Harnessing Artificial Intelligence in Network Detection and Response

Imagine this scenario: You are an office administrator responsible for the upkeep of the workplace. Every day, someone sneaks in and steals employee lunches from the breakroom fridge. First, you put up a sign that says, "No stealing food!" The culprit ignores it and takes the food anyway. Next, you install a security camera with motion detection. You receive an alert any time motion is detected near the fridge. Eventually, you can actively watch the thief stealing food, allowing you to catch them in the act. 

Now, imagine there are multiple fridges across the entire office that are under threat from multiple thieves. How are you supposed to monitor all the fridges, respond to threats and also tend to your other job duties? This is how many older network detection and response (NDR) mechanisms respond to cyber threats, overwhelming security teams with alerts. But what if there was a way to detect how and when the thief is stealing lunches — even if they are using unexpected methods such as wearing a disguise or turning off the lights — and then respond to the thief with no interaction from you? This is how AI-driven NDR solutions help security teams improve threat detection and accelerate response time. 

The evolution of network detection and response (NDR) 

NDR has come a long way from a simple rule-based system that relied solely on predefined signatures to detect threats. While effective for known attacks, these methods fail to identify new or evolving threats. Many of the threats on the rise today — including advanced persistent threats (APTs) and polymorphic malware — no longer follow a cookie-cutter approach, rendering the old-school rule-based defenses obsolete. AI bridges the gap by continuously analyzing network traffic, identifying anomalies, adapting to attacks in real time and alerting network teams when high-priority threats become critical. Using an AI-powered NDR solution allows organizations to secure networks by improving the detection of threats, accelerating response time and reducing the burden on security teams.

AI-powered threat detection

AI NDR solutions will establish baselines for normal network behavior and then identify deviations from that baseline that may signal threats. For example, a network with AI-driven NDR might notice unusual login activity from a foreign IP address outside of normal business hours. This could be explained away as a manager on an international vacation logging in to check emails. However, it could also be a foreign adversary deciding to launch an attack when network teams are home and not able to respond. With AI, this anomaly would be flagged instantly, enabling a plan to mitigate the potential risk regardless of whether the attack signature is recognized.

The power of AI lies in its ability to detect patterns that humans miss. Machine learning (ML) algorithms sift through terabytes of network data to identify:

• Sudden spikes in data transfer, indicating exfiltration of data and assets.
• Lateral movement within a network, indicating malware attacks. 
• Unusual communication between devices. 

A key advantage of implementing an AI-driven NDR solution is the ability to adapt to different industries and their unique security challenges. In highly regulated sectors, such as finance and healthcare, compliance is critical to ensure continuous business operations. These sectors have laws and standards, such as GLBA in the financial sector or HIPAA in healthcare, which mandate the protection of customer data and enforce strict security standards in their respective industries. AI-powered NDR solutions help organizations comply with regulations by detecting unauthorized access attempts, preventing data breaches and ensuring continuous monitoring of sensitive information. 

Additionally, international organizations must comply with region and country-specific data protection laws. In the United States, businesses that operate in multiple states must comply with laws localized to the state, such as California's CCPA. In addition, many countries and regions have their own laws on data protection, such as the European Union's GDPR. These laws and regulations establish guidelines for data privacy and security, requiring companies to protect personal data and provide transparency on its usage. 

AI-powered NDR solutions assist businesses in staying compliant with these industry-specific, state-level laws and international regulations by automatically detecting and mitigating risks before they lead to violations or costly penalties.

Accelerating response times

Speed is critical when responding to network threats. AI-driven NDR systems can automate responses — such as isolating compromised endpoints or blocking malicious traffic — reducing the time between detection and mitigation. The system can react instantly, much faster than network engineers could even identify the threat on their own.

Take the example of a global retailer that deploys an AI-powered NDR platform. The company uses a bring-your-own-device (BYOD) policy allowing employees to bring their personal devices onto the organization's network. A disenfranchised employee decides to steal company data for malicious purposes. The system will detect the device trying to access and copy sensitive customer data and then label it as a threat in response. The automated response would isolate the employee's device and alert the security team, preventing data theft and saving the company millions in potential damages. 

