Cryptography in Business Intelligence and Data Analytics

Abstract

This chapter aims to determine the role of cryptography in the provision of secure applications of business intelligence and data analytics. Through this, the legal implications for weak cryptographic systems are illustrated in areas such as safeguarding customer information, trade secrets, and intellectual property in the context of data-driven businesses. Among the key areas explained are the various data encryption methods in transit (HTTPS/TLS) and at rest (database/disk encryption), including more advanced techniques such as homomorphic encryption which allows the calculations to be performed on encrypted data without the need to decrypt it. Searchable encryption, privacy retrieval, and multi-party sub-computation will also be examined as means of analysis over encrypted datasets. These technologies encompass, but are not limited to, secure outsourcing of analytics, privacy-preserving machine learning, blockchain-based data sharing, and safekeeping of personally identifiable information (PII).