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市場調查報告書
商品編碼
2169953
網路偵測與回應 (NDR) 市場預測至 2034 年-全球分析(按元件、部署模式、偵測方法、網路環境、組織規模、應用程式、最終使用者和地區分類)Network Detection and Response Market Forecasts to 2034 - Global Analysis By Component (Solutions and Services), Deployment Mode, Detection Technique, Network Environment, Organization Size, Application, End User and By Geography |
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根據 Stratistics MRC 的數據,預計到 2026 年,全球網路偵測和回應市場規模將達到 43.4 億美元,在預測期內以 14.5% 的複合年成長率成長,到 2034 年將達到 128.4 億美元。
網路偵測與回應 (NDR) 指的是一套網路安全解決方案、平台和服務,它們持續監控網路流量和元資料,以識別繞過傳統邊界和終端防禦的異常、惡意或可疑活動。這些系統利用行為分析、機器學習和基於特徵的檢測技術,分析本地、雲端、混合和營運技術 (OT) 環境中的「南北向」和「東西向」通訊。透過將網路遙測資料與身分資訊和威脅情報關聯起來,這些平台使安全團隊能夠偵測到原本會被忽略的橫向移動、資料外洩和入侵後活動。
網路威脅和規避攻擊的方法日益複雜
各行各業的組織都面臨著日益複雜的威脅行為者。他們利用合法工具、加密通訊管道以及「借力打力」(LoTL)技術來繞過傳統的安全控制,並在企業網路中長時間保持不被發現的狀態。僅靠邊界防禦和端點檢測與回應(EDR)解決方案無法應對這些漏洞,因此,對能夠提供其他工具無法觸及區域的網路中心檢測能力的需求日益成長。隨著攻擊者以機器般的速度加速偵察和橫向移動,各行各業對能夠即時識別入侵後活動的NDR解決方案的需求也不斷增加。
與現有安全基礎設施整合的複雜性
部署網路偵測與回應平台通常需要與現有的安全資訊和事件管理 (SIEM)、安全營運自動化與回應 (SOAR) 以及終端安全工具進行大規模整合。這可能導致部署延遲,並給本已分散的工具棧的安全團隊帶來維運上的不便。企業經常會面臨警報疲勞和需要在多個主機之間頻繁切換的問題,從而降低網路偵測與回應 (NDR) 投資的有效性。這些整合挑戰可能會延誤部署進度,並限制保全行動資源有限的企業的投資回報。
AI驅動的基於代理的SOC和自主運行
基於代理的人工智慧 (AI) 技術在保全行動的興起,為網路偵測與回應 (NDR) 平台帶來了變革性的成長機遇,使其能夠自動化目前耗費分析師大量時間的調查、分類和回應工作流程。 AI 代理可以查詢網路遙測數據,關聯來自不同身分和終端來源的證據,並以機器速度執行遏制措施。隨著各組織機構尋求縮短平均回應時間並解決長期存在的安全人才短缺問題,預計 AI 增強 NDR 技術的採用速度將顯著加快。
大規模DDoS攻擊與網路可用性風險
威脅情勢日益嚴峻,其中分散式阻斷服務 (DDoS) 攻擊的流量越來越大,足以癱瘓網路基礎設施並危及服務可用性。根據 NETSCOUT 發布的《2026 年上半年威脅情報報告》,全球已記錄超過 910 萬起 DDoS 攻擊,其中流量超過 1 Tbps 或 1 Gpps 的攻擊數量同比成長 1286%。這些高流量攻擊已不再是罕見現象,而是司空見慣,給電信業者的緩解能力帶來了巨大壓力,並迫使負責人做好準備,應對攻擊在整個網路邊緣的升級。
在疫情初期,各組織優先考慮遠距辦公,而非升級安全基礎設施,導致網路偵測與回應 (NDR) 的部署和採購週期出現暫時性延誤。隨著分散式辦公模式的擴展和雲端採用的加速,企業面臨著來自非託管設備和不斷擴大的攻擊面的日益成長的風險,而這些風險是邊界防禦無法應對的。疫情後,網路偵測與回應 (NDR) 成為一項策略重點,各組織正在整合 NDR 功能,以支援零信任架構並維持對其永久混合環境的可見性。
在預測期內,解決方案領域預計將佔據最大的市場佔有率。
預計在預測期內,解決方案細分市場將佔據最大的市場佔有率,這主要得益於訂閱式網路偵測與回應 (NDR) 平台持續穩定的收入模式,以及市場對整合網路流量分析、行為檢測和自動回應等功能的整合解決方案日益成長的需求。各組織正在將各個獨立產品整合到一個統一的平台中,從而實現端到端的可視性。因此,解決方案預計將在整個預測期內保持領先地位。
在預測期內,基於機器學習的檢測領域預計將呈現最高的複合年成長率。
在預測期內,基於機器學習的檢測領域預計將呈現最高的成長率,這主要得益於人工智慧驅動的異常檢測技術的日益普及。此技術無需依賴靜態特徵或預定義規則即可識別規避型威脅。隨著攻擊者不斷改進其策略以規避傳統檢測方法,對能夠識別行為偏差並檢測「借力打力(LoL)」攻擊的機器學習能力的需求正在加速成長,預計該領域將走上最快的成長軌道。
在預測期內,北美地區預計將佔據最大的市場佔有率。這主要歸功於領先的網路偵測與回應 (NDR) 供應商、超大規模雲端服務供應商以及擁有成熟安全營運中心 (SOC) 的企業在美國和加拿大的集中佈局。該地區健全的法規結構、大量的網路安全投資以及對先進檢測技術的早期應用,進一步鞏固了北美市場的領先地位,並推動了整個競爭格局的持續創新。
