Cloud IDS IPS Market by Component (Services, Solution), Organization Size (Large Enterprises, Small And Medium Enterprises), End User, Deployment Mode - Global Forecast 2025-2032
Description
The Cloud IDS IPS Market was valued at USD 2.77 billion in 2024 and is projected to grow to USD 3.40 billion in 2025, with a CAGR of 23.30%, reaching USD 14.83 billion by 2032.
A concise strategic introduction explaining why modern intrusion detection and prevention capabilities are essential to secure hybrid and cloud-native application estates against evolving threats
The acceleration of cloud-native architectures and the persistent sophistication of adversaries have elevated intrusion detection and prevention systems from a defensive convenience to a strategic imperative. Organizations now must reconcile legacy perimeter defenses with cloud-native, containerized, and distributed application environments while preserving performance and minimizing false positives. This introduction outlines the operational and strategic drivers compelling security and risk leaders to reassess how IDS and IPS capabilities are selected, integrated, and governed.
Across industry verticals, the priorities have shifted toward real-time visibility across multi-cloud estates, automated threat prioritization, and seamless integration with orchestration and incident response workflows. Security teams are increasingly measured by their ability to detect complex attack patterns that traverse host and network layers, to enforce policies continuously, and to do so without impeding developer velocity. As a result, the evaluation lens now spans technical efficacy, deployment flexibility, and the maturity of vendor support models. This section sets the stage for a deeper analysis of technological shifts, segmentation dynamics, and practical recommendations for leaders aiming to harmonize detection, prevention, and operational resiliency.
An in-depth analysis of the transformative technological and operational shifts that are redefining detection, prevention, and orchestration across cloud, hybrid, and multi-environment security infrastructures
The landscape for intrusion detection and prevention is being reshaped by several convergent forces that are transforming how security controls are designed, delivered, and consumed. First, the shift to cloud-native development patterns - including microservices, containers, and serverless functions - demands detection controls that operate at the application and orchestration layers while maintaining minimal latency. This transition has prompted vendors to embed IDS and IPS functions directly into platform toolchains and to provide APIs for orchestration-driven enforcement.
Second, the adoption of zero trust principles and identity-centric controls is reframing where and how preventive controls are applied. Rather than relying solely on network perimeters, organizations now need granular telemetry and policy enforcement tied to identities, workloads, and runtime contexts. Third, the maturation of machine learning and behavioral analytics is enabling anomaly detection that can surface novel attack techniques, although these models require careful tuning and explainability to reduce operational friction. Fourth, the continued growth of encrypted traffic and complex application protocols increases the need for visibility techniques that respect privacy and compliance constraints while still enabling effective inspection. Finally, market dynamics around managed detection and response and cloud provider-native security offerings are shifting buyer preferences toward integrated security stacks and consumption models that emphasize ongoing operational support over point-product procurement. Together, these shifts are creating an environment in which interoperability, automation, and risk-based prioritization determine long-term value.
A focused evaluation of how recent United States tariff measures in 2025 have reshaped procurement decisions, vendor pricing strategies, and the broader shift toward software-first security consumption models
Recent tariff adjustments in the United States for 2025 have created cascading effects across procurement, supply chain management, and vendor strategy within the cybersecurity ecosystem. Elevated import levies on certain hardware components and networking equipment have sharpened focus on total cost of ownership and accelerated the transition toward software-centric and cloud-delivered security functions. Organizations with heavy on-premises footprints have confronted higher acquisition costs, prompting procurement teams to reassess refresh cycles, negotiate revised vendor terms, and explore second-source options to mitigate supply-chain exposure.
Vendors responded by increasing the emphasis on subscription models, offering virtualized or appliance-less deployment options, and accelerating partnerships with cloud service providers to preserve price competitiveness. These commercial adjustments have been accompanied by strategic product shifts; some vendors prioritized software adaptation that reduces dependency on tariff-affected hardware, while others expanded managed service offerings to offset capital expense spikes for customers. In addition, procurement timelines lengthened in sectors with stringent compliance or budgetary oversight, as stakeholders undertook scenario planning to understand long-term operational impacts. The cumulative outcome is a tangible reorientation toward flexible consumption models, deeper vendor-client commercial collaboration, and heightened scrutiny of supply chain resilience when evaluating IDS and IPS solutions.
Comprehensive segmentation insights that reveal how deployment mode, component architecture, end-user industry needs, and organizational scale shape IDS and IPS evaluation and procurement choices
Understanding segmentation dynamics illuminates how deployment preferences, component composition, end-user needs, and organizational scale drive divergent requirements for detection and prevention solutions. Deployment mode distinctions between cloud and on-premises environments are fundamental; cloud deployments bring expectations for rapid scalability and native integrations, while on-premises environments prioritize control and low-latency inspection. Within cloud environments there is further differentiation among hybrid models that blend on-premises control with cloud elasticity, private cloud deployments that emphasize isolation and bespoke policy controls, and public cloud environments that prioritize API-driven automation and provider-native integrations.