The ability to quickly respond to threats has tangible benefits for an organization's overall health. Reducing the time from threat detection to response drastically minimizes the impact of a data breach. For large enterprises, a quicker response means significantly lower financial losses due to data theft, ransomware and security threats. Mean time to respond (MTTR) — which tracks the average time it takes to mitigate a detected threat in an organization's network — is a key metric to measure an organization's response efficiency. Prolonged exposure to a threat increases the likelihood or amount of stolen data; a decreased MTTR mitigates operational disruption and reduces financial damage. Organizations that prioritize reducing MTTR through automation and AI-driven solutions react to threats in real time, preventing escalation, minimizing the overall impact of a breach and ensuring business continuity after a threat. 

Additionally, automation reduces the workload on security teams, allowing them to focus on proactive threat hunting and strategic security improvements rather than constantly reacting to alerts. By leveraging AI-driven NDR solutions, organizations can increase operational efficiency while maintaining a stronger security posture.

Reducing the burden on security teams

The sheer volume of alerts, which often turn out to be false positives, is overwhelming security teams and reducing their efficiency. An AI-driven NDR solution alleviates this burden by filtering out noise and prioritizing only high-risk incidents that require human intervention. This allows security analysts to brush past the false positives and minor threats to focus on legitimate threats. 

AI-driven NDR solutions also significantly reduce the workload of security teams by automating repetitive and time-consuming tasks such as log analysis, anomaly detection and incident triage. Traditional security methods require analysts to manually inspect individual alerts, including false positives that require no intervention from the team. Not only is this method inefficient, but it also leads to alert fatigue and burnout. AI-driven NDR solutions reduce this burden by filtering out the noise, prioritizing high-risk threats and ensuring that only critical incidents that require human intervention are brought to security teams. AI allows security analysts to focus their expertise on genuine threats rather than wasting time on low-priority alerts.

Furthermore, AI-powered solutions enhance operational efficiency by accelerating threat response times and improving accuracy. With machine learning models continuously analyzing network behavior, AI can detect threats proactively, before they escalate into major incidents. Automated response mechanisms enable security teams to address threats swiftly and minimize potential damage. Additionally, AI-driven analytics provide deeper visibility into attack patterns, allowing organizations to customize their security strategies and strengthen defenses to the threats they are facing. By reducing the manual effort required for threat detection and response, security teams can work more efficiently, optimize resources and maintain a proactive security posture.

AI-powered security solutions from WWT partners

WWT's security partners are leveraging AI to enhance and evolve their NDR solutions, providing organizations with greater visibility, faster threat detection, and more efficient response capabilities. By integrating AI-driven analytics, machine learning and automation, these solutions help security teams reduce manual workloads, improve accuracy and mitigate cyber threats more effectively.

NETSCOUT: Enhances network visibility and threat detection across hybrid environments.

ExtraHop: Utilizes deep packet inspection and AI to detect and respond to threats in real time.

Illumio: Focuses on micro-segmentation and zero trust security to limit lateral movement.

Guardicore: Provides flexible segmentation solutions to protect critical assets and contain threats.

For a deeper dive into these AI-powered security solutions, check out WWT's partner articles for each vendor.

Conclusion

AI-driven NDR solutions are transforming the way organizations detect, respond to and mitigate cyber threats. Just as the office administrator and lunch thief highlighted the challenge of monitoring multiple threats at once, security teams face an overwhelming number of alerts, making it difficult to focus on the real dangers that threaten an organization's network. AI solutions filter out false positives, prioritize high-risk incidents and automate responses, enabling security teams to focus only on threats that require human intervention.

By embracing AI-powered NDR solutions, organizations gain enhanced visibility, faster response times and an improved security posture. Whether through anomaly detection, automated threat mitigation, or improved compliance with industry regulations, AI is revolutionizing organizations' security posture. As threats continue to evolve, leveraging AI-driven security solutions from WWT and its partners will be essential in staying ahead of threats, safeguarding critical assets, and maintaining business continuity in an increasingly complex digital landscape.