Morné Vermeulen and Wesley van Rayne at Redvine Networks

The rapid digital transformation of businesses, adoption of cloud-based technologies, and the increasing complexity of cyber threats have compelled organisations to re-evaluate their network security strategies. As enterprises strive to maintain robust and secure networks, the importance of artificial intelligence (AI) in enhancing the network security footprint becomes more apparent.

In recent months, AI has emerged as a hot topic in South Africa and across the continent. There is no denying the allure of this technology and the temptation it presents for tech and business leaders to incorporate it into their organisations. Nevertheless, the true power of AI lies in the machine learning (ML) algorithms operating behind the scenes, which can be harnessed to benefit the infrastructure environment in more meaningful ways.

For example, ML can analyse historical and real-time data to identify patterns, optimise network performance, and detect anomalies. It is in this anomaly detection that significant value can be uncovered. Essentially, this involves capitalising on AI-driven tools to spot unusual behaviour in network traffic, facilitating early detection of potential security threats and performance issues.

Numerous vendors offer network solutions that incorporate anomaly detection within their AI platforms. Some even take it a step further by performing behavioural monitoring on users, flagging potential security and operational issues before they adversely affect the organisation’s infrastructure.

This software-driven approach to strengthening the network has led to the growing popularity of Software-Defined Wide Area Networking (SD-WAN) orchestration and network management in recent years. The ability to extract greater functionality from existing hardware using rapidly evolving software, powered by AI and ML, has unleashed boundless potential.

Moreover, this has underscored the significance of AI in Secure Access Service Edge (SASE) and SD-WAN solutions. Its capacity to proactively prevent network downtime and security breaches has become indispensable for today’s connected organisations.

SASE it up

SASE is an emerging cybersecurity framework that combines network security functions, such as firewall-as-a-service, secure Web gateway, and zero-trust network access, with wide-area network (WAN) capabilities. It aims to provide a single, unified solution for securing and optimising network traffic across different branches and remote users.

AI plays a crucial role in enhancing SASE’s network security features. By utilising machine learning algorithms, SASE can analyse massive amounts of data to identify patterns and correlations, which can help detect potential threats in real-time. AI-powered SASE can also adapt to new threats, enabling organisations to stay one step ahead of malicious actors.

Route traffic intelligently

SD-WAN simplifies the management and operation of WANs by decoupling the control plane from the data plane. It offers a more agile, cost-effective, and scalable approach to networking as compared to traditional WAN architectures.

AI integration within SD-WAN solutions allows for intelligent traffic routing, ensuring optimal performance and reduced latency. Furthermore, AI-driven SD-WAN can identify unusual network behaviour, which may indicate a security breach or potential network downtime. By continuously monitoring network traffic and proactively identifying threats, AI-powered SD-WAN solutions help to maintain network security and stability.

Taking a proactive stance

AI’s ability to process vast amounts of data and learn from it enables organisations to identify patterns and predict potential security breaches or network downtime. AI-based predictive analytics can be employed to recognise irregularities in network traffic and detect anomalies, which may indicate a cyberattack or system failure.

Additionally, AI-driven tools can provide automated responses to mitigate risks, such as isolating affected devices or blocking suspicious traffic, thus reducing the impact of security breaches or downtime on the organisation’s operations.

As businesses continue to embrace digital transformation and rely on cloud-based services, maintaining a secure and stable network becomes imperative. By integrating AI into network security solutions like SASE and SD-WAN, organisations can achieve enhanced security footprints and proactively prevent network downtime or security breaches. The ability of AI to adapt to new threats and predict potential issues ensures that businesses can maintain the highest level of network security, safeguarding their data and operations.