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Network Analytics: From Detection to Active Prevention


April 6, 2021
Last Updated: November 5, 2024
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Network analytics involves collecting, monitoring, and analyzing network traffic. The insights gained from network analyses can help you identify threats on a network and mitigate them, optimize performance and capacity planning, and monitor cloud resources. 

To perform network analysis, organizations deploy network analytics software. These tools enable you to perform real-time visibility of traffic flow, automate analysis, and discover accurate forecasting. Backed by network analytics, organizations can stop assuming and start implementing data-driven advanced threat protection

What Is Network Analytics?

Network analytics applies big data practices to ensuring the security and management of networks. Analytics provide insight into network performance and use. Network analysis can be applied to help IT teams optimize performance, increase security, troubleshoot issues, predict use, and audit functionality. 

Leveraging network analytics requires organizations to build infrastructures that capture performance data at all levels. This includes port bit rates, packet drop rates, latency, and effects created by network policies. Organizations need to be able to collect, store, and analyze this data efficiently and in real-time for the greatest impact.

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Top Network Analytics Use Cases

Top Network Analytics Use Cases

There are multiple reasons why organizations choose to use network analytics, including the following use cases.

Improving security

The use of compromised credentials is often difficult to identify. This is because attackers “legitimately” bypass security measures, such as privilege restrictions and authentication. Network analytics can help you identify these situations by comparing user behavior to expected patterns. When patterns differ, you can investigate, potentially identifying credential abuse or malicious insiders. 

Network analytics can also be used to track the progress of incidents. Teams can use analytics to trace an attacker’s path, identifying what resources they accessed, when, and how. This information can be used to catch attackers still at large and to identify system vulnerabilities that need to be corrected. 

Performance optimization and capacity planning

Network analytics can increase the visibility of network performance issues and provide a clearer understanding of capacity. With analytics, teams can uncover network design issues and hidden bottlenecks that block or limit performance. Analytics can also be used to ensure that performance stays at an expected level, highlighting when it drops. 

By looking at past performance, organizations can use analytics to anticipate how networks will behave under certain conditions. This enables teams to plan for changing traffic patterns and amounts. It also simplifies upgrading since you can reliably predict how upgrades may affect capabilities.

Cloud network monitoring

Network analytics can be useful for monitoring the value and availability of cloud resources. Just as with on-premises networks, you can use analytics to monitor and evaluate cloud performance. This includes both internal and external use. For example, monitoring how and when third-parties access your resources or cloud-hosted services. 

Tips From the Expert

In my experience, here are tips that can help you better adapt to network analytics for security:

  1. Real-time Anomaly Scoring: Leveraging machine learning models to continuously score traffic anomalies ensures that threats are prioritized and addressed promptly.
  2. Automated Incident Playbooks: Integrating analytics with automated response playbooks streamlines the incident response process, saving time and reducing the impact of attacks.
  3. Correlate across Data Sources: Combining data from various sources (e.g., endpoints, applications) provides a more comprehensive view of network activity and helps identify potential threats.
  4. Active Threat Intelligence: Incorporating real-time threat intelligence allows for proactive detection of attackers using known techniques.
  5. Baseline Network Behavior: Establishing baselines for normal traffic patterns is essential for identifying deviations that may indicate a security breach.

Eyal Gruner is the Co-Founder and CEO of Cynet. He is also Co-Founder and former CEO of BugSec, Israel’s leading cyber consultancy, and Versafe, acquired by F5 Networks. Gruner began his career at age 15 by hacking into his bank’s ATM to show the weakness of their security and has been recognized in Google’s security Hall of Fame.

What Is Network Analytics Software?

You can use a host of tools to monitor and log network traffic, including Simple Network Management Protocol (SNMP), syslog, or Cisco NetFlow. However, using these tools often requires custom integrations and complicates workflows by requiring multiple dashboards and management consoles.

Network analytics software can combine the functionality of the various network tools you are currently using. This makes management and analysis simpler and helps ensure standardized practices and policies. Additionally, network analytics tools aggregate data for you and typically include AI, which is applied to real-time analysis. 

Benefits of network analytics software

Implementing unified tooling can provide several significant benefits to your IT teams:

  • Real-time visibility of traffic flow—can provide information on flows across specific portions of your network or the whole network. From a single dashboard you can monitor individual devices, resources, and network connections. This is particularly useful for cloud and hybrid cloud deployments, which can provide limited visibility due to the complexity of network connections. 
  • Automated analysis—the amount of network data that is generated by many organizations is more that many IT teams can manage. This causes issues to be overlooked and can make troubleshooting difficult. The inclusion of AI enables teams to evaluate all data across networks, providing better correlation between events and more context for any issues that arise. Additionally, since analytics are automated, teams can spend more time improving performance and less interpreting data. 
  • Accurate forecasting—comprehensive analyses enable teams to more accurately predict future resource requirements and to better anticipate the effect of changes. Additionally, because analysis is automated, more scenarios can be evaluated, enabling teams to plan more thoroughly.

Considerations for Selecting Network Analytics Software

When selecting network analytics software, you should keep in mind the composition of your network and the amount of visibility required. Be mindful of changes that you may need to make in the near future and try to select a tool that provides flexibility and scalability. 

You should also consider how you want to host your software. If you are working in a highly regulated industry with only on-premises resources, it doesn’t make sense to choose a cloud-based service. However, if you are operating in the cloud, especially if you have a small team, outsourcing network analytics to a cloud service provider may be ideal for you. 

Cloud-based services, whether managed or not, can help you reduce bandwidth use internally and can better accommodate distributed networks. These services can also potentially provide greater support and lower operating costs than what is available on-premises. 

With a cloud service, you aren’t responsible for managing host hardware or keeping software up-to-date. All of this is managed for you. The downside of this is that you do not have full control over your network data and must account for any security risks created by granting network access to your vendor. 

Network Analytics for Security: The Importance of Dedicated Network Security Solutions

Network analytics has an important impact on security, as many cyber attacks are conducted through the network. While general-purpose network analytics tools can help identify security issues, there are strong advantages to using specialized solutions for network security monitoring. Specialized network security tools can help you:

    • Identify attack patterns – maintaining a database of known attacks and alerting when network traffic exhibits one of these known patterns.
    • Identify and score anomalies – leverage machine learning and behavioral analytics to identify ports, network segments, or entities on the network that are not behaving as usual, and prioritizing these anomalies to identify potential security incidents.
  • Identify attackers – leverage a threat intelligence database that has information about known attackers. When a certain IP connects to your network, network security tools can identify it belongs to a known attacker group, and help you defend against their tactics, techniques and procedures (TTP).

Stop advanced cyber
threats with one solution

Cynet’s All-In-One Security Platform

  • Full-Featured EDR and NGAV
  • Anti-Ransomware & Threat Hunting
  • 24/7 Managed Detection and Response

Achieved 100% detection in 2023

review stars

Rated 4.8/5

review stars

2024 Leader

Network Analytics With Cynet 360

Advanced attackers target your blindspots. To protect yourself against advanced attacks you need to move from detection to active prevention. 

Cynet Network Analytics continuously monitors network traffic to detect and block otherwise invisible malicious activity. Unlike common network analytics tools that provide only threat detection, Cynet enables you to choose between detection mode and proactive prevention.

Cynet Network Analytics protection spans the wide range of advanced attacks stages, utilizing network visibility, behavioral analysis, deterministic modules and threat intelligence. You can enable Cynet built-in preventions or tailor a customized flow utilizing host isolation, traffic block and user disable.

Learn more about Cynet Network Analytics.

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