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市场调查报告书
商品编码
1785331
身分威胁侦测与回应市场-全球产业规模、份额、趋势、机会和预测(按产品、部署模式、垂直产业、地区和竞争细分,2020-2030 年预测)Identity Threat Detection and Response Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Offering, By Deployment Mode, By Vertical, By Region & Competition, 2020-2030F |
2024 年全球身分威胁侦测与回应 (ITDR) 市值为 130.2 亿美元,预计到 2030 年将达到 427.2 亿美元,复合年增长率为 21.90%。全球身分威胁侦测与回应 (ITDR) 市场是指网路安全解决方案领域,专注于侦测、监控和减轻数位生态系统中与身分相关的威胁。
市场概览 | |
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预测期 | 2026-2030 |
2024年市场规模 | 130.2亿美元 |
2030年市场规模 | 427.2亿美元 |
2025-2030 年复合年增长率 | 21.90% |
成长最快的领域 | 资讯科技与 ITES |
最大的市场 | 北美洲 |
与传统的身分和存取管理系统不同,ITDR 解决方案能够主动监控身分活动、侦测异常并即时回应恶意攻击。这些解决方案利用进阶分析、行为生物识别和人工智慧驱动的洞察,帮助防范凭证盗窃、权限提升、横向移动和未经授权的存取。如今,企业正在优先部署 ITDR,以加强身分基础设施,并降低代价高昂的资料外洩和违反法规的风险。
全球身分威胁侦测与回应 (ITDR) 市场的成长受到多种因素的推动。远距办公、云端应用和混合 IT 环境的激增扩大了攻击面,增加了基于身分的威胁的风险。因此,企业正在寻求能够提供端到端可视性和自动回应功能的全面 ITDR 解决方案。围绕资料隐私的监管压力,例如 GDPR、CCPA 以及不断发展的网路安全法律,进一步加剧了对主动身分威胁侦测的需求。此外,ITDR 解决方案越来越多地与现有安全框架(例如零信任架构和安全资讯与事件管理 (SIEM) 平台)集成,从而增强了其市场相关性。
受人工智慧、机器学习和身分分析技术进步的推动,全球身分威胁侦测与回应 (ITDR) 市场预计将实现强劲成长。各行各业的企业,尤其是金融服务、医疗保健和关键基础设施,都可能将 ITDR 工具纳入其更广泛的网路安全策略。以身分为中心的安全方法的兴起将使 ITDR 成为寻求自适应防御机制的企业的关键投资领域。此外,ITDR 供应商与云端服务供应商之间的合作预计将增强产品创新和市场拓展,使 ITDR 成为未来几年企业网路安全韧性的核心支柱。
基于身分的网路威胁和凭证窃盗增多
与市场上现有安全基础设施的整合复杂性
ITDR 中人工智慧和机器学习的应用日益增多
The Global Identity Threat Detection and Response (ITDR) Market was valued at USD 13.02 Billion in 2024 and is expected to reach USD 42.72 Billion by 2030 with a CAGR of 21.90% through 2030. The Global Identity Threat Detection and Response (ITDR) Market refers to the segment of cybersecurity solutions focused on detecting, monitoring, and mitigating identity-related threats across digital ecosystems.
Market Overview | |
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Forecast Period | 2026-2030 |
Market Size 2024 | USD 13.02 Billion |
Market Size 2030 | USD 42.72 Billion |
CAGR 2025-2030 | 21.90% |
Fastest Growing Segment | IT & ITES |
Largest Market | North America |
Unlike traditional identity and access management systems, ITDR solutions proactively monitor identity activities, detect anomalies, and respond to malicious attempts in real-time. These solutions help protect against credential theft, privilege escalation, lateral movement, and unauthorized access by leveraging advanced analytics, behavioral biometrics, and artificial intelligence-driven insights. Enterprises today are prioritizing ITDR deployments to strengthen identity infrastructure and reduce the risk of costly data breaches and regulatory non-compliance.
The growth of the Global Identity Threat Detection and Response (ITDR) Market is being fueled by several factors. The surge in remote work, cloud adoption, and hybrid IT environments has expanded the attack surface, increasing the risk of identity-based threats. As a result, organizations are seeking comprehensive ITDR solutions that can provide end-to-end visibility and automated response capabilities. Regulatory pressures surrounding data privacy, such as GDPR, CCPA, and evolving cybersecurity laws, have further heightened the demand for proactive identity threat detection. Moreover, ITDR solutions are increasingly integrated with existing security frameworks, such as Zero Trust architecture and Security Information and Event Management (SIEM) platforms, enhancing their market relevance.
