Data Encryption For Multi-Server Searches
The expansion of cloud storage leads to significant advances in encryption technologies, trying to respond to the challenges posed by distributed architectures. An example is a work published by a team of researchers from a University, mainly focused on multi-server search tasks. In this context, the MS-SDC system promises to reduce file upload time by up to 64%, providing the right balance between performance and security.
Due to security and compliance demands, cloud providers must implement encryption technologies that substantially reduce performance in favor of security. This affects many tasks related to data hosted in the cloud, and multi-server searches are one of them. To improve performance, the researchers propose a new Symmetric Search Encryption (SSE) system for operations run on multiple servers simultaneously.
This scheme allows dividing the uploaded file in encrypted form into blocks and distributing them among various storage providers. This approach would be more efficient than uploading entire files to each of the lookup servers, each containing only a subset of files or blocks to improve security.
This system also extracts keywords for each uploaded file, which are stored so that the user can perform searches without having to apply encryption techniques again. This makes searching your files much faster, such as in indexed local storage environments, similar to searching on personal computers.
The researchers’ proposal is essentially similar to others that other researchers have made but includes additional features such as a multi-threaded application to speed up loading time. A randomly created master key generator for each uploaded file is different from current approaches, where a key is generated for each document, increasing the risk of hacking.
Its creators point out that the MS-SDC system differs from the others due to its ease of use and robustness since it can be run in any browser and applied to any file. And they say that their experiments demonstrate greater effectiveness in terms of load and search times and provide additional features that make it well suited for current and future cloud storage environments.
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