Component-level segmentation similarly influences buyer evaluation. Solutions that provide host-based capabilities address workload telemetry and kernel-level enforcement, whereas network-based solutions focus on east-west and north-south traffic inspection; within network approaches, anomaly-based detection emphasizes behavior and deviations while signature-based detection relies on known indicators of compromise. Services augment solutions in distinct ways: managed services deliver continuous operational oversight and threat hunting capabilities, while professional services support deployment, tuning, and incident response readiness. End-user verticals present discrete risk profiles and regulatory requirements; financial services and insurance demand high assurance and low false positives, government buyers prioritize auditability and sovereign controls, healthcare organizations require patient-data privacy and compliance alignment, IT and telecom sectors demand high-throughput and low-latency inspection, and retail operations emphasize point-of-sale and e-commerce transaction security. Organizational size further refines requirements: large enterprises typically invest in bespoke integration, in-house SOC capabilities, and hybrid architectures, while small and medium enterprises often prioritize turnkey cloud-delivered protections and managed service options to compensate for constrained security operations resources.
When these segmentation dimensions are considered together, they create a matrix of prioritized capabilities that inform architecture choices, vendor selection criteria, and operational commitments for implementation and lifecycle maintenance.
Key regional insights into how the Americas, Europe, Middle East & Africa, and Asia-Pacific each influence regulatory priorities, deployment preferences, and vendor engagement models for IDS and IPS
Regional dynamics materially influence how intrusion detection and prevention solutions are deployed, regulated, and supported. In the Americas, particularly in North America, there is strong adoption of cloud-native security products and a pronounced appetite for managed detection services; buyers in this region often prioritize innovation velocity, deep integrations with major cloud providers, and robust threat intelligence sharing. Commercial procurement in the Americas tends to favor flexible contracting and a willingness to pilot emerging technologies, which accelerates vendor roadmaps and operational maturity.
Europe, Middle East & Africa present a heterogenous landscape with diverse regulatory frameworks and interoperability challenges. Data protection regulations and national sovereignty concerns increase demand for private deployments, strong data residency guarantees, and demonstrable compliance controls. Buyers in this region also place a premium on explainable detection models and vendor transparency, as procurement committees must balance security efficacy with legal and privacy obligations. Managed services and regional partnerships are common routes to bridge capability gaps while ensuring compliance.
Asia-Pacific combines rapid cloud adoption with varying maturity across markets. Leading markets in this region show high uptake of automated and AI-augmented detection tools, often influenced by growth in digital services and telecom modernization. However, supply-chain considerations and localization requirements mean that some customers prefer hybrid or private deployments. Across the region, channel ecosystems and local integrators play a pivotal role in tailoring solutions to language, regulatory, and operational contexts, making ecosystem partnerships a critical factor for vendor success.
A strategic overview of vendor dynamics, partnership ecosystems, and services-led differentiation that drive competitive advantage in detection and prevention platforms
Competitive dynamics among leading vendors reflect a balance between platform integration, specialization, and services-led differentiation. Many companies are broadening their portfolios to offer combined detection and prevention capabilities that span host and network telemetry, while simultaneously investing in APIs and connectors to ensure interoperability with cloud providers and orchestration platforms. Strategic partnerships with hyperscalers and SIEM or SOAR vendors have become essential to provide end-to-end detection-to-response workflows and to embed intelligence into continuous protection pipelines.
At the same time, a cohort of specialized vendors continues to differentiate through deep technical competencies, such as kernel-level host visibility, high-fidelity anomaly detection, or low-latency inline prevention. These specialists often target complex environments where precision and performance are non-negotiable. Services-led companies and managed service providers have expanded their offerings to include threat hunting, continuous tuning, and compliance reporting, enabling clients with limited SOC capacity to achieve near-enterprise levels of protection. Consolidation activity and strategic investment in R&D are enabling firms to accelerate feature parity, but meaningful differentiation increasingly depends on the quality of threat intelligence, the maturity of automation playbooks, and the strength of integration ecosystems that reduce operational overhead for security teams.
Actionable, prioritized recommendations for security and IT leaders to accelerate adoption, optimize operations, and reduce risk through targeted architecture, telemetry, and governance changes
Leaders seeking to strengthen detection and prevention postures should prioritize an agenda that balances technical rigor with pragmatic operational change. First, adopt a workload- and identity-centric approach that aligns detection rules and prevention policies to runtime context rather than rigid network zones. This alignment reduces false positives and improves the relevance of alerts while enabling more precise enforcement during lateral movement scenarios. Second, invest in telemetry consolidation and normalization so that host, network, and cloud logs are correlated within a single pane of glass; this reduces mean time to detection and improves investigator efficiency.
Third, favor solutions that offer flexible deployment modes and APIs for orchestration, enabling policies to be enforced consistently across hybrid and multi-cloud environments. Fourth, build a phased adoption plan that pairs technical pilots with measurable operational objectives, such as reduction in alert triage time or improvement in containment speed, and use these metrics to guide scaling decisions. Fifth, where internal SOC capacity is constrained, leverage managed detection and response services or co-managed models to accelerate time to value while retaining oversight. Finally, integrate procurement and legal stakeholders early in vendor evaluations to ensure contract terms, data handling practices, and SLAs align with regulatory and operational requirements, thereby reducing friction during implementation and lifecycle adjustments.