在預測期內,亞太地區預計將呈現最高的複合年成長率,這主要得益於新興經濟體的快速數位轉型、雲端運算的廣泛應用以及中國、印度、日本和東南亞市場對網路安全威脅日益增強的認知。隨著當地企業面臨越來越大的監管壓力,需要對其IT基礎設施進行現代化改造並保護敏感數據,對網路偵測和回應解決方案的需求也隨之加速成長。同時,跨國供應商正在擴大在該地區的業務,以把握這一不斷擴大的市場機會。
According to Stratistics MRC, the Global Network Detection and Response Market is accounted for $4.34 billion in 2026 and is expected to reach $12.84 billion by 2034 growing at a CAGR of 14.5% during the forecast period. Network detection and response refers to the set of cybersecurity solutions, platforms, and services that continuously monitor network traffic and metadata to identify anomalous, malicious, or suspicious activity that evades traditional perimeter and endpoint defenses. These systems apply behavioral analytics, machine learning, and signature-based detection techniques to analyze both north-south and east-west communications across on-premises, cloud, hybrid, and operational technology environments. By correlating network telemetry with identity data and threat intelligence, such platforms enable security teams to detect lateral movement, data exfiltration, and post-breach activity that would otherwise remain invisible.
Escalating Sophistication of Cyber Threats and Attack Evasion
Organizations across industries face increasingly sophisticated threat actors who leverage legitimate tools, encrypted channels, and living-off-the-land techniques to evade traditional security controls and remain undetected within enterprise networks for extended periods. Perimeter defenses and endpoint detection and response solutions alone cannot address these gaps, thereby driving demand for network-centric detection capabilities that provide visibility where other tools cannot reach. As attackers accelerate reconnaissance and lateral movement at machine speed, the need for NDR solutions that can identify post-breach activity in real time continues to intensify across all industry verticals.
Integration Complexity with Existing Security Infrastructure
Deploying network detection and response platforms often requires significant integration effort with existing SIEM, SOAR, and endpoint security tools, which can introduce deployment delays and operational friction for security teams already managing fragmented tool stacks. Organizations frequently struggle with alert fatigue and context switching across multiple consoles, which reduces the effectiveness of NDR investments. These integration challenges slow adoption timelines and can limit the return on investment for organizations with constrained security operations resources.
