A Comparative Study of Recent Advances in Big Data for Security and Privacy

Kourid, Ahlam; Chikhi, Salim

doi:10.1007/978-981-10-4600-1_23

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…The security and privacy issue in big data is an ongoing challenge requiring continued research and development. Particularly on the platform side, security measures have been mainly limited to providing access control on data sets, data analytics jobs, resource scheduling/sharing, or setups [7], [8]. However, there is a pressing need to address key management in a decentralized environment, especially when utilizing MPC.…”

Section: Introductionmentioning

confidence: 99%

Secure Key Management for Multi-Party Computation in MOZAIK

Marquet,

Moeyersons,

Pohle

et al. 2023

2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

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The immense growth of data from the proliferation of Internet of Things (IoT) devices presents opportunities and challenges for privacy engineering. On the one hand, this data can be harnessed for personalized services, cost savings, and environmental benefits. On the other hand, (new) legislation must be complied with and privacy risks arise from collecting and processing of such data. Distributed privacy-preserving analytics offers a promising solution, providing insights while also protecting privacy. However, this approach has new challenges and risks, such as key management and confidentiality. When designing a data marketplace which offers distributed privacy-preserving analytics, the key management comes with different threats, which require a solution adapted to the distributed architecture.In this context, the paper presents a comprehensive, endto-end secure system called MOZAIK for privacy-preserving data collection, analysis, and sharing. The article focuses on the key management aspect of the secure multi-party computation (MPC) component in a distributed privacypreserving analytics architecture and the specific challenges created by introducing MPC. The proposed solution involves temporary storage of (symmetric) key shares and publickey encryption schemes to ensure secure key management for privacy-preserving computation. Our solution has the potential to be applied in other MPC-based setups, making it a valuable addition to the field of privacy engineering. By addressing key management challenges and risks, MOZAIK enhances data protection while enabling valuable insights from IoT data.

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Section: Introductionmentioning

confidence: 99%