Federated Learning for Secure Genomic Research: Privacy-Preserving AI Solutions for Precision Medicine | Chapter 3 | Science and Technology: Developments and Applications Vol. 9

The applications of AI technology in genomic research are increasing, and as centralized AI models need to be trained on aggregated raw genomic data, federated learning (FL), which is inherently a privacy-preserving AI approach, has evolved. Importantly, FL enables multiple institutions to jointly train machine learning models without transmitting raw genomic datasets out of the source institution. Nonetheless, it complies with the most intensive data protection laws, such as the GDPR, HIPAA, or PIPL. This paper recognizes FL in promoting the cybersecurity of genomic data and analyzes its potential for counteracting the non-compliance with individual genomic data privacy by first examining a fundamental optimization algorithm for fitting decentralized models, Federated Averaging. It also covers techniques for preserving privacy, such as Homomorphic Encryption and Differential Privacy. For one, HE is about performing encrypted computations on genomic data to mitigate the risk of adversarial inference attacks, while DP injects carefully designed noise into model updates to alleviate risks of data reconstruction and membership inference attacks. In addition, the paper comments on the ethical and regulatory aspects of genomic FL, such as data ownership, cybersecurity hazards of training on sensitive data, and the trustworthiness of the produced models. It also draws attention to critical future research areas: hybrid encryption methods, quantum-safe cryptographic protocols, and cross-compatibility standards to improve the effectiveness of FL over dissimilar genomic data. These developments represent the beginning of the potential for transforming genomic AI research while preserving privacy using FL.

 

Author (s) Details

 

Alex Mathew
Bethany College, USA.

 

Hannah Alex
University of Pittsburgh, USA.

 

Please see the book here:- https://doi.org/10.9734/bpi/stda/v9/5116

Surveillance Capitalism and Data Privacy in the Digital Age: Balancing Innovation with Regulatory Compliance | Chapter 4 | Business, Management and Economics: Research Progress Vol. 9

Advancements in technology have created the environment for companies to engage in systematic surveillance of individuals and exploit such data for profit without necessarily asking for the user’s permission. This paper therefore seeks to discuss the intricate correlation between surveillance capitalism and data privacy, and how well legislations like the GDPR and the CCPA have worked out. In a systematic literature review of academic works, the study analyses the ways through which surveillance capitalism is enacted, assesses the provided surveillance regulation strategies, and explores the possibilities of the tension between privacy and innovation. The results imply privacy’s prominence as well as the necessity for the implementation of privacy regulation at multiple levels based on the privacy-by-design concept, the use of such technologies as differential privacy, efficient enforcement measures for user privacy protection along the promotion of innovations. The paper concludes with policy recommendations that could improve international standards of data protection and ensure privacy as a right in the global economy.

 

Author (s) Details

Ogochukwu C. Nweke
School of Business, Leadership and Legal Studies (SBLL), Regent University College of Science and Technology, Accra, Ghana and Faculty of Law, Governance and International Relations, Kings University College (KUC), Accra, Ghana.

 

Bashiru Salifu Zibo
Ghana Police Service, Accra Regional Command, Faculty of Law, Governance and International Relations, Kings University College (KUC), Accra, Ghana and Centre for Distant and e-Learning, University of Education Winneba, Kasoa, Ghana.

 

Emmanuel Kweku Amoako Appiah
Customs Division, Ghana Revenue Authority, UNICAF University, Malawi.

 

Samuel Osekre
Regent University College of Science and Technology, Accra, Ghana.

 

Please see the book here:- https://doi.org/10.9734/bpi/bmerp/v9/2640