According to the Cisco SDSI v1.0 objectives, Artificial Intelligence and Machine Learning (ML) provide significant benefits in automating the identification of complex security weaknesses. One of the primary benefits is the ability of AI to performEncrypted Threat Analytics (ETA). AI models can analyze the metadata and initial handshake patterns of encrypted traffic—without needing to decrypt it—toidentify vulnerabilities associated with weak TLS algorithmsor outdated cipher suites.

By recognizing specific fingerprints in the TLS handshake, AI-driven tools can alert administrators to non-compliant encryption standards that might be susceptible to interception. While AI is a powerful force multiplier, it doesnot replacea comprehensive defense-in-depth strategy (Option B); rather, it enhances it. It does not directlyspeed up data transmission(Option A), as that is a function of hardware and bandwidth. Furthermore, while AI helps mitigate DDoS attacks, it rarely provides "complete" protection (Option C) on its own, as DDoS mitigation requires a multi-layered approach involving massive bandwidth and specialized scrubbing. The ability to identify cryptographic weaknesses at scale is a core functional benefit of AI in modern security infrastructure, aligning with the Cisco goal of maintaining a hardened and compliant network posture through automated visibility.