personal data for the common good to produce socially useful information, resulting from data analytics or machine learning computations. Sharing raw personal data with a…

Many recent IT companies use cloud services for deploying their products, mainly because of their convenience. As such, cloud assets have become a new attack surface, and the concept of cloud security has emerged. However, cloud security is…

Data Management portfolio within an organization has seen an upsurge in initiatives for compliance, security, repurposing and storage within and outside the organization. When such initiatives are being put to practice care must be taken…

Cloud computing has become the de facto paradigm for delivering software to system users, with organizations and enterprises of all sizes making use of cloud services in some way. On the surface, adopting the cloud appears to be a very…

The growing complexity of Internet of Things (IoT) environments, particularly in cross-domain data sharing, presents significant security challenges. Existing data-sharing schemes often rely on computationally expensive cryptographic…

As cloud services become central in an increasing number of applications, they process and store more personal and business-critical data. At the same time, privacy and compliance regulations such as GDPR, the EU ePrivacy regulation, PCI,…

Cloud computing provisions computer resources at a cost-effective way based on demand. Therefore it has become a viable solution for big data analytics and artificial intelligence which have been widely adopted in various domain science.…

With the increasing popularity of the cloud, clients oursource their data to clouds in order to take advantage of unlimited virtualized storage space and the low management cost. Such trend prompts the privately oursourcing computation,…

We present a case study on the strategic planning of a security operations center in a typical, modern, mid-size organization. Against the backdrop of the company's multi-cloud strategy a distributed approach envisioning the involvement of…

Data sharing in large consortia, such as research collaborations or industry partnerships, requires addressing both organizational and technical challenges. A common platform is essential to promote collaboration, facilitate exchange of…

Modern distributed applications in healthcare, supply chain, and the Internet of Things handle a large amount of data in a diverse application setting with multiple stakeholders. Such applications leverage advanced artificial intelligence…

Blockchain has attracted a broad range of interests from start-ups, enterprises and governments to build next generation applications in a decentralized manner. Similar to cloud platforms, a single blockchain-based system may need to serve…

In the current paradigm of digital personalized services, the centralized management of personal data raises significant privacy concerns, security vulnerabilities, and diminished individual autonomy over sensitive information. Despite…

In the age of cloud computing, data privacy protection has become a major challenge, especially when sharing sensitive data across cloud environments. However, how to optimize collaboration across cloud environments remains an unresolved…

This paper focuses on designing a privacy-preserving Machine Learning (ML) inference protocol for a hierarchical setup, where clients own/generate data, model owners (cloud servers) have a pre-trained ML model, and edge servers perform ML…

In modern information systems different information features, about the same individual, are often collected and managed by autonomous data collection services that may have different privacy policies. Answering many end-users' legitimate…