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Network Segmentation in 2024: 6 Benefits & 8 Best Practices

Updated on May 31
8 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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Researched by
Mert Palazoğlu
Mert Palazoğlu
Mert Palazoğlu
Mert Palazoglu is an industry analyst at AIMultiple focused on customer service and network security with a few years of experience. He holds a bachelor's degree in management.
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Network Segmentation in 2024: 6 Benefits & 8 Best PracticesNetwork Segmentation in 2024: 6 Benefits & 8 Best Practices

AIMultiple team adheres to the ethical standards summarized in our research commitments.

Cybersecurity development is increasing as companies continue to invest in network segmentation technologies.

Digital-hungry companies can learn about network segmentation and its statistics to obtain a competitive edge by establishing, growing, and sustaining stakeholders’ trust in the usage of their digital-enabled products and services against threats.

Thus, security executives may understand network segmentation examples and network segmentation use cases, features, and benefits to understand how to secure their operational and web-based resources.

What is network segmentation?

Network segmentation is a defense-in-depth security mechanism that divides the main network into several, smaller subnetworks to limit a cyber attacker’s activity by minimizing lateral network movement.

Each subnetwork or “zone” represents an extra layer of security (e.g. microsegmentation, role-based access control (RBAC), zero trust network access (ZTNA)), with its access point, username and password, and firewall protection. 

Note: A network is a group of machines that are connected.

Read more: Network segmentation vs microsegmentation.

What is an example of segmentation?

Consider a major retailer with several branch locations. According to the retailer’s security protocol, branch personnel are not permitted to access the accounting data system. By prohibiting all branch data from accessing the accounting system, network segmentation can implement the security standard. 

Physical vs logical network 

Network segmentation can be classified under two major categories: physical and logical network segmentation.

The physical network is the visible infrastructure, whereas the logical network is the abstract, functional framework that determines how data flows inside the physical network.

Learn more about insider threat management and its insider threat management software.

Here is how the segmentation process works for these two types of networks:

  • Physical network: A physical network refers to the actual hardware components that connect devices, such as wires, routers, endpoints, hubs, switches, and other physical structures. 
  • Logical network: A logical network applies to how data is transported between devices and how they are structured and controlled, frequently through the use of protocols and addressing schemes. 

Learn more about Internet of Things (IoT) cybersecurity.

Why should organizations consider implementing network segmentation?

Network segmentation is an effective instrument for preventing outsiders (e.g. customers, vendors, malicious attackers, or any unauthorized user) and protecting static IP addresses, whether third parties, from accessing sensitive data such as personal data or corporate accounting files.

The following are some of the reasons for implementing network segmentation:

  • Massive networks are divided into smaller, more manageable portions.
  • Security operators can create specific rules for each subnet.
  • Operators can regulate, manage, and restrict traffic flow across subnets.
  • Some parts of the network can experience reduced user traffic, leading to increased network performance.
  • Improves security in terms of minimizing how far a harmful attack may move, by constraining the fraud or network threat (e.g. ransomware) into a single segment.

Read more: Data security posture management or DSPM vendors.

How does network segmentation work?

Network segmentation separates a network into many portions, each of which may be controlled differently. This technique is often carried out by adopting one of two approaches: physical segmentation or logical segmentation.

1- Physical segmentation 

Physical segmentation is the process of dividing a large computer network into smaller subnets. For example, a physical or virtual firewall can operate as the subnet gateway, regulating which traffic enters and exits the network. 

Functionality: Because the layout is set in the design, physical segmentation is simple to manage, however, it is economically expensive, less flexible, and scalable since the company must purchase, deploy, and manage actual hardware on-premises.

Since physical segmentation needs more flexibility and scalability it may reduce the different types of security protocols. For example, if the company expects to update its network setup to achieve PCI DSS compliance, the company may need to wait until it has the necessary resources, equipment, and specialized personnel.

2- Logical segmentation

Logical segmentation is the process of using software to divide a network into smaller sections by subnetting. Logical segmentation creates subnets using two major methods: virtual local area networks (VLANs) or network addressing schemes. 

VLANs — divide traffic on one physical network into different networks without the need for additional routers or Internet connections to route network data to various destinations.

Network addressing schemes — divide network resources among different layers to generate network segments across the Layer 3 network (determines how data is forwarded, routed, and addressed to the receiving device).

Functionality:  Logical segmentation is far more adaptable than physical segmentation. Both VLAN and network addressing schemes segmentation methods are less costly and more flexible since these approaches allow users to set up real-time security configurations or redesign the network without purchasing new equipment.

For example, VLAN and network addressing schemes tags autonomously route traffic to the proper subnet, and VLAN-based systems are relatively simple to install. 

Example of a network segmentation use case:

For example, companies may isolate their PCI (peripheral component interconnect, a local computer network that is used to connect hardware devices in a computer) zone from their network by setting firewall policies to guarantee compliance with the PCI-DSS council’s criteria. 

Network administrators may then further divide their PCI connection into “PCI Web, PCI App, and PCI Data zones”, specifying which zones may connect to the others and how (in this instance, only the company’s network can connect with the PCI zone, and not the public network).

Figure: Network segmentation with firewalls

Traditional network segmentation (VLAN, ACL, and Firewall) vs microsegmentation

Traditional networks classify service traffic via firewalls, virtual local area network VLANs, and access control lists (ACLs). These methods have certain differences:

VLAN: VLANs are set up to separate services by using subnets, however, they cannot isolate servers inside the same subnet.

ACL: Servers can be isolated using ACLs. A data center network, on the other hand, has a high number of servers. When host services are being segmented, a significant number of ACL rules are required to be set, leading to complicated setup and administration. Furthermore, network devices are restricted in ACL capabilities and are incapable of meeting the criteria for installing a large number of ACL constraints.

Firewall: Firewalls are only used to link the DC to third-party networks for internal isolation, a firewall can be installed on each network node in a DC. This entails a high number of firewalls, which involves a significant amount of hardware and technology investment along with significant configuration and service operations.

Microsegmentation: Microsegmentation implements security access control to particular workloads or applications rather than the entire network. 

It differentiates itself from other traditional network segmentation methods by providing a finer-grained segmentation. Microsegmentation tools allow administrators to adjust segmentation based on IP address, IP network segment, MAC address*, and VM name segmentation.

Read more: Microsegmentation use cases, microsegmentation examples.

*A MAC is a unique identifier issued to a network interface controller that serves as a network address in intra-network communications.

Benefits of network segmentation

1- Improved cybersecurity risk management: Segmentation can neutralize attacks with mobility limits by defining barriers between distinct sub-segments. This granular approach improves security by preventing hackers from moving laterally once they have breached the network. 

Automated cyber risk management: Automated security risk assessment employs automated technologies to automate the data collecting process for risk assessment, allowing more accurate analysis and identification of prospective risks. 

This process involves using machine learning, and automated techniques in technologies such as:

2- Increased network visibility: Network segmentation creates subnets (a network inside a network) where traffic may move a shorter distance without passing through unnecessary routers. This makes it significantly easier to monitor vulnerabilities and detect the most common cyber attack vectors compared to a larger network because of its limited reach.

3- Protecting physical devices: Segmentation can prevent risky traffic from accessing devices incapable of defending themselves by creating a flat network. A facility’s networked control systems, for example, may not be constructed with strong security measures. Network segmentation can prevent potentially risky Internet traffic from accessing them.

*Flat networks are intended to decrease the number of switches and routers on a network by connecting devices to a single switch rather than numerous switches.

4- Limiting cyberattack damage: Segmentation helps cybersecurity by restricting the distribution of an attack. Segmentation, for example, prevents malware from spreading in one part from contaminating devices in another.

5- Building IT governance:  Network segmentation transforms security policies into a useful baseline, providing transparency into current compliance failures and enabling active detection of requests for data that violate compliance

6- Developing compliance: With network segmentation compliance can be achieved by modeling security policies. By establishing this baseline of allowed access through approved services, companies can identify and clear up existing breaches while preventing the entry of new ones. 

8 Best practices of network segmentation

Learn more about cybersecurity best practices.

1- Limit third-party access

74% of IT users say that data breaches result from providing too much privileged access to third parties.1

Companies may limit and control third-party risk. Not all third-party suppliers require complete access to the corporate servers to continue functioning at full capacity. To mitigate the effect of a possible data breach, companies should only grant contractors the minimal degree of access required to perform their duties. Creating distinct gateways with specific security measures for each user is one method for isolating third-party access to minimize data leaks.

2- Avoid excessive or insufficient segmentation

A typical error when implementing network segmentation is over-segmenting or under-segmenting into excessive networks. Large-scale companies with a high volume of network activities may assume that the most security is achieved by segmenting as much as practical. However, it is essential to achieve a balance between having enough resources to govern and manage various networks and affecting digital worker efficiency.

  • Over-segmentation can lead employees to navigate through many access points to acquire data access, resulting in bottlenecks in workflow. 
  • Under-segmenting a network may also result in ineffective operations if the isolation between each system is inadequate. A single network divided into two or three segments would not offer the degree of security required for appropriate network segmentation.

3- Monitor and audit networks in real-time

To eliminate the gaps or weaknesses in the network, all segmentation operations should include continuous monitoring and auditing of network traffic and activity. 

Network monitoring: Continuous network monitoring gives businesses a thorough view of their networks and information about possible vulnerabilities. For this, you can check our in-depth vendor selection guide on network monitoring tools.

Network audits: Periodic network audits allow companies to assess the success of their present security practices. With network audits companies can detect security breaches in the network so that the network’s administration team may take corrective action. 

Auditors often examine the following critical parameters during a network audit:

  • Network administration.
  • Network accessibility (e.g. role-based access control RBAC).
  • Network security.
  • Network performance.

Read more: RBAC use cases, RBAC examples.

4- Classify resource attributes

Companies can assess their resources and attribute values to them before setting up any network segmentation constraints. Each resource (applications, IoT (internet of things) devices, databases) should be classified according to its relevance, data sensitivity, and priority.

5. Combine identical or similar resources

After the resources are classified based on their attributes and value, companies can begin grouping comparable network resources. Items with lower security should be placed on an identical network as other assets with higher security. 

This approach can help to make it easier to design and maintain security protocols for each network and determine which networks are prioritized against others, which streamlines network surveillance and filtering.

6. Execute endpoint security 

Endpoint devices are frequently targeted by cyber assaults because they are frequently neglected and lack sufficient security. Only one attacker has access to the whole main network. 

The endpoint detection and response (EDR) method can help companies add an extra layer of security by actively tracking cyber threat intelligence (CTI) metrics such as IOAs (indicators of attacks) and IOCs (indicators of compromise). Thus, companies may record the actions and activities that occur on endpoints and across all workloads, giving security personnel the insight they need to find issues that might otherwise go undetected.

7. Adhere to the principle of least privilege

When network segmentation is in place, each network should adhere to the zero-trust paradigm and the concept of least privilege. These practices entail restricting network access at all tiers, which entails authentication from all users inside the network perimeter.

The following technologies help companies build a zero-trust architecture: 

8- Automate cybersecurity practices

Creating a network segmentation strategy can be an overwhelming task, particularly for large-scale networks. Manually doing all of these tasks may be impracticable. Cybersecurity automation is a useful instrument for detecting cyber threats or vulnerabilities, streamlining workloads, and recognizing new assets added to the network while implementing network segmentation.

Security users can leverage automation (e.g. RPA for Cybersecurity ) capabilities to perform operations such as automating data enrichment tasks, automating privileged data management, and eliminating unauthorized access. 

For guidance on choosing the right tool or service for your organization, check out our data-driven research and lists of software-defined perimeter (SDP) software, microsegmentation tools, and zero trust networking software.

Further Reading

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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