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"Secure Replication-Based Outsourced Computation Using Smart Contracts" by Willy Susilo, Fuchun Guo et al.

The replication-Based Outsourced Computation (RBOC) mechanism allows a client to outsource the same computing job to multiple contractors and the honest contractors will get paid in the incentivized system based on the fact that a majority of contractors will honestly perform the computation. As self-executing contracts, smart contracts are utilized in the decentralized blockchain networks to execute coded programs automatically transparently, and publicly. It is natural to apply smart contracts to RBOC to improve performance by setting smart contracts as the converter between the client and contractors to reduce the load on the client. However, it is infeasible to directly combine these two blocks together because the data including returned computing results from contractors in the decentralized blockchain are in the form of plaintexts such that some lazy contractors could copy others' results as their own and still get paid, which will compromise the security of RBOC. The exist ....

Based Outsourced Computation , Azy Contractors , Utsourced Computation , Performance Evaluation , Public Key , Ublic Key Encryption With Equality Test , Smart Contracts ,

"Cloud-Based Outsourcing for Enabling Privacy-Preserving Large-Scale No" by Anmin Fu, Zhenzhu Chen et al.

It is inevitable and evident that outsourcing complicated intensive tasks to public cloud vendors would be the primary option for resource-constrained clients in order to save cost. Unfortunately, the public cloud vendors are usually untrusted. They may inadvertently leak the data or misuse the user's data, compromise user's privacy or intentionally corrupt computational results to make the system unreliable. It is therefore important how to stop this happening whilst embracing the computational power of public cloud vendors. Non-negative matrix factorization (NMF) is a significant method for conducting data dimension reduction, which has been widely used in large-scale data processing. Nevertheless, due to its non-polynomial hardness, NMF cannot be conducted efficiently using local computation resources, especially when dealing with big data. Motivated by this issue, we address this by presenting a novel outsourced scheme for NMF (O-NMF), which aims to lessen clients' c ....

Dimensionality Reduction , Onnegative Matrix Factorization Nmf , Utsourced Computation , Privacy Preserving ,