Data security issues in cloud scenarios

The amount of data created, stored, and processed has enormously increased in the last years. Today, millions of devices are connected to the Internet and generate a huge amount of (personal) data that need to be stored and processed using scalable, efficient, and reliable computing infrastructures. Cloud computing technology can be used to respond to these needs. Although cloud computing brings many benefits to users and companies, security concerns about the cloud still represent the major impediment for its wide adoption. We briefly survey the main challenges related to the storage and processing of data in the cloud. In particular, we focus on the problem of protecting data in storage, supporting fine-grained access, selectively sharing data, protecting query privacy, and verifying the integrity of computations

Cloud Security: Issues and Concerns

The cloud has emerged as a successful computing paradigm, allowing users and organizations to rely on external providers to store and process their data and make it available to others. An increasingly important priority, if there is to be wide adoption and acceptance of cloud computing, is for data owners and users to have security guarantees. Guaranteeing security means ensuring confidentiality and integrity of data, access to it, and computations with it, and ensuring availability of data and services to legitimate users in compliance with agreements with the providers. In this chapter, we present an overview of the main security issues and concerns arising in the cloud scenario, in particular with respect to the storage, management, and processing of data

Data Security and Privacy in the Cloud

Relying on the cloud for storing data and performing computations has become a popular solution in today\u2019s society, which demands large data collections and/or analysis over them to be readily available, for example, to make knowledge-based decisions. While bringing undeniable benefits to both data owners and end users accessing the outsourced data, moving to the cloud raises a number of issues, ranging from choosing the most suitable cloud provider for outsourcing to effectively protecting data and computation results. In this paper, we discuss the main issues related to data protection arising when data and/or computations over them are moved to the cloud. We also illustrate possible solutions and approaches for addressing such issues

Privacy of Outsourced Data

Abstract. Data outsourced to an external storage server are usually encrypted since there is the common assumption that all data are equally sensitive. The encrypted data however cannot be efficiently queried and their selective release is not possible or require the application of specific solutions. To overcome these problems, new proposals have been recently developed, which are based on a fragmentation technique possibly combined with encryption. The main advantage of these proposals is that they limit the use of encryption, thus improving query execution efficiency. In this paper, we describe such fragmentation-based approaches focusing in particular on the different data fragmentation models proposed in the literature. We then conclude the paper with a discussion on some research directions

Empowering Owners with Control in Digital Data Markets

We propose an approach for allowing data owners to trade their data in digital data market scenarios, while keeping control over them. Our solution is based on a combination of selective encryption and smart contracts deployed on a blockchain, and ensures that only authorized users who paid an agreed amount can access a data item. We propose a safe interaction protocol for regulating the interplay between a data owner and subjects wishing to purchase (a subset of) her data, and an audit process for counteracting possible misbehaviors by any of the interacting parties. Our solution aims to make a step towards the realization of data market platforms where owners can benefit from trading their data while maintaining control

Towards privacy-aware identity management

The overall goal of the PRIME project (Privacy and Identity Management for Europe) is the development of a privacy-enhanced identity management system that allows users to control the release of their personal information. The PRIME architecture includes an Access Control component allowing the enforcement of protection requirements on personal identifiable information (PII). The overall goal of the PRIME project (Privacy and Identity Management for Europe) is the development of a privacy-enhanced identity management system that allows users to control the release of their personal information. The PRIME architecture includes an Access Control component allowing the enforcement of protection requirements on personal identifiable information (PII)

Privacy in Microdata Release: Challenges, Techniques, and Approaches

Releasing and disseminating useful microdata while ensuring that no personal or sensitive information is improperly exposed is a complex problem, heavily investigated by the scientific community in the past couple of decades. Various microdata protection approaches have then been proposed, achieving different privacy requirements through appropriate protection techniques. This chapter discusses the privacy risks that can arise in microdata release and illustrates some well-known privacy-preserving techniques and approaches

Open world reasoning in semantics-aware access control: A preliminary study

We address the relationships between theoretical foundations of Description Logics and practical applications of security-oriented Semantic Web techniques. We first describe the advantages of semantics-aware Access Control and review the state of the art; we also introduce the basics of Description Logics and the novel semantics they share. Then we translate the principle underlying the Little House Problem of DL into a real-world use case: by applying Open World Reasoning to the Knowledge Base modelling a Virtual Organization, we derive information not achievable with traditional Access Control methodologies. With this example, we also show that a general problem such as ontology mapping can take advantage of the enhanced semantics underlying OWL Lite and OWL DL to handle under-specified concepts