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AI-Driven Cybersecurity for Telemedicine
2
Zitationen
3
Autoren
2025
Jahr
Abstract
AI-driven solutions utilize machine learning, behavioral analysis, and autonomous defense systems to identify and mitigate risks more effectively than conventional methods. These systems continuously adapt to evolving threats, ensuring proactive and dynamic defense mechanisms. Additionally, integrating blockchain technology enhances data security through immutable records and secure transactions. Despite its benefits, AI-driven cybersecurity raises ethical and regulatory concerns, including data privacy issues, algorithmic bias, and adversarial AI attacks. Striking a balance between automation and human oversight is vital to uphold ethical standards and regulatory compliance. This chapter examines the role of AI-driven cybersecurity in telemedicine, exploring its capabilities, challenges, and future trends. By harnessing AI and blockchain, healthcare organizations can develop robust cybersecurity frameworks that safeguard patient data, ensure system reliability, and maintain trust in digital healthcare services.
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