Present Traffic Analysis is Hardware-Heavy<\/strong><\/h3>\nToday, monitoring network traffic requires a lot of hardware as network speeds and volume continue to increase. What makes it even more challenging is to scale across the many delivery platforms and locations used by any enterprise.\u00a0 With the sophistication and frequency of attacks increasing, organizations need to get better visibility into all traffic, not just at select points in the network.\u00a0 With attackers exploring networks for months before the actual attack happens, visibility into the internal network activities is becoming increasingly important. This is not just for detection but also for determining the impacted resources (some call this \u201cblast radius\u201d<\/em>) and swift incident response.<\/p>\nGiven the various analysis goals across network and security operations, most organizations are challenged with many self-contained solutions, each one capturing and analyzing the same traffic on their own proprietary hardware for different analysis purposes. This model generates narrow “stovepipe” solutions with the need to duplicate the traffic to multiple analysis applications, limiting interoperability and the exchange of vital data. In addition to prohibiting effective interaction between network and security operations, it also further increases the need for even more hardware to process and store the growing amount of traffic. These systems often use custom NIC cards to record and analyze information.\u00a0 They also have custom analysis engines running on FPGAs or on several CPUs at once to keep up with the analysis of the incoming traffic in real-time, store the findings, and then ignore and discard the original traffic.<\/p>\n
This is one of the reasons why many organizations have implemented monitoring logs, alarms, and flow data generated by network elements and endpoint devices, to reduce the need for traffic analysis. As this resulting metadata is creating less volume than actual network traffic, these observations are based upon applications like SIEMs and SOARs, and can be more easily virtualized. The primary drawback with relying on metadata is that it only provides indicators of attacks or emerging issues, but can\u2019t determine the event’s severity. This requires a view into the network traffic, which is rarely, if ever, available.<\/p>\n
How network and security operations can build a scalable and economical system to decrypt and analyze growing network traffic has long been a topic of discussion.\u00a0 Infrastructure for servers and storage has successfully and effectively virtualized all computing and storage components for many years.\u00a0 Even in networking, a trend to virtualize switches, routers, and firewalls has been taking hold over the last several years.\u00a0 But the technique of virtualizing traffic monitoring and analysis is still in its infancy.\u00a0 This makes actual traffic monitoring solutions concentrate on key aggregation locations, such as network ingress-egress points, often in the form of IDS or IPS systems, or Network Detection and Response solutions. \u00a0Due to the cost and complexity of those systems, internal core networks or other internal high-value content infrastructure is often left unmonitored.\u00a0 Visibility in those areas is often left to metadata supplied by network or end-point devices, resulting in more abstracted information and flow data, which adds to more data with less insight.<\/p>\n
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