Extreme Networks (Nasdaq: EXTR) has launched its ExtremeAI Security application, a network security solution that leverages artificial intelligence and machine learning to identify and remediate advanced threats against IoT devices.
The convergence of multi-cloud, mobility, and the massive influx of IoT devices in the enterprise expands the attack surface, making it an imperative to deploy advanced security technologies deep inside the network and not just at the perimeter, stated Extreme Networks. This explosion of endpoints and network traffic would create complexity and make it difficult for network administrators and security teams to gain visibility into the “chaos” through traditional solutions.
With IoT devices ranging from million-dollar smart MRI machines to five-dollar sensors, device-level security alone can’t be trusted to secure endpoints, added Extreme Networks. As a result, enterprise security teams would be working overtime to keep up, but often be shorthanded due to a lack of trained cybersecurity personnel.
Real-time Monitoring IoT Devices
ExtremeAI Security delivers deep visibility and detection of malicious traffic, and real-time monitoring of IoT devices for behavioral anomalies, “illuminating enterprise networks so attackers have nowhere to hide.”
Through fully-automated remediation of suspicious devices and traffic, ExtremeAI Security would ensure threats are contained without manual intervention, preventing them from moving across the network.
Extreme’s traffic analytics and visibility capabilities are embedded in this new security solution, combining enterprise networking with innovations in machine learning to identify and remediate threats.
ExtremeAI Security will be generally available in October 2019.
Key features of ExtremeAI Security would include:
- Behavioral monitoring and baselining – Massively scalable behavioral anomaly detection leverages machine learning to understand typical behavior of IoT devices and automatically trigger alerts when endpoints act in unusual or unexpected ways.
- Unsupervised learning – A zero-touch, zero-configuration approach would make ExtremeAI Security easy to implement. The advanced machine learning algorithm automatically responds when triggered and mitigates threats. This innovation is based on advancements in the field of Natural Language Processing.
- Insights and granular analytics – By leveraging its ExtremeAnalytics application – Extreme Networks’ flagship, end-to-end, analytics application – users can get deep visibility into the lateral movement of malicious traffic and any impact on crucial network services. Through the analytics platform, they can view threats by severity, category, high-risk endpoints and geography.
- Multi-vendor interoperability and integration – ExtremeAI Security works with all leading threat intelligence feeds, and close integration with Extreme Workflow Composer enables automatic threat mitigation and remediation. The automated ticketing feature integrates with variety of popular IT tools like Slack, Jira, and ServiceNow, and the solution as a whole interoperates with many popular security tools, including existing network taps. This extra layer of security would be necessary in today’s changing enterprise IT environment.
“Security is top of mind for all of our customers,” said Abby Strong, Vice President of Product Marketing, Extreme Networks. “They have seen the devastating impact of data breaches across industries and understand that they need to change the way they view security infrastructure. The ability to stop cyberattacks from moving across networks is an absolute necessity to prevent the types of data breaches that can dramatically harm a business. Extreme’s advancements in both security and machine learning will bring added peace of mind and a much-needed extra layer of security for our customers.”
Founded in 1996, Extreme Networks is headquartered in San Jose, California. The company has around 30,000 customers globally, including half of the Fortune 50 and some of the world’s leading names in business, hospitality, retail, transportation and logistics, education, government, healthcare and manufacturing.