Biblio

Filters: Author is Shafagh, Hossein  [Clear All Filters]
2019-02-08
Viand, Alexander, Shafagh, Hossein.  2018.  Marble: Making Fully Homomorphic Encryption Accessible to All. Proceedings of the 6th Workshop on Encrypted Computing & Applied Homomorphic Cryptography. :49-60.

With the recent explosion of data breaches and data misuse cases, there is more demand than ever for secure system designs that fundamentally tackle today's data trust models. One promising alternative to today's trust model is true end-to-end encryption without however compromising user experience nor data utility. Fully homomorphic encryption (FHE) provides a powerful tool in empowering users with more control over their data, while still benefiting from computing services of remote services, though without trusting them with plaintext data. However, due to the complexity of fully homomorphic encryption, it has remained reserved exclusively for a small group of domain experts. With our system Marble, we make FHE accessible to the broader community of researchers and developers. Marble takes away the complexity of setup and configuration associated with FHE schemes. It provides a familiar programming environment. Marble allows rapid feasibility assessment and development of FHE-based applications. More importantly, Marble benchmarks the overall performance of an FHE-based application, as part of the feasibility assessment. With real-world application case-studies, we show the practicality of Marble.

2018-09-28
Shafagh, Hossein, Hithnawi, Anwar, Burkhalter, Lukas, Fischli, Pascal, Duquennoy, Simon.  2017.  Secure Sharing of Partially Homomorphic Encrypted IoT Data. Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. :29:1–29:14.
IoT applications often utilize the cloud to store and provide ubiquitous access to collected data. This naturally facilitates data sharing with third-party services and other users, but bears privacy risks, due to data breaches or unauthorized trades with user data. To address these concerns, we present Pilatus, a data protection platform where the cloud stores only encrypted data, yet is still able to process certain queries (e.g., range, sum). More importantly, Pilatus features a novel encrypted data sharing scheme based on re-encryption, with revocation capabilities and in situ key-update. Our solution includes a suite of novel techniques that enable efficient partially homomorphic encryption, decryption, and sharing. We present performance optimizations that render these cryptographic tools practical for mobile platforms. We implement a prototype of Pilatus and evaluate it thoroughly. Our optimizations achieve a performance gain within one order of magnitude compared to state-of-the-art realizations; mobile devices can decrypt hundreds of data points in a few hundred milliseconds. Moreover, we discuss practical considerations through two example mobile applications (Fitbit and Ava) that run Pilatus on real-world data.
2018-05-09
Shafagh, Hossein, Burkhalter, Lukas, Hithnawi, Anwar, Duquennoy, Simon.  2017.  Towards Blockchain-based Auditable Storage and Sharing of IoT Data. Proceedings of the 2017 on Cloud Computing Security Workshop. :45–50.
Today the cloud plays a central role in storing, processing, and distributing data. Despite contributing to the rapid development of IoT applications, the current IoT cloud-centric architecture has led into a myriad of isolated data silos that hinders the full potential of holistic data-driven analytics within the IoT. In this paper, we present a blockchain-based design for the IoT that brings a distributed access control and data management. We depart from the current trust model that delegates access control of our data to a centralized trusted authority and instead empower the users with data ownership. Our design is tailored for IoT data streams and enables secure data sharing. We enable a secure and resilient access control management, by utilizing the blockchain as an auditable and distributed access control layer to the storage layer. We facilitate the storage of time-series IoT data at the edge of the network via a locality-aware decentralized storage system that is managed with the blockchain technology. Our system is agnostic of the physical storage nodes and supports as well utilization of cloud storage resources as storage nodes.