Homomorphic Encryption: The ‘Holy Grail’ for Big Data Analytics and Legal Compliance in the Pharmaceutical and Healthcare Sector?

Abstract

The pharmaceutical and healthcare sector is a prime target for cybercriminals around the world. These cyber-attacks represent significant challenges in the context of data protection and data security. The General Data Protection Regulation (GDPR) imposes strict rules regarding the processing and analysis of personal data. In conventional approaches, data analysts request data from various sources. Then, they anonymise or pseudonymise the data using various tools and techniques. These methods often use powerful algorithms to ensure a high level of security. However, these methods tend to either reduce the quality of data for further analysis or they expose the data while decrypting it for analysis. Homomorphic Encryption (HE) has recently been touted as the 'Holy Grail' of cryptography since it allows the analysis of big data sets without ever needing to decrypt and thus compromising the confidentiality of the data. This provides a whole new layer of protection and at the same time allows the processing of data for secondary use and scientific research. While HE is not a new technology, it is still in the early stages of development. In this piece, we will introduce a new automated tool for searching and analysing encrypted data using HE techniques, which is being developed within the scope of the EnergyShield project. 1

Hash-Comb: A Hierarchical Distance-Preserving Multi-Hash Data Representation for Collaborative Analytics

“…This embedding process is a simple translation from the hexadecimal hash value to a numerical representation. While it is true that this mapping introduces an ordering between dimensions 10 where a distance could be…”

“…Our work is motivated by widespread concerns that HE encryption techniques may not guarantee that encrypted personal data can be considered as anonymous data, and therefore processed outside the scope of the data protection regulations like the EU's GDPR 2 [2]. Three relevant factors must be considered when assessing the level of security of encrypted data: the strength of the encryption algorithm used, the length of the encryption key, and the security of encryption key management [10]. If an organization holds some third party's data (acting, in GDPR terms, as the data controller) in encrypted form but does not hold nor can access the decryption key in any way, it is reasonable to assume that it will not be able to access any personal information within the data [5].…”

“…For example, prefix distance can preserve country neighborhoods, which can be handy for grouping the bulk of botnet traffic 9. We could trivially increase the number of dimensions by segmenting the IP address into finer grains, which would result in a linear increase in size 10. Figure2computed between h 1 and h 1 , the avalanche effect of cryptographic hashing algorithm ensures that the hashed values of the same dimension are far enough from each other.…”

Community-based health care providers as research participant recruitment gatekeepers: ethical and legal issues in a real-world case example

“…The rise of digitalization and new mobile technologies such as medical apps and cloud-based electronic health records have increased data security risks (Compagnucci et al, 2019). One of the primary goals of the HIPAA Security Rule is to protect individual privacy, in particular while implementing new technologies that are intended to improve the quality and efficiency of patient care.…”

Noise Free Fully Homomorphic Encryption Scheme Over Non-Associative Algebra

“…T HE Fully Homomorphic Encryption (FHE) scheme was referred to as the "Holy Grail" of the cryptography [1]. They have the ability to perform encrypted data processing without prior decryption.…”