The Global Identity Threat Detection and Response (ITDR) Market is expected to see robust growth driven by advancements in artificial intelligence, machine learning, and identity analytics. Enterprises across sectors-especially financial services, healthcare, and critical infrastructure-are likely to adopt ITDR tools as part of their broader cybersecurity strategies. The rise of identity-centric security approaches will make ITDR a key investment area for enterprises seeking adaptive defense mechanisms. Additionally, partnerships between ITDR providers and cloud service vendors are expected to enhance product innovation and market expansion, positioning ITDR as a core pillar of enterprise cybersecurity resilience in the coming years.
Key Market Drivers
Rise in Identity-Based Cyber Threats and Credential Theft
The Global Identity Threat Detection and Response (ITDR) Market is strongly driven by the escalating frequency of identity-based cyber threats and credential theft. Cyber attackers increasingly exploit compromised credentials to bypass traditional security perimeters, gain unauthorized access, and carry out malicious activities like data exfiltration, privilege escalation, and ransomware deployment. Unlike conventional malware attacks, these identity-centric attacks operate silently, often going undetected for extended periods, leading to severe operational and financial impacts on enterprises. In 2024, identity-related cyber incidents accounted for nearly 50% of global reported security breaches, as documented by corporate cybersecurity incident disclosures and threat analysis reports. This sharp increase in credential theft and misuse highlights the critical role of identity-based vulnerabilities in modern cyberattacks, significantly driving the demand for identity threat detection and response solutions worldwide.
With digital transformation accelerating across sectors, enterprises are handling massive volumes of user identities, both human and machine. This expansion amplifies the attack surface and makes robust identity threat detection and response tools indispensable. Organizations are now prioritizing solutions that offer real-time monitoring of user behaviors, anomaly detection, and automated remediation. As identity threats become the preferred attack vector for cybercriminals, demand for specialized ITDR solutions is poised to grow significantly.
Key Market Challenges
Integration Complexities with Existing Security Infrastructure in the Market
The integration of identity threat detection and response solutions with existing security infrastructure remains one of the most significant challenges facing the Global Identity Threat Detection and Response (ITDR) Market. Organizations typically operate complex ecosystems of legacy systems, various security tools, identity and access management platforms, and data protection solutions. Integrating advanced identity threat detection and response platforms into these heterogeneous environments often requires extensive customization, middleware deployment, and infrastructure overhauls. This complexity not only extends implementation timelines but also escalates costs and demands skilled cybersecurity professionals with specialized knowledge of both existing and new systems. Furthermore, seamless data flow, interoperability, and consistent security policy enforcement across multiple platforms become increasingly difficult to manage, especially for large multinational enterprises operating in highly regulated sectors such as finance, healthcare, and government services.
This integration challenge is further compounded by the rapid evolution of digital transformation initiatives across industries. As organizations migrate to hybrid cloud environments and adopt multi-cloud strategies, identity threat detection and response platforms must adapt to secure identities across on-premises, cloud, and edge computing infrastructures. However, achieving this level of seamless integration without disrupting existing workflows or compromising security performance is highly complex. Enterprises often face technical bottlenecks, fragmented visibility, and operational silos, which diminish the effectiveness of identity threat detection and response solutions. Additionally, failure to align identity threat detection systems with broader security information and event management (SIEM) frameworks or extended detection and response (XDR) platforms may result in security gaps, rendering organizations vulnerable to sophisticated identity-based attacks. Therefore, the integration barrier remains a critical restraint on the widespread adoption and operational effectiveness of solutions within the Global Identity Threat Detection and Response (ITDR) Market.
Key Market Trends
Increasing Adoption of Artificial Intelligence and Machine Learning in ITDR
The Global Identity Threat Detection and Response (ITDR) Market is witnessing a rapid integration of artificial intelligence and machine learning technologies to enhance threat detection capabilities. Organizations are leveraging AI-driven behavioral analytics and anomaly detection to identify unusual access patterns and potential identity-based breaches in real-time. These technologies enable automated threat hunting, predictive analysis, and faster incident response, reducing the dependency on manual processes. Machine learning algorithms continuously evolve by analyzing large volumes of identity and access data, improving accuracy and minimizing false positives. This intelligent automation helps enterprises stay ahead of increasingly sophisticated identity threats and reduces operational strain on cybersecurity teams.
AI and machine learning facilitate adaptive security models that dynamically adjust access privileges based on contextual risk factors such as device type, location, and user behavior. This proactive approach significantly enhances the effectiveness of identity threat detection and response frameworks by preventing unauthorized access before damage occurs. The integration of AI into ITDR solutions also accelerates compliance with data protection regulations by providing detailed audit trails and risk scoring. As a result, AI and machine learning adoption is a defining trend shaping the future of the Global Identity Threat Detection and Response (ITDR) Market, driving innovation and efficiency in identity security management.
In this report, the Global Identity Threat Detection and Response (ITDR) Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Identity Threat Detection and Response (ITDR) Market.
Global Identity Threat Detection and Response (ITDR) Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: