Network traffic analysis (NTA) monitors traffic flowing over the network and can tip off an organization of a potential cyberattack on the network infrastructure.
Network traffic analysis is the process of capturing, inspecting, and analyzing network data packets to gain insights into the behavior, performance, and security of a computer network. It involves examining the patterns, protocols, and volume of data flowing through a network to understand how devices and systems communicate with each other.
The process allows network administrators, security professionals, and analysts to monitor network performance, detect network security threats, troubleshoot network issues, understand network usage, and gather information for compliance and auditing. This article focuses on the use of NTA in cybersecurity.
As organizations evolve their infrastructure based on digital transformation efforts, networks are increasingly becoming more complex and operating in hybrid multi-cloud environments. This has led to a larger threat landscape with more security gaps. Threat actors can more easily perform reconnaissance, lateral movement, communicate with external systems, and deliver malicious payloads or exfiltrate data. Log data, endpoint solutions, and other telemetry are not suited to exposing these kinds of attack patterns or abnormal activity that are part of an overall active attack campaign.
Network traffic analysis solutions serve as a proactive defense mechanism, enabling organizations to identify, respond to, and mitigate cyber threats effectively. By continuously monitoring and analyzing network traffic, companies can spot unusual or suspicious patterns that indicate potential security incidents. For example, quickly identifying traffic going to a known external malicious domain gives administrators the opportunity to break that connection and prevent the download of malware.
NTA also provides visibility into unknown and undetected network threats based on risky abnormal behavior. This gives organizations the opportunity to strengthen their cybersecurity posture and protect their critical assets from various attacks.
The goal of analyzing and monitoring network traffic for cyber threats is to enhance an organization’s cybersecurity defenses. This is done by having another layer of threat detection; getting an early warning of threats before they can cause damage; getting valuable insights to assist with incident response; gathering evidence for attack attribution; and identifying vulnerabilities and weaknesses in the network infrastructure.
Network traffic analysis involves monitoring and examining the data flowing through a computer network to gain insights into its behavior, performance, and security. It typically follows these general steps:
There are numerous security-oriented use cases for network traffic analysis.
Network traffic analysis plays a crucial role in enhancing security by providing valuable insights into the network activities and detecting potential security threats. Overall, NTA enables proactive monitoring, threat detection, and incident response, helping organizations identify and mitigate security risks in a timely manner. It provides valuable insights into network behavior, assists in detecting and responding to security incidents, and strengthens the overall security posture of the network infrastructure.
Network traffic analysis delivers numerous benefits, including improved network performance, efficient troubleshooting, effective capacity planning, enhanced security, policy enforcement, forensic analysis capabilities, and comprehensive network visibility. These advantages contribute to better network management, optimized operations, and a strengthened security posture for organizations. The benefits specific to security include:
Network traffic analysis plays a crucial role in identifying security threats and potential breaches. By monitoring and analyzing network traffic, organizations can detect suspicious activities, malware infections, intrusion attempts, and unauthorized access attempts. It helps in mitigating security risks, preventing data breaches, and proactively responding to security incidents.
NTA assists in enforcing security policies, regulatory compliance, and acceptable use policies within an organization. It helps in identifying policy violations, detecting unauthorized access or data transfers, and ensuring adherence to security standards and regulations. It supports organizations in maintaining compliance with industry-specific requirements such as PCI DSS or HIPAA.
NTA provides valuable data for forensic investigations and incident response. By analyzing captured packets and network logs, security teams can reconstruct the sequence of events leading up to a security incident, identify the source of an attack, and gather evidence for legal proceedings or post-incident analysis. It aids in understanding the scope and impact of security breaches and facilitates remediation efforts.
When selecting a network traffic analysis tool, there are several key features organizations should consider ensuring it aligns with the company’s specific needs and helps to effectively monitor, analyze, and secure the network infrastructure.
Here are some important features to look for:
Gurucul has tailored its Network Traffic Analysis product to focus on identifying unknown network threats using advanced machine learning algorithms on network traffic and packet data. Gurucul NTA provides pre-packaged machine learning models which are pre-configured and tuned to run on high frequency network data streams to detect real-time anomalies and risk ranked threats.
