Computing on Masked Data to improve the security of big data

Abstract

Organizations that make use of large quantities of information require the ability to store and process data from central locations so that the product can be shared or distributed across a heterogeneous group of users. However, recent events underscore the need for improving the security of data stored in such untrusted servers or databases. Advances in cryptographic techniques and database technologies provide the necessary security functionality but rely on a computational model in which the cloud is used solely for storage and retrieval. Much of big data computation and analytics make use of signal processing fundamentals for computation. As the trend of moving data storage and computation to the cloud increases, homeland security missions should understand the impact of security on key signal processing kernels such as correlation or thresholding. In this article, we propose a tool called Computing on Masked Data (CMD), which combines advances in database technologies and cryptographic tools to provide a low overhead mechanism to offload certain mathematical operations securely to the cloud. This article describes the design and development of the CMD tool.

SoK: Cryptographically Protected Database Search

“…CryptDB replicates most DBMS functionality with a performance overhead of under 30% [15]. This approach has been extended to NoSQL key-value stores [157], [158]. Arx is built on a NoSQL keyvalue store called mongoDB [63].…”

An Investigation towards Paradigm Shift of Cloud Computing Approach and Need of New Security Protocol

“…It has been found that majority of the paper in this topic is just a discussion manuscript, so this paper discusses about 5 most relevant implementation work that has been carried out in last 5 years. Gadepally et al [21] have presented a cryptography based approach to encipher a big data while performing analysis of it. The system uses D4M (Dynamic Distributed Dimensional Data Model) for processing the unstructured data and have used Galois Field Cryptography with AES encryption approach.…”

Untitled

“…However, these advantages also create a single point where adversaries may try to attack the confidentiality, integrity and/or availability of sensitive information stored or being processed [26].…”

“…The sensitivity of data being processed in the cloud is increasing; and it is possible to make use of cryptographic advances to secure processing in the cloud to address a growing veracity of big data [26].…”