Analyzing network traffic patterns is the heart of a successful security strategy. As organizations continue to grow their digital landscapes, cyber threats have also progressed in complexity and now utilize sophisticated evasion techniques to evade detection. Conventional security countermeasures are no longer able to cope with such dynamic and persistent security threats, hence now organizations are relying on network traffic analysis to detect and mitigate any security incidents.
Network traffic patterns analysis can give us a proactive way to detect anomalies or potential threats before they reach out to cause harm. By monitoring data flows and real time network traffic, security teams can spot anomalous behavior, including unauthorized access, network data exfiltration, or malware communication. It informs things like what changes we need to make in our defense posture.
Here comes Fidelis Network®, an advanced solution that processes network traffic analysis to seamlessly advance threat detection capabilities. With its advanced detection capabilities, network traffic analysis capabilities, and contextual intelligence, Fidelis Network® enables organizations to effectively detect, respond to, and help mitigate threats—securing enterprise networks against the advanced cyber risks organizations are facing today.
What Are Network Traffic Patterns?
Network traffic patterns refer to the flow data and behavior of data as it travels across a network. They include details such as the volume, direction, and frequency of data packets exchanged between devices. While analyzing network traffic these patterns provide valuable insights into how networks are utilized and help detect deviations that could signal security incidents.
There are two types of network traffic patter – normal network traffic pattern & abnormal network traffic pattern. Understanding the difference between normal and abnormal traffic patterns is crucial for effective network traffic analysis.
| Aspect | Normal Traffic Patterns | Abnormal Traffic Patterns |
|---|---|---|
| Volume | Consistency in flow data during business hours. | Sudden spikes in data transfer (e.g., potential data exfiltration). |
| Direction | Typical internal communications between servers and endpoints. | Unusual outbound connections to unknown IPs or locations. |
| Frequency | Regular access to frequently used applications or services. | Excessive repeated requests to a single endpoint (e.g., DDoS attack). |
| Behavior | Devices communicating within expected time frames and protocols. | Communication with command-and-control servers or unknown devices. |
| Example | Employees accessing shared files on internal servers. | Large volumes of data being sent to an unknown external IP at midnight. |
Why Is Network Traffic Pattern Analysis Essential for Cybersecurity?
Anomaly Detection in Network traffic analysis (NTA) is very important to detect vulnerability of a system and monitor network traffic. The idea is that due to the baseline level of normal activity, anything outside that baseline can be a red flag that we should be concerned about. For example, anomalous network traffic data flows such as bulk file transfers outside posting hours might indicate unauthorized access or data exfiltration. The ability to quickly detect such abnormalities enables security teams to accelerate investigation and reduce potential risks.
Also, real time network traffic analysis performs an essential role in discovering lurking vulnerabilities that can be exploited by attackers. Malware can have anomalous patterns on network activity, involuntarily make outbound connections or perform irregular patterns of communication. Spotting these anomalies helps security center to intercept malicious activities before they could do substantial damage to systems or sensitive network data.
Examples of patterns indicative of threats include:
- Unusual data transfer: Movement of high volume of network traffic data outside of business operations hours could indicate a form of data exfiltration.
- Traffic spikes: Sudden increases in inbound or outbound traffic may indicate a Distributed Denial-of-Service (DDoS) attack or unusual internal activity.
Key Challenges Faced by Security Teams in Network Traffic Analysis
- Encrypted traffic: Malicious activities concealed within encrypted traffic is extremely tough to identify and evaluate.
- High data volume: The amount of network traffic volume in modern organizations could overwhelm teams and making it challenging to spot significant anomalies, hindering comprehensive network traffic analysis.
- Dynamic network environments: Networks evolve continuously and what is “normal” network traffic is subject to change on a regular basis making network traffic pattern analysis a hard task.
- False positives: False positives mean identifying a harmless activity as an attack as it’s tough to distinguish between legitimate traffic anomaly and malicious behavior.
- Complexity in identifying hidden security threats: Advanced attackers often disguise malicious traffic patterns, making it harder to identify and flag unusual activities, making malicious network traffic analysis challenging.
Techniques for Analyzing Network Traffic Patterns
There are five major techniques of network traffic analysis (NTA) that organization implement to detect and mitigate a breach attempt proactively.
Session Inspection:
Application session inspection focuses on analyzing the application-level data over a network session, including elements such as duration, involved endpoints, and communication patterns. Fidelis Network® delivers on this session inspection to gain deep clarity into every individual connection, and to identify anomalous or malicious behavior beyond what traditional techniques such as Deep Packet Inspection (DPI) can provide.
Behavioral Analysis Using Machine Learning:
With its capability of analyzing network traffic data, machine learning can examine network traffic in real-time by detecting traffic that no longer behaves according to the normal behavior pattern. Machine learning models can help analyze normal network operations and detect suspicious anomalies like data exfiltration or unauthorized access attempts that rules-based methods may not catch.