AI-Driven Agentic SOC and Autonomous Operations
The emergence of agentic AI capabilities within security operations presents a transformative growth opportunity by enabling NDR platforms to automate investigation, triage, and response workflows that currently consume significant analyst time. AI agents can query network telemetry, correlate evidence across identity and endpoint sources, and execute containment actions at machine speed. As organizations seek to reduce mean time to response while addressing persistent security skills shortages, adoption of AI-enhanced NDR capabilities is expected to accelerate considerably.
High-Volume DDoS Attacks and Network Availability Risks
The threat landscape includes increasingly high-capacity distributed denial-of-service attacks that can overwhelm network infrastructure and disrupt service availability. NETSCOUT's first half 2026 threat intelligence report recorded more than 9.1 million DDoS attacks globally, with attacks exceeding 1 Tbps or 1 Gpps surging 1,286 percent year over year . These high-capacity events are no longer anomalies but routine occurrences, placing significant pressure on carrier mitigation capacity and requiring defenders to prepare for greater attack intensity across network edges.
The pandemic initially disrupted NDR deployments as organizations prioritized remote work enablement over security infrastructure upgrades, causing temporary delays in procurement cycles. As distributed workforces expanded and cloud adoption accelerated, enterprises faced heightened risks from unmanaged devices and expanded attack surfaces that perimeter defenses could not address. Post-pandemic, network detection and response has become a strategic priority, with organizations embedding NDR capabilities to support zero-trust architectures and maintain visibility across permanently hybrid environments.
The solutions segment is expected to be the largest during the forecast period
The solutions segment is expected to account for the largest market share during the forecast period, owing to the recurring revenue nature of subscription-based NDR platforms and the increasing preference for integrated solutions that combine network traffic analysis, behavioral detection, and automated response capabilities within a unified offering. Organizations seek to consolidate point products into cohesive platforms that provide end-to-end visibility, thereby making solutions the dominant component category throughout the forecast horizon.
The machine learning-based detection segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the machine learning-based detection segment is predicted to witness the highest growth rate, propelled by the increasing adoption of AI-powered anomaly detection that can identify evasive threats without relying on static signatures or predefined rules. As attackers continuously modify their techniques to bypass conventional detection methods, demand for machine learning capabilities that recognize behavioral deviations and detect living-off-the-land attacks accelerates accordingly, positioning this segment for the fastest growth trajectory.
During the forecast period, the North America region is expected to hold the largest market share, due to the concentration of leading NDR vendors, hyperscale cloud providers, and enterprises with mature security operations centers across the United States and Canada. The region's robust regulatory framework, substantial cybersecurity investments, and early adoption of advanced detection technologies further reinforce North American market leadership and drive continued innovation across the competitive landscape.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to rapid digital transformation across emerging economies, expanding cloud adoption, and increasing awareness of cybersecurity threats across China, India, Japan, and Southeast Asian markets. As local organizations modernize IT infrastructure and face growing regulatory pressure to protect sensitive data, demand for network detection and response solutions accelerates accordingly, while multinational vendors expand regional presence to capture this growing opportunity.
Key players in the market
Some of the key players in Network Detection and Response Market include Cisco Systems, Inc., Darktrace plc, Vectra AI, Inc., ExtraHop Networks, Inc., Corelight, Inc., Fortinet, Inc., Palo Alto Networks, Inc., Trend Micro Incorporated, Broadcom Inc., Trellix, NETSCOUT Systems, Inc., Arista Networks, Inc., Gigamon Inc., OpenText Corporation, Stellar Cyber, Inc., Sangfor Technologies Inc. and NIKSUN, Inc.
In September 2026, Trellix was recognized as a Visionary in the 2026 Gartner Magic Quadrant for Network Detection and Response, with Trellix Wise GenAI capability enabling customers to spend 57 percent less time prioritizing alerts and save an average of 48 hours per investigated alert.
In August 2026, ExtraHop Networks, Inc. announced its 400 Gbps sensor, making ExtraHop RevealX the first NDR platform to analyze enterprise data center traffic in full at line rate, providing autonomous agents with complete evidence rather than sampled telemetry.
Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.