What is Network Traffic Analysis?

Network traffic analysis is the process of analyzing network traffic using machine learning and rule-based algorithms. I know this definition isn’t very helpful, so let me expand on the idea of NTA (network traffic analysis).

Suppose you are working on a task within your company network when a hacker or an unknown person tries to access your network or tries to install malware in your system. What would happen? You probably wouldn’t know right away because you’re not constantly monitoring the network for suspicious activity. This is where NTA helps: it constantly monitors the network. If it detects any suspicious activity or security threat, it tries to fix minor issues. If it detects more serious vulnerabilities, it alerts the IT team.

Other network security tools also exist, such as firewall, intrusion prevention systems (IPS)and intrusion detection systems (IDS). These tools secure your network at its perimeter against traffic that attempts to enter the network without permission. In contrast, NTA secures the network against intra-parameter threats and outside traffic threats from the cloud, virtual switches, and traditional networks. TCP/IP packets.

Nowadays, in addition to traditional algorithms, NTA incorporates machine learning solutions. Machine learning algorithms, such as time series analysis, analyze general network behavior. If the algorithms detect abnormal activity, the NTA tools notify the network team. Using NTA has several advantages:

  • Provides analytics services
  • Monitors IoT devices that generate and send lots of data over the network
  • Addresses various security issues
  • Improves end-to-end cloud visibility

In this article, you will discover the NTA, its importance, its strengths and its weaknesses.

NTA solutions keep track of every device connected to your network. They keep tabs on who is using the network and when. When cloud computing has become a thing, network visibility has become difficult. Multiple devices on a network share data via the cloud or IoT devices. Hackers or anyone unknown can enter a network using different tactics; with advances in technology, hackers are constantly training to crack all the security element.

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When we think of security, firewalls can tackle most threats that arise when installing software or exchanging files on a network, but there can be difficult traffic that even a firewall cannot stop. For example, Ransomware might look like software and pass through a firewall. Sometimes network users can use different mechanisms like VPN to bypass a firewall which can lead to security issues. NTAs can fight ransomware and other security threats that pass through the firewall.

The machine learning algorithms used for NTA can detect security threats even if they are encrypted. And that’s not all. In addition to analyzing threats on the network, NTA also helps monitor resource usage and helps IT teams manage resources accordingly. In cases where a network does not use a resource for a long period of time, the NTA solution asks the IT team to decommission it. This saves the cost of that extra resource. Finally, NTA also provides information about network availability and downtime. Some vulnerabilities can cause network downtime, and an NTA tool will notify the network team so they can inspect anomalies and resolve issues.

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Now that you know about NTA and why it is important for any organization that uses a network, let’s focus on the strengths and weaknesses of NTA. Let’s start by identifying the strengths first.

  • Integrated predictive analysis: You have already learned that NTA uses different machine learning algorithms, such as time series analysis, to identify suspicious activity on a network. This analysis process begins with storing data on the network, then training machine learning algorithms on that data, and finally using the data to make runtime predictions about traffic traversing the network. .
  • Extended visibility: I believe that broad visibility is the greatest strength of NTA solutions. They monitor traffic from almost any source, such as TCP/IP packets, connected IoT devices, switches, and API calls.
  • Speed: NTA solutions analyze security threats faster than any other network monitoring tool. Not only do they identify the threat, but they also respond appropriately, either by blocking unknown entities or notifying the network security team.
  • Traffic analysis: Organizations need an easy-to-use technique to decrypt network traffic without compromising data privacy. NTA systems meet this requirement. They assess the entire payload so that security professionals know the risks of the network without having to examine the network themselves.
  • Resource Monitoring: Along with monitoring security threats, NTA keeps notes on resource usage. This helps IT teams manage resources accordingly. If a resource remains inactive for a long period of time, it may be removed or adjusted.
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Since you are IT professionals, you might know that every technology has its dark side. NTA also has some weaknesses and drawbacks.

  • Data storage: Network traffic analysis is based on historical data. Obviously, you need some data to train time series models, which you can then use to identify unknown objects and fluctuations in the network. You need a lot of data to train the machine learning algorithms. Most NTA tools do not store the oldest data, and over time they only store the most recent data. Due to this flaw, NTA tools may sometimes fail to identify issues. Machine learning models are iteratively trained on older data and if older data is not available, the algorithms may be poorly trained. This can cause NTA solutions to miss some issues.
  • Data processing: In a network, data moves in different forms, namely packet data and stream data. These types of data movement come from different sources. Most NTA solutions do not handle both types of data. This makes the network more vulnerable to security threats, as hackers can break into your network using either type of data movement.
  • Cost and complexity: NTA solutions retain data in packets. Because of this, organizations have to purchase devices such as load balancers, packet filtering firewalls, and storage devices, which increase an organization’s costs. In addition, they are complex to manage and therefore require some expertise to operate.
  • Security: Although NTA solutions secure your network, they are manufactured by many different companies. Organizations must have great confidence in the companies providing these solutions. If the company is trustworthy, there is no reason to worry, but if not, it brings security issues to your network.

Now that you know a bit about the strengths and weaknesses of NTA, let me tell you that this is only a very short explanation. To really know the NTA and know more about its importance, strengths and weaknesses, you must read The price of hubris. This book ensures that you won’t have to visit other resources to learn more about NTA. It goes into more detail about how hackers exploit gaps in NTAs. Good reading!

After reading this article, you now know a bit more about network traffic analysis, its importance in securing networks, and its various strengths and weaknesses. A network is a combination of different entities connected together with data flowing in different forms. Traditional security mechanisms, such as firewalls and intrusion detection systems, help secure the perimeter of a network. But it is difficult for these solutions to identify security threats from cloud components, IoT components, and externally connected components. NTA solutions solve this problem by analyzing these sources as well.

This post was written by Gourav Singh Bais. Gurav is an applied machine learning engineer, specializing in the development of computer vision and deep learning pipelines, the creation of machine learning models, the training of recycling systems and the transformation of data science prototypes into manufacturing solutions.

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*** This is a syndicated blog from the Security Bloggers Network of Blog written by Gourav Bais. Read the original post at: https://www.traceable.ai/blog-post/network-traffic-analysis

Charles J. Kaplan