Safeguarding Networks and Applications under the EU AI Act


To address the rapid advancement of AI technologies, the European Union has introduced the EU AI Act. This regulatory framework aims to protect individuals’ rights, safety, and democratic values while fostering AI innovation. The Act classifies AI systems into four risk levels—unacceptable, high, limited, and minimal—each with distinct regulatory requirements based on the potential harm the system may cause.

Risk Categories Explained:

  1. Unacceptable Risk: AI applications in this category pose significant threats to individual rights and democratic processes and are therefore banned. Examples include government social scoring, real-time biometric identification, and AI systems that exploit vulnerable groups.
  2. High Risk: These systems impact areas such as healthcare, education, and law enforcement and require stringent controls. Organizations using high-risk AI must comply with risk assessment protocols, data quality standards, transparency, and human oversight.
  3. Limited Risk: Moderate-risk AI systems, such as chatbots and recommendation engines, must meet transparency requirements to inform users they are interacting with AI.
  4. Minimal Risk: These applications, including spam filters and video games, are considered safe and have no specific regulatory obligations.

Security and Compliance Tools for High-Risk AI

For high-risk applications, security is paramount, aligning with requirements for data protection, availability, and transparency. Here’s how specific security measures can help comply with the EU AI Act, as well as related frameworks like NIS2 (Network and Information Security) and DORA (Digital Operational Resilience Act).

  • Web Application Firewalls (WAFs): These firewalls filter internet traffic to protect sensitive data and prevent unauthorized access. They support transparency and data protection by maintaining audit trails, ensuring organizations can demonstrate compliance during inspections.
  • DDoS Protection: DDoS (Distributed Denial of Service) defenses are critical for sustaining service availability. By mitigating high-traffic attacks, these tools help prevent disruptions in essential services, a requirement under both the EU AI Act and the NIS2 directive.
  • Bot Protection: Malicious bots threaten security by scraping data, causing denial of service, and infiltrating systems. Advanced bot protection identifies and blocks harmful bot activity, maintaining system integrity and preventing unauthorized access.
  • Load Balancers and Application Delivery Controllers (ADCs): By distributing traffic across servers, load balancers help maintain reliability and scalability, essential for high-risk applications that must remain robust and resilient to meet EU AI Act standards.

Achieving Continuous Compliance with Managed Services

Organizations can also leverage managed services to stay compliant with the EU AI Act, NIS2, and DORA by accessing around-the-clock support, threat monitoring, and incident response that yjey may lack in-house. Managed service providers bring specialized expertise, including maintaining compliance documentation, providing audit support, and ensuring systems are secure against evolving threats.

Conclusion

Through structured risk categorization and the encouragement of robust security tools, the EU AI Act, NIS2, and DORA create a compliance landscape that helps organizations protect networks, ensure privacy, and maintain service continuity. For companies navigating these regulations, employing advanced cybersecurity tools and managed services is crucial in aligning AI-driven applications with EU standards, ultimately fostering a safer digital environment in the EU.

Prakash Sinha

Prakash Sinha

Prakash Sinha is a technology executive and evangelist for Radware and brings over 29 years of experience in strategy, product management, product marketing and engineering. Prakash has been a part of executive teams of four software and network infrastructure startups, all of which were acquired. Before Radware, Prakash led product management for Citrix NetScaler and was instrumental in introducing multi-tenant and virtualized NetScaler product lines to market. Prior to Citrix, Prakash held leadership positions in architecture, engineering, and product management at leading technology companies such as Cisco, Informatica, and Tandem Computers. Prakash holds a Bachelor in Electrical Engineering from BIT, Mesra and an MBA from Haas School of Business at UC Berkeley.

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