In cloud-based Internet of Things (IoT), sharing of data with third-party services and other users, inherently incurs potential risk and leads to unique security and privacy concerns. Existing cryptographic solutions ensure the security of IoT data, but due to their significant computational overhead, most of them are not suitable for resource-constrained IoT devices. To address these concerns, we propose a data protection system to store encrypted IoT data in a cloud while still allowing query processing over the encrypted data. More importantly, our proposed system features a novel encrypted data sharing scheme based on Boneh-Goh-Nissim (BGN) cryptosystem, with revocation capabilities and in-situ key update. We perform exhaustive experiments on real datasets, primarily to assess the feasibility of the proposed system on resource-constrained IoT devices. We next measure the computation overhead, storage overhead and throughput. The experimental results show that our system is not only feasible, but also provides a high level of security. Furthermore, the results show that our system is 34% more computationally faster, requires 25% less storage and 15% more throughput than the best performed system in the state-of-the-art.

Don't hesitate to share! A novel IoT data protection scheme based on BGN cryptosystem

Halder S.;Conti M.
2019

Abstract

In cloud-based Internet of Things (IoT), sharing of data with third-party services and other users, inherently incurs potential risk and leads to unique security and privacy concerns. Existing cryptographic solutions ensure the security of IoT data, but due to their significant computational overhead, most of them are not suitable for resource-constrained IoT devices. To address these concerns, we propose a data protection system to store encrypted IoT data in a cloud while still allowing query processing over the encrypted data. More importantly, our proposed system features a novel encrypted data sharing scheme based on Boneh-Goh-Nissim (BGN) cryptosystem, with revocation capabilities and in-situ key update. We perform exhaustive experiments on real datasets, primarily to assess the feasibility of the proposed system on resource-constrained IoT devices. We next measure the computation overhead, storage overhead and throughput. The experimental results show that our system is not only feasible, but also provides a high level of security. Furthermore, the results show that our system is 34% more computationally faster, requires 25% less storage and 15% more throughput than the best performed system in the state-of-the-art.
2019
Proceedings of the ACM Symposium on Applied Computing
9781450359337
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3339767
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