Signature-Based Analysis:
Signature-based analysis looks for known attack patterns, or malicious signatures, in the traffic. This technique uses predefined lists of threat signatures, enabling rapid detection of well-known exploits. Although it excels at detecting known threats, it has limitations regarding zero-day exploits or advanced persistent threats (APTs) that do not have any established signature.
Baselining and Network Traffic Anomaly Detection:
Normal network behavior is the baseline for good threat detection. As said, the traffic is compared against the historical network data to find the outliers, showing unusual patterns of activity within the organization which helps you to prevent the threats at the very beginning by taking smart actions like detecting and removing malware, insider threats, data exfiltration, data breaches, etc.
Leveraging Fidelis Network® for Advanced Network Traffic Analysis:
Fidelis Network® leverages a variety of techniques to analyze network traffic from session inspection, behavioral analysis, and real-time monitoring. With actionable insights and strong detection capabilities, SOC use this powerful platform to quickly identify, investigate, and accurately eliminate threats, making it a crucial asset for today’s network security.
Discover insights on:
- Current Cyber Threat Trends
- Key Security Strategies
- Next-Gen Network Defense
How Network Traffic Analysis Works (Step-by-Step)
Network traffic analysis involves ongoing monitoring, capturing, and analyzing network traffic data to detect threats, optimize network performance, and ensure network security. Here’s a step-by-step breakdown:
Thus, network traffic analysis is fostered through a systematic process instead of just isolating them, thus ensuring network security and reliability.
Best Practices for Network Traffic Pattern Analysis
Network Traffic Analysis plays a crucial role in proactive network management and cybersecurity. By examining the flow data through your network, you can uncover hidden threats, optimize network performance, and make data-driven decisions to strengthen your infrastructure.
Establish a Traffic Baseline
Analyze historic traffic data and define the normal network behavior. This baseline is used as a reference to detect anomalies. It is of utmost importance to have the baseline updated regularly based on the changes in the business, including addition of new applications, user behavior, and/or bandwidth usage.
Segment Your Network
Segment the network into smaller, isolated sub-networks to better monitor network traffic. Traffic segmentation helps in containing sensitive data and reduces the blast-radius of the breach. Tune detection mechanisms according to the environment — for example, separate user traffic from critical server traffic to detect unusual access attempts.
Leverage Advanced Analytics Tools
Implement modern network traffic analysis solutions such as Network Detection and Response (NDR) systems, or Endpoint Detection and Response (EDR) solutions to effectively analyze the data in real time. Other platforms, such as Fidelis Network®, employ machine learning and behavioral-based network traffic analysis to rapidly detect known and unknown threats while minimizing false positives.
Monitor Encrypted Traffic
A significant portion of modern network traffic is encrypted, which can obscure potential threats. Invest in solutions capable of decrypting and analyzing encrypted traffic to detect malicious activities hidden within legitimate communications.
Review and Update Threat Intelligence Regularly
Utilize current threat intelligence feeds to catch any new threat or tactic. Frequent updates keep your network traffic analysis effective at detecting both advanced persistent threats (APTs) or zero-day exploits using sophisticated techniques to avoid detection.
By implementing these practices, organizations can enhance their ability of network traffic analysis which will eventually lead to enhanced threat detection, minimizing risks, and maintain robust network security.
Fidelis Network®: Enhancing Threat Detection Through Network Traffic Analysis
Fidelis Network® is the industry’s best in class network traffic analysis tool, giving organizations the ability to enhance their network performance and overall cybersecurity posture by providing deep visibility into network traffic patterns and behaviors. It allows security centers to detect, investigate, and respond to threats in real-time due to its advanced detection and network traffic analysis capabilities.
Fidelis Network® ensures early threat detection, even for sophisticated and evasive cyberattacks. The platform integrates seamlessly with other security solutions to provide a holistic view of network activity, making it an essential tool for securing modern, complex networks.
Key Features and Capabilities of Fidelis Network®
- Deep Session Inspection: Analyzes full network sessions, ensuring a comprehensive understanding of all communications.
- Integration with Deception Technology: Enhances threat hunting by using decoys to reveal attacker techniques and paths.
- Inspection of Encrypted Traffic: Fidelis Network® is capable of network traffic analysis of encrypted website traffic without sacrificing data protection.
- Actionable Threat Intel: Frequently updates threat signatures and provides context to alerts for better-faster decision-making and improved network performance.
- Extensive Coverage: Spans East-West and North-South network traffic in on-premises, cloud and hybrid environments.
Threat Protection offered by Fidelis Network® Detection and Response:
- Data Theft
- Lateral Movement in Network
- Malware Threat
