Big Data SAVE: Secure Anonymous Vault Environment

Soliman, Omar
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There has been great progress in taming the volume, velocity and variation of Big Data. Its volume creates need for increased storage space and improved data handling. Its velocity is concern for the speed and efficiency of applied algorithms and processes. Its variation requires flexibility to handle assorted data-types. However, as with many emerging fields, security has taken a backseat to benchmarks. This has led to retrofitting traditional security techniques ill-suited for Big Data protection, or high-performance setups exposed to data breach. Proposed is an innovative storage system that can provide large-scale, low-overhead data security, akin to safe-deposit boxes. This approach allows for anonymously-shared storage space, discrete levels of access, plausible deniability, and customizable degrees of overall protection (including warrant-proof). A promising factor of this new model is the use of a simple encryption algorithm (proven faster than industry-standard ciphers), that provides inherent attack resiliency and strong backward secrecy.
Cyber Systems and Analytics, Software Technology, Anonymous, Big Data, Encryption, Vault, Warrant-proof
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