Ensuring data security and compliance in AI-powered business applications
Independent researcher Sheffield Hallam University.
Research Article
Global Journal of Engineering and Technology Advances, 2023, 15(01), 125-142.
Article DOI: 10.30574/gjeta.2023.15.1.0067
Publication history:
Received on 26 February 2023; revised on 10 April 2023; accepted on 13 April 2023
Abstract:
Artificial intelligence technologies revolutionized how firms make judgments while transforming both data automation and processing throughout company operations. The fast commercial adoption of artificial intelligence technology produced new demanding hurdles for data security coupled with regulatory compliance issues. The vast processing of secret data by AI systems makes them into key targets that cyber attackers and auditors both seek to access. Businesses must supply secure defenses for AI integration operations combined with full compliance standards because operational efficiency requirements exist.
Safeguarding AI is attainable through modern systems which combine threat identification with aberrant pattern detecting speeds at high speed. AI systems produce well-protected cyber services by using predictive analytics with behavioral analysis coupled with automated threat intelligence which constructs defensive networks for system protection from attacks. The advancement of encrypted technology provided two key tools dubbed homomorphic encryption coupled with differential privacy to safeguard AI-generated data during operational maintenance. The implemented cryptographic infrastructure helps enterprises to defend operational functions through dual-purpose protection of data dependability and privacy.
Organizations must build AI-law and data-security regulation framework understanding regardless of regulatory changes. Business operations must create data protection standards that integrate GDPR compliance alongside relevant privacy requirements from specific business sectors at worldwide and regional levels. Organizations accomplish suitable legal and ethical standard alignment with AI applications through three fundamental techniques that link automated systems for compliance with security models which include AI-powered governance and accountability features.
AI security coupled with compliance needs enterprises to use an integrated solution that integrates AI security tools with proven cybersecurity methods. A comprehensive security plan must integrate safe cloud configurations with improved endpoint defenses coupled with regular risk checks. AI security and compliance enhancement demands all parties concerned to collaborate together between AI developers and cybersecurity professionals and regulatory agencies.
Businesses need to establish technical-progress equilibrium with tight security measures when preserving data security and compliance standards in their AI-based software solutions. The protection of sensitive company data in addition to cyber risk reduction and building of trust in AI operations becomes possible through security frameworks employing AI as well as cryptographic techniques and regulatory compliance maintenance. Organization success in digital resilience depends on their capacity to forecast security threats and compliance concerns which result from advancing AI technologies.
Keywords:
AI Security; Data Protection; Compliance; AI-Powered Business Applications; Cybersecurity; Threat Detection; Regulatory Frameworks
Full text article in PDF:
Copyright information:
Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0