Analysis of cryptographic authentication and manipulation detection methods for Big Data

Abstract

The emergence of Big Data has made it possible to obtain more information about the customer and competitive base, as well as about market trends. Therefore, the desire of criminals to gain unauthorized access to this data also increases in direct proportion. However, not enough attention is paid to security issues of Big Data systems and their creation does not take into account the information security component. The purpose of the article is to develop approaches to the cyber protection of Big Data, which are stored and transmitted by telecommunication communication channels when responding to a request, namely their integrity and authentication. The main problems when working with Big Data are analyzed. Based on the results of the analysis of Big Data protection problems, a cryptographic transformation of data indexes when they are stored in the database and when transmitted in the form of hash codes is proposed to increase the efficiency of search by user requests. The expediency of using crypto-code constructions on elliptic curves of various types of modifications to form a pseudo-random substrate in order to increase the crypto-resistance of transmitted messages is proven. When forming hash codes, it is advisable to use modified elliptical codes, and under stricter conditions, the level of cryptographic resistance of authentication codes can be increased due to hybrid crypto-code constructions. A pseudo-random substrate can be represented by varieties that must equally ensure the necessary transformations and preservation of universality properties by the UMAC algorithm.