Sourcefire, Inc. (Nasdaq: FIRE), a leader in intelligent cybersecurity solutions, today announced that Immunet®, the company's advanced anti-malware solution, has surpassed 2 million installed endpoints. Immunet achieved this milestone due to its “big data” approach to endpoint security, which allows it to provide an additional layer of protection not afforded by traditional anti-malware technologies.
"The rapid adoption witnessed with Immunet demonstrates that users are seeking both an added layer of protection to bolster their defenses, and a more intelligent approach to block advanced threats," said Oliver Friedrichs, Senior Vice President of Sourcefire's Cloud Technology Group. "This intelligence comes from designing a product with a big data mindset, which is an absolute requirement in today's threat landscape. Traditional anti-malware solutions simply cannot achieve the protection and control that customers require."
The explosion and advancement of threats each day has allowed them to bypass traditional solutions. For example, threats today are transitory with at least 75 percent being seen on only a single endpoint. Threat lifetimes can be measured in hours that require a centralized “ big data” repository that can be monitored, observed, culled and used to make intelligent security decisions for all of Immunet’s users. A data-driven approach also enables Immunet to gather real-world metrics on how technologies perform in the field. Immunet was built on the principle of Collective Immunity™, which is shared protective resistance gained through community and collective intelligence to fight against computer malware infection.
"The data deluge is having an impact on the changing nature of security management. Not only has there been an explosion in the sheer volume of data requiring protection, but there has also been a dramatic growth in threats as well as disclosed vulnerabilities," said Scott Crawford, research director, Enterprise Management Associates. "The centralized data approach enables the capability to collect and act on large data sets with great speed, accuracy and efficacy."
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