Profit protection 2.0: The future of large language models (LLMS) in data security
Fujitsu North America Inc, Senior Solutions Architect (For Emerging Solutions), United States of America.
Research Article
World Journal of Advanced Research and Reviews, 2024, 21(03), 2667-2678
Publication history:
Received on 10 February 2024; revised on 18 March 2024; accepted on 21 March 2024
Abstract:
In cybersecurity, large language models are a two-edged sword: they stand to offer opportunities in data protection, threats mitigation, and privacy preservation; and threats on the same in data protection, threats mitigation, and privacy preservation. The present paper discusses how large language models are changing roles in cybersecurity and innovative security concepts such as Profit Protection 2.0, AI-based encryption, and automated threat response. It goes on to discuss how large language models have been integrated into the security technologies that already exist and how the emergent technologies-such as blockchain, federated learning, and decentralized AI-considerably empower data security. It highlights the possible risks large language models pose, such as privacy and vulnerability to adversarial attacks. In anticipation of advancements in AI-powered cybersecurity, this research singles out predictive security, adaptive defense systems, and regulation for companies as well as policymakers. The paper picks up from insights in the latest literature to make recommendations for practical measures of safeguarding these systems and also for their ethical implementation. The findings enrich the debate around AI security with proposals for organizations to adopt measures of shielding sensitive data while welcoming LLMs into the innovation of cybersecurity.
Keywords:
Large Language Models (Llms); Cybersecurity; AI-Driven Security; Data Privacy; Threat Mitigation; Profit Protection 2.0; AI Encryption; Automated Threat Response
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0