In addition to network data, Gurucul also can ingest and link application and platform logs, security alerts, DHCP, CMDB data, vulnerability assessment reports, threat intelligence and access control data to build rich context. This provides end-to-end visibility and trace of the anomalous behavior kill-chain from across the network. This contextual linked data and extensive library of out-of-the-box behavior and threat models help identify advanced and unknown threats like zero-day exploits, fileless malware, and ransomware. This is achieved by detecting unusual behavior on a given entity (e.g. server, IP, device), any related lateral movement within the network, command and control (C2) communication, suspicious account activity from a compromised account, as well as access misuse.
The platform supports real-time data processing and analytics to quickly detect such threats at near real-time as well as uncover APT / stealth attacks which lay dormant between various stages of an attack. For instance, if a host belonging to the database administrator shows indications of suspicious outbound C2 traffic as well as lateral movement across a range of hosts not seen before, Gurucul NTA will immediately flag such risky abnormal behavior. The solution can be configured to trigger automated risk response to isolate the host from the production network or allow the NetOps team to take preventive actions before the compromise.
With the expansion of IoT and mobility in the borderless enterprise environment, one of the top threats has been the unauthorized use of non-registered devices, and WiFi/IoT networks, to gain access to enterprise networks. The Gurucul NTA solution also discovers and reports any unknown or unseen devices on the network. It closely monitors all activities from such devices with a higher resident risk score.
NetOps and SecOps users can further customize existing machine learning models or deploy their own from templates offered out of the box. These models are highly flexible and allow users to run analytics on a wide variety of attributes including IP addresses, ports, byte size, etc. Custom models are especially useful to track activity from non-traditional hosts such as CCTVs, PoS terminals and IoT devices. With an increasing number of Robotic Process Automations, bots and scripts on the prowl, accounting for and reducing the attack surface for what could be weak links in the network becomes imperative to ensure the overall health of the environment. There exist very few inherent means of securing these devices, and Gurucul Network Traffic Analysis can serve as a valuable alerting tool to preempt any malicious activity.
A side benefit is that network behavior analytics also can identify unregistered devices, network policy violations and network misconfigurations that result in higher risk.
Network traffic analysis is an important proactive defense mechanism that provides one more layer of security by delivering valuable insights into unusual or suspicious network activities. NTA enables proactive monitoring, threat detection, and incident response, helping organizations identify and mitigate security risks in a timely manner.
About The Author
Craig Cooper, Chief Operating Officer, Gurucul
Craig Cooper has served in several information security and risk management roles including CISO for a Fortune 500 Financial Services organization. While in this role, Craig defined and implemented an ISO standards-based Information Security program. Craig has led, developed, and delivered multiple Identity and Access Management Strategies and Roadmaps for several organizations. Craig has written for several trade magazines and has been a speaker with Burton Catalyst, Gartner, and ISSA
Network traffic data is analyzed by capturing and collecting packets, filtering, and parsing the information, applying statistical analysis and machine learning techniques for anomaly detection and pattern recognition, conducting deep packet inspection, and interpreting the results to identify security threats, performance issues, or network optimization opportunities.
The goal of analyzing and monitoring network traffic for cyber threats is to enhance an organization’s cybersecurity defenses. This is done by having another layer of threat detection; getting an early warning of threats before they can cause damage; getting valuable insights to assist with incident response; gathering evidence for attack attribution; and identifying vulnerabilities and weaknesses in the network infrastructure.
UEBA (User and Entity Behavior Analytics) and NTA (Network Traffic Analysis) are two distinct approaches to network security. UEBA focuses on analyzing user and entity behavior within a network to detect abnormal or potentially malicious activities. It utilizes machine learning and behavioral analytics to establish baselines of normal behavior and identify deviations that could indicate security threats. On the other hand, NTA primarily focuses on analyzing network traffic patterns, protocols, and flow data to detect anomalies or indicators of compromise. It involves monitoring and inspecting network packets to identify malicious activities or unauthorized access attempts. While UEBA emphasizes user behavior, NTA is more concerned with the network-level aspects of security monitoring.