Practical Techniques Building on Encryption for Protecting and Managing Data in the Cloud

Abstract

Abstract. Companies as well as individual users are adopting cloud solutions at an over-increasing rate for storing data and making them accessible to others. While migrating data to the cloud brings undeniable benefits in terms of data availability, scalability, and reliability, data protection is still one of the biggest concerns faced by data owners. Guaranteeing data protection means ensuring confidentiality and integrity of data and computations over them, and ensuring data availability to legitimate users. In this chapter, we survey some approaches for protecting data in the cloud that apply basic cryptographic techniques, possibly complementing them with additional controls, to the aim of producing efficient and effective solutions that can be used in practice.

An authorization model for multi provider queries

“…The query optimizer can choose to apply different encryption schemes (e.g., deterministic or randomized encryption) depending on the operations to be executed on the encrypted values [10,22]. We propose to adopt, for each attribute, the scheme providing highest protection, while supporting the operations to be executed on the attribute's encrypted values.…”

Self-Enforcing Access Control for Encrypted RDF

“…In spite of inherent performance improvements, such a solution is still dominated by the available number of peers and the -potentially large -number of encrypted triples each peer would have to process. Current efficient solutions for querying encrypted data are based on (a) using indexes to speed up the decryption process by reducing the set of potential solutions; or (b) making use of specific encryption schemes that support the execution of operations directly over encrypted data [13]. Our solution herein follows the first approach, whereas the use of alternative and directly encryption mechanisms (such as homomorphic encryption [28]) is complementary and left to future work.…”

“…However, the structure should also be protected as hashbased indexes can represent a security risk if the data server is compromised. State-of-the-art solutions (cf., [13]) propose the inclusion of spurious information, that the query processor must filter out in order to obtain the final query result.…”

Empowering Owners with Control in Digital Data Markets

“…While effective, this simple solution could not be efficient since it might create more tokens than necessary. To reduce the number of tokens, the key derivation structure is typically enriched with additional vertices whose key is used for derivation only [3], [5]. While in cloud-based scenarios such additional vertices are typically associated with groups of users, the considered scenario would benefit from the definition of keys associated with groups of resources.…”