The swift rise of artificial intelligence technologies is significantly altering enterprise networking in unexpected ways. A new white paper from VeloCloud, a division of Broadcom, titled VeloRAIN: Next-Gen Security for AI-Driven Networks, explores these changes. Companies utilizing AI applications are finding that traditional network designs, which were mainly crafted for client-server web traffic, struggle to meet the distinctive requirements posed by AI workloads. This challenge goes beyond just network performance; it necessitates a rethinking of how networks are structured and safeguarded.
The Evolving Networking Landscape of Generative AI
Generative AI applications challenge standard networking paradigms. Unlike conventional web traffic that primarily flows down to users, AI tasks generate equivalent upload and download volumes, resulting in symmetrical traffic patterns. These applications are highly latency-sensitive, as even slight delays can hinder distributed AI processing and yield unreliable outcomes. Coupled with unpredictable and bursty traffic nature, organizations must reconsider their network frameworks to effectively support AI demands.
New Security Concerns
The security implications that arise are equally significant. As AI tools become widely adopted, they create new vulnerabilities and attack vectors that existing security frameworks fail to adequately address. Organizations now face challenges such as adversarial attacks on AI models, data poisoning risks, and the rise of shadow AI, which involves unauthorized use of AI tools that could compromise sensitive company data. Traditional security measures that heavily depend on signature-based detection are ill-equipped to address these emerging threats.
VeloCloud’s Security Solutions
To tackle these intricate demands, VeloCloud has developed a suite of solutions centered on the innovative VeloRAIN architecture. VeloRAIN, which stands for VeloCloud Robust Artificial Intelligence Networking, redefines how enterprise networks should function in the age of AI.
At the core is VeloCloud SD-WAN, which offers robust security through multiple protective layers. This solution incorporates strong encryption across all network components, enables advanced traffic segmentation for isolating various traffic types, and includes enhanced inspection capabilities via its Firewall Service. These elements work together to safeguard AI workloads while ensuring necessary performance is maintained.
In addition to VeloCloud SD-WAN features, the cloud-based Symantec SSE for VeloCloud addresses the specific security challenges associated with distributed AI applications. Notable features include: malware detection powered by machine learning to block new threats, high-speed decryption of SSL/TLS traffic to reveal hidden threats, inline cloud access security broker (CASB) capabilities to mitigate shadow AI risks, and AI-driven data loss prevention (DLP) solutions for enhanced data security.
Balancing Security and Efficient Management
The benefits of this integrated approach are significant for businesses. Organizations not only enhance their defenses against emerging threats but also experience improved performance for AI workloads through smart traffic management. Centralized oversight across security measures simplifies operations, while the architecture’s built-in flexibility guarantees adaptability to future threats.
As AI continues to transform the enterprise technology environment, businesses require partners who comprehend the opportunities and challenges this change presents. VeloCloud’s comprehensive security solutions underscore a commitment to aiding clients in securely navigating this evolving landscape. By merging advanced threat defense, intelligent network optimization, and zero-trust strategies, VeloCloud empowers organizations to leverage AI innovation without compromising on security or performance.
For more insights on how VeloCloud solutions secure AI-driven network infrastructure, read the complete white paper.
