Bernardo Ferreira

Practical Privacy-Preserving Content-Based Retrieval in Cloud Image Repositories

Storage requirements for visual data have been increasing in recent years, following the emergence of many highly interactive multimedia services and applications for mobile devices in both personal and corporate scenarios. This has been a key driving factor for the adoption of cloud-based data outsourcing solutions. However, outsourcing data storage to the Cloud also leads to new security challenges that must be carefully addressed, especially regarding privacy. In this paper we propose a secure framework for outsourced privacy-preserving storage and retrieval in large shared image repositories. Our proposal is based on IES-CBIR, a novel Image Encryption Scheme that exhibits Content-Based Image Retrieval properties. The framework enables both encrypted storage and searching using Content-Based Image Retrieval queries while preserving privacy against honest-but-curious cloud administrators. We have built a prototype of the proposed framework, formally analyzed and proven its security properties, and experimentally evaluated its performance and retrieval precision. Our results show that IES-CBIR is provably secure, allows more efficient operations than existing proposals, both in terms of time and space complexity, and paves the way for new practical application scenarios.

Management and search of private data on storage clouds

The article presents a solution for storage and management of private data kept in Internet Storage Clouds. The solution supports operations over the data kept ciphered, including reads, writes and searches based on multiple keywords and relevance classification. The approach is based on a middleware architecture supported by homomorphic encryption techniques combined with dynamic indexing mechanisms. The solution preserves conditions of privacy without need to either decipher data during operations in the cloud or transfer the data during searches. The article further describes an implementation prototype of the solution and its evaluation. The performance obtained in different implementation scenarios is analyzed and compared to a solution promoted by AMAZON S3. The evaluation shows that the solution is viable, offers more security and control for the user and does not aggravate conditions of latency and data availability.

Multimodal Indexable Encryption for Mobile Cloud-Based Applications

In this paper we propose MIE, a Multimodal Indexable Encryption framework that for the first time allows mobile applications to securely outsource the storage and search of their multimodal data (i.e. data containing multiple media formats) to public clouds with privacy guarantees. MIE is designed as a distributed framework architecture, leveraging on shared cloud repositories that can be accessed simultaneously by multiple users. At its core MIE relies on Distance Preserving Encodings (DPE), a novel family of encoding algorithms with cryptographic properties that we also propose. By applying DPE to multimodal data features, MIE enables high-cost clustering and indexing operations to be handled by cloud servers in a privacy-preserving way. Experiments show that MIE achieves better performance and scalability when compared with the state of art, with measurable impact on mobile resources and battery life.

Towards an Image Encryption Scheme with Content-Based Image Retrieval Properties

In this paper we introduce a new secure cryptographic scheme, named IES-CBIR, specifically designed for images and their outsourced storage and retrieval in large private image repositories. Our solution enables both encrypted storage and querying using Content Based Image Retrieval (CBIR), while preserving privacy. We have implemented a prototype system around the proposed scheme, and experimentally analyzed its performance when compared to similar proposals for privacy-preserving image retrieval. Our results show that IES-CBIR allows more efficient operations than existing proposals, both in terms of time and space overheads, while enabling less restrictive application scenarios.

TMS: a trusted mail repository service using public storage clouds

In this paper we present the Trusted Mail System (TMS), a dependable Email repository service that explores multiple untrusted storage clouds for storing, accessing and searching private email data. The system architecture provides security and reliability services while leveraging the heterogeneity and diversity offered by different untrusted cloud storage solutions from different service providers. To address dependability issues, TMS enforces a security model that protects confidentiality and integrity of mailboxes stored in those clouds, adding availability, reliability and intrusion-tolerance guarantees. The system uses homomorphic encryption mechanisms and indexing techniques allowing ranked multi-keyword searching operations over encrypted email messages and its contents. We illustrate TMS feasibility from an implemented prototype, evaluating its performance, design options, and services. The experimental results show that the solution is viable, offers reliability and privacy control for the users and does not aggravate conditions of data-access latency and availability.