Why We Need a New Approach for Network Security

Network analysis provides an unparalleled advantage for enterprise security and operations. As network, application, and security expertise continue to diverge with the acceleration of technology, critical advancements in network monitoring are analogous to the development of better telescopes in astronomy – and allow us to see further and more clearly. However, the approach to analyzing the network has traditionally offered a challenging choice between packet recording and metadata flow records. The cost of each approach varies from the simple capture, to complex optimization of storage, to detailed analysis before or after query time. Most use cases benefit from longer retention history, but the relative cost of that retention varies dramatically between the approaches. The availability of historical data leads to the discovery of additional use cases, providing even higher ROI. Even more nuanced is the cost of the specific expertise required to utilize each approach effectively. Historically, organizations had to choose between approaches, but now there is a breakthrough that allows companies to take advantage of a complete solution that surpasses both legacy approaches providing deep benefits to the company’s security strategy.

Packet Recording

Packet Recording is the oldest form of data capture for network monitoring. Engineers and scientists used the packet recording and playback to develop and optimize the networking stack directly. A primary benefit is the zero-touch aspect to ensure that the observation of the packets does not impact the network infrastructure in any form including basic resource utilization. While the technique is often applied across the application stack, the rapidly evolving applications and network capacity is increasing the complexity cost to capture, store, recall, and analyze the traffic. The primary cost factor is the storage resources and capacity to record enough network traffic to provide relevant history. However, the additional cost is the recall and queries that requires expertise to reconstruct network activity to provide insight.

Packet Recording

Flow Records or metadata extraction was introduced as a simplified version of network analysis to provide visibility into connectivity, bandwidth, and other key performance indicators. The forms of metadata records evolved to encompass more metrics, but the primary approach utilizes the network elements to generate a simplified record often referred to as a tuple (sFlow, NetFlow, IPFIX). The primary tradeoff of this approach is the loss of granularity due to the summarization of the observed traffic at common network layers and visibility to application specific details. While the overall resource cost for flow records is not high, metadata generation is always a lower priority than network routing and is impacted during heavy load.

Flow Records

A Balanced Approach

WireX Systems Contextual Capture™ incorporates aspects of both deep packet analysis and metadata extraction to provide a more balanced approach to the complexity cost. This approach significantly improves overall performance through expanded historical capacity and more directly accessible insight. Passively monitoring packets ensures the zero-touch philosophy prevents any additional resource demands on the network elements to generate metadata. Additionally, this enhances security by providing an isolated second factor evaluation and record of application, endpoint, and user activity. Contextual Capture™ processes all packets in real-time through protocol specific analyzers to produce contextual records that are then indexed and archived for rapid historical queries of up to one year. The detailed summary of application-level context is indexed during storage to enable efficient, relevant answers to queries posed. WireX Systems Contextual Capture™ enhances a variety of use cases by supporting both less experienced staff and accelerating the work of top-level analysts.

Packet Recording Flow Records WireX Systems Contextual Capture ™
Granularity of Data Good

Detailed packet-level data

Bad

Summarized traffic data

Good

Rich Contextual information from payload

Storage Requirements Bad

Requires substantial storage space

Good

Less storage than packet recording

Good

Optimized through indexing and compression

Real-time Analysis Capability Bad

Mostly used for retrospective analysis

Moderate

Suitable for some real-time applications

Good

Designed for real-time and historical analysis

Ease of Use for
Non-Experts
Bad

Requires significant expertise to interpret

Moderate

Easier than packet recording but requires network expertise

Good

Accessible to a wide range of users

Impact on Network Performance Good

Depending on whether taps or span-ports are utilized

Bad

Collect and transmit flow records.

Good

Depending on whether taps or span-ports are utilized

Historical Data Access Bad

Limited to hours or days of storage

Moderate

Much longer history but fewer answers due to limited detail.

Good

Vastly longer history (Months) with application context to drive decisions.

Information Density Bad

Significant detail, but massive volume.

Bad

Significant history but lacking detail due to summarization

Good

Proper balance of application detail and historical significance.

 

As indicated in the comparison table, the advantages of WireX Systems Contextual Capture™ provide the best balance between cost and needs. Unlocking the value of network data through historical data enables more rapid incident response. The quality and speed of response is limited to the quality of available data. The accessibility of the contextual records enables a broad array of secondary use cases and provides significant value through direct network observation.

It is important to understand the complete picture of capabilities when selecting network instrumentation. WireX Systems Contextual Capture ™ provides complete accessible insights from direct network observation providing organizations unmatched visibility.

Contact us today for a Complete Assessment.

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