by Network detection and response (NDR) solutions provide network-based context to detect threats, help investigate incidents, and automate response actions. These solutions analyze network traffic in real time to detect intrusions and threats. With the increasing volume and sophistication of cybersecurity attacks, organizations are increasingly adopting NDR solutions to strengthen their security posture. NDR solutions offer comprehensive visibility into networked environments, exposing hidden and unknown threats. The global network detection and response (NDR) Market is estimated to be valued at US$ 3.27 Bn in 2023 and is expected to exhibit a CAGR of 10% over the forecast period 2024 to 2031, as highlighted in a new report published by Coherent Market Insights.
Market Dynamics:
High Growth Owing to Rising Cybersecurity Threats
The network detection and response (NDR) market is expected to witness high growth due to the increasing frequency and complexity of cyber-attacks. According to Cybersecurity Ventures, cybercrime costs are projected to grow by 15% per year over the next five years, reaching US$ 10.5 trillion annually by 2025. As organizations accumulate more digital assets and adopt advanced technologies like cloud, IoT, and OT systems, their attack surface increases multi-fold. Traditional perimeter-based security tools are unable to detect threats within the networked environment. NDR solutions offer enhanced visibility for an organization’s entire attack surface, addressing both known and unknown threats in real time. Their ability to provide comprehensive network visibility and detect anomalies at early stages is creating significant demand.
SWOT Analysis
Strength: Network Detection and Response (NDR) solutions provide enhanced network visibility by monitoring network traffic patterns across the entire IT infrastructure in real-time. They leverage advanced analytics and machine learning to identify potentially malicious activities with high accuracy. Additionally, NDR solutions integrate various security controls and deliver consolidated security insights through a single interface, simplifying threat investigations and management for organizations.
Weakness: While NDR technology analyzes massive amounts of network traffic data in real-time, evaluating unusual patterns can sometimes lead to false positives and inaccurate alerts. Also, the high cost of deployment and management of NDR solutions poses budgeting challenges for smaller organizations with limited security budgets.
Opportunity: With the accelerating transition to remote and hybrid work models, the attack surface for organizations has expanded multi-fold. NDR’s capabilities for monitoring external and cloud-based assets help extend visibility beyond on-premises networks. Also, the tech’s potential for detecting unknown threats and stopping lateral movement make it a strategic priority area for cybersecurity investments moving forward.
Threats: Cybercriminals constantly devise sophisticated new tactics to bypass traditional defenses. Without regular upgrades, the ML and behavioral analytics of older NDR deployments may struggle to recognize new threat types. Additionally, the shortage of cybersecurity skills could impair some organizations’ ability to fully leverage the capabilities of NDR solutions.
Key Takeaways
The Global Network Detection And Response (NDR) Market Share is expected to witness high growth over the forecast period from 2024 to 2031.
North America currently accounts for the largest share of the NDR market owing to stringent regulatory compliance mandates and rising frequency of cyber-attacks targeting critical infrastructure sectors in the region.
Key players like ABB, Xcel Energy Inc., EDF, National Grid Renewables are investing in advanced AI/ML-driven NDR solutions to strengthen monitoring of IoT/OT environments and detect threats across hybrid enterprise networks spanning data centers, cloud platforms and remote endpoints.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
