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Cloud computing helps reduce costs, increase business agility and deploy solutions with a high return on investment for many types of applications. However, data security is of premium importance to many users and often restrains their…
The emerging paradigm of data economy can constitute an unmissable and attractive opportunity for companies that aim to consider their data as valuable assets. To fully leverage this opportunity, data owners need to have specific and…
Data cooperatives with fiduciary obligations to members provide a promising direction for the empowerment of individuals through their own personal data. A data cooperative can manage, curate and protect access to the personal data of…
Scientific problems that depend on processing large amounts of data require overcoming challenges in multiple areas: managing large-scale data distribution, controlling co-placement and scheduling of data with compute resources, and…
The Internet of Things (IoT) has become increasingly popular in people's daily lives. The pervasive IoT devices are encouraged to share data with each other in order to better serve the users. However, users are reluctant to share sensitive…
As large-scale theft of data from corporate servers is becoming increasingly common, it becomes interesting to examine alternatives to the paradigm of centralizing sensitive data into large databases. Instead, one could use cryptography and…
Orchestrating service-oriented workflows is typically based on a design model that routes both data and control through a single point - the centralised workflow engine. This causes scalability problems that include the unnecessary…
Large amount of data is often required to train and deploy useful machine learning models in industry. Smaller enterprises do not have the luxury of accessing enough data for machine learning, For privacy sensitive fields such as banking,…
Locating data efficiently is a key process in every distributed data storage solution and particularly those deployed in multi-site environments, such as found in Cloud and Fog computing. Nevertheless, the existing protocols dedicated to…
Edge Computing (EC) offers an infrastructure that acts as the mediator between the Cloud and the Internet of Things (IoT). The goal is to reduce the latency that we enjoy when relying on Cloud. IoT devices interact with their environment to…
Edge computing is a promising solution to enable low-latency IoT applications, by shifting computation from remote data centers to local devices, less powerful but closer to the end user devices. However, this creates the challenge on how…
The distributed edge storage system can store data collected at the edge of the network in a decentralised manner, with low latency, high security, and flexibility. Traditional edge-distributed storage systems only consider one single…
Spot instances are virtual machines offered at 60-90% lower cost that can be reclaimed at any time, with only a short warning period. Spot instances have already been used to significantly reduce the cost of processing workloads in the…
Data is a precious resource in today's society, and is generated at an unprecedented and constantly growing pace. The need to store, analyze, and make data promptly available to a multitude of users introduces formidable challenges in…
Data security and availability for operational use are frequently seen as conflicting goals. Research on searchable encryption and homomorphic encryption are a start, but they typically build from encryption methods that, at best, provide…
Enforcing data protection and privacy rules within large data processing applications is becoming increasingly important, especially in the light of GDPR and similar regulatory frameworks. Most modern data processing happens on top of a…
Data sharing among partners---users, organizations, companies---is crucial for the advancement of data analytics in many domains. Sharing through secure computation and differential privacy allows these partners to perform private…
Secure multiparty computations enable the distribution of so-called shares of sensitive data to multiple parties such that the multiple parties can effectively process the data while being unable to glean much information about the data (at…
In this paper, we introduce a data capsule model, a self-contained and self-enforcing data container based on emerging self-sovereign identity standards, blockchain, and attribute-based encryption. A data capsule allows for a transparent,…
This paper presents a case for exploiting the synergy of dedicated and opportunistic network resources in a distributed hosting platform for data stream processing applications. Our previous studies have demonstrated the benefits of…