This week at HP Protect in Washington, D.C., attendees will be able to learn about how HP is using Lancope’s StealthWatch System to improve network visibility and security. During a session entitled, “Bigger data means bigger security,” an expert from HP will discuss technologies such as StealthWatch that enable enterprises to access and analyze massive amounts of network data to create actionable security intelligence. The session will take place on Wednesday, September 18 at 1:30 p.m. U.S. Eastern time. Lancope is also exhibiting the StealthWatch System at HP Protect, which runs until Sept. 19.
HP relies on StealthWatch, along with its own HP Vertica solution, to quickly detect anomalous activity across its enormously complex, global network. With the combined solution, HP leverages network flow data to obtain in-depth information that enables its security teams to act more quickly and minimize potential damage.
Today’s data deluge is making it difficult for security professionals to pinpoint malicious traffic amidst the sea of network information generated around the clock. HP’s network, for example, contains roughly 16,000 switches and 10,000 routers, serving approximately 300,000 users at 600 sites and countless remote locations around the world, generating 150,000 flows per second of data. Lancope’s StealthWatch helps HP make sense of all of this data to detect issues such as malware, network misuse and DDoS attempts.
Since it collects information from existing infrastructure, StealthWatch cost-effectively scales to meet the needs of even the largest organizations. According to HP network security architect Jim O’Shea, “With Lancope we don’t need extra hardware to get a comprehensive, scalable view of network activity.” He added, “Network-based anomaly detection is a critical component of any enterprise cyber security framework…Lancope has proven to be a very effective addition to our cyber security arsenal.”
Click here for the full Lancope/HP case study.
TAGS netflow, network security, stealthwatch, lancope, anomaly detection, network visibility, malware, ddos, security intelligence, hp, big data