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During its GTC 2021 virtual keynote this morning, Nvidia announced Morpheus, a “cloud-native” app framework aimed at providing cybersecurity partners with AI skills that can be used to detect and mitigate cybersecurity attacks. Using machine learning, Morpheus identifies, captures, and acts on threats and anomalies, including leaks of sensitive data, phishing attempts, and malware.
Morpheus is available in preview from today, and developers can apply for early access on Nvidia’s landing page.
Reflecting the pace of adoption, the AI in cybersecurity market will reach $38.2 billion in value by 2026, Markets and Markets projects. That’s up from $8.8 billion in 2019, representing a compound annual growth rate of around 23.3%. Just last week, a study from MIT Technology Review Insights and Darktrace found that 96% of execs at large enterprises are considering adopting “defensive AI” against cyberattacks.
Morpheus essentially enables compute nodes in networks to serve as cyberdefense sensors — Nvidia says its newly announced BlueField-3 data processing units can be specifically configured for this purpose. With Morpheus, organizations can analyze packets without information replication, leveraging real-time telemetry and policy enforcement, as well as data processing at the edge. Thanks to AI, Morpheus can ostensibly analyze more security data than conventional cybersecurity app frameworks without sacrificing cost or performance.
Developers can create their own Morpheus skills using deep learning models, and Nvidia says “leading” hardware, software, and cybersecurity solutions providers are working to optimize and integrate datacenter security offerings with Morpheus, including Aria Cybersecurity Solutions, Cloudflare, F5, Fortinet, Guardicore Canonical, Red Hat, and VMware. Morpheus is also optimized to run on Nvidia-certified systems from Atos, Dell, Gigabyte, H3C, HPE, Inspur, Lenovo, QCT, and Supermicro.
Businesses are increasingly placing their faith in defensive AI like Morpheus to combat the growing number of cyberthreats. Known as an autonomous response, defensive AI can interrupt in-progress attacks without affecting day-to-day business. For example, given a strain of ransomware an enterprise hasn’t encountered in the past, defensive AI can identify the novel and abnormal patterns of behavior and stop the ransomware even if it isn’t associated with publicly known compromise indicators (e.g., blacklisted command-and-control domains or malware file hashes).
According to the above-mentioned MIT and Darktrace survey, 44% of executives are assessing AI-enabled security systems and 38% are deploying autonomous response technology. This agrees with findings from Statista. In a 2019 analysis, the firm reported that around 80% of executives in the telecommunications industry believe their organization wouldn’t be able to respond to cyberattacks without AI.
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