Transparent research methodology describing interview-based evidence, technical validation, vendor evaluation, and data triangulation used to produce practical and verifiable insights for decision-makers
The research methodology integrates qualitative and quantitative approaches to produce robust, validated insights that reflect operational realities. Primary interviews with security leaders, SOC managers, and technical architects provided frontline perspectives on deployment challenges, vendor performance, and integration bottlenecks. These interviews were complemented by structured vendor assessments that evaluated technical architecture, integration capabilities, and service models. Technical validation included hands-on testing of detection efficacy, false positive rates, and performance overhead in representative environments to ensure practical relevance.
Data triangulation techniques were applied to reconcile findings from interviews, technical assessments, and publicly available documentation, producing a coherent view of capability trends and buyer priorities. Scenario analysis helped model implications of supply-chain and regulatory shifts on procurement and deployment strategies. Throughout the process, findings were reviewed with independent practitioners for plausibility checks and to surface alternative interpretations. This mixed-method approach ensures that recommendations are grounded in operational evidence, technical validation, and stakeholder realities.
A concise conclusion synthesizing strategic imperatives for aligning detection and prevention investments with operational resilience, integration priorities, and regulatory realities
The convergence of cloud-native adoption, evolving threat techniques, and shifting commercial conditions requires organizations to reframe how they evaluate intrusion detection and prevention capabilities. Detection and prevention must be assessed not only on technical effectiveness but also on their ability to integrate with orchestration tooling, to scale across hybrid estates, and to minimize operational overhead. Regulatory and procurement pressures further necessitate flexible consumption models and vendor transparency around data handling and supply-chain dependencies.
For security leaders, the path forward involves prioritizing integration-first solutions, strengthening telemetry and context enrichment, and adopting consumption models that match operational maturity. Organizations that combine technical rigor with pragmatic adoption playbooks will be better positioned to reduce dwell time, accelerate incident response, and maintain developer productivity. Ultimately, IDS and IPS investments should be measured by their contribution to risk reduction, operational sustainability, and the ability to support evolving application architectures.
Note: PDF & Excel + Online Access - 1 Year
A concise strategic introduction explaining why modern intrusion detection and prevention capabilities are essential to secure hybrid and cloud-native application estates against evolving threats
The acceleration of cloud-native architectures and the persistent sophistication of adversaries have elevated intrusion detection and prevention systems from a defensive convenience to a strategic imperative. Organizations now must reconcile legacy perimeter defenses with cloud-native, containerized, and distributed application environments while preserving performance and minimizing false positives. This introduction outlines the operational and strategic drivers compelling security and risk leaders to reassess how IDS and IPS capabilities are selected, integrated, and governed.
Across industry verticals, the priorities have shifted toward real-time visibility across multi-cloud estates, automated threat prioritization, and seamless integration with orchestration and incident response workflows. Security teams are increasingly measured by their ability to detect complex attack patterns that traverse host and network layers, to enforce policies continuously, and to do so without impeding developer velocity. As a result, the evaluation lens now spans technical efficacy, deployment flexibility, and the maturity of vendor support models. This section sets the stage for a deeper analysis of technological shifts, segmentation dynamics, and practical recommendations for leaders aiming to harmonize detection, prevention, and operational resiliency.
An in-depth analysis of the transformative technological and operational shifts that are redefining detection, prevention, and orchestration across cloud, hybrid, and multi-environment security infrastructures
The landscape for intrusion detection and prevention is being reshaped by several convergent forces that are transforming how security controls are designed, delivered, and consumed. First, the shift to cloud-native development patterns - including microservices, containers, and serverless functions - demands detection controls that operate at the application and orchestration layers while maintaining minimal latency. This transition has prompted vendors to embed IDS and IPS functions directly into platform toolchains and to provide APIs for orchestration-driven enforcement.
Second, the adoption of zero trust principles and identity-centric controls is reframing where and how preventive controls are applied. Rather than relying solely on network perimeters, organizations now need granular telemetry and policy enforcement tied to identities, workloads, and runtime contexts. Third, the maturation of machine learning and behavioral analytics is enabling anomaly detection that can surface novel attack techniques, although these models require careful tuning and explainability to reduce operational friction. Fourth, the continued growth of encrypted traffic and complex application protocols increases the need for visibility techniques that respect privacy and compliance constraints while still enabling effective inspection. Finally, market dynamics around managed detection and response and cloud provider-native security offerings are shifting buyer preferences toward integrated security stacks and consumption models that emphasize ongoing operational support over point-product procurement. Together, these shifts are creating an environment in which interoperability, automation, and risk-based prioritization determine long-term value.
A focused evaluation of how recent United States tariff measures in 2025 have reshaped procurement decisions, vendor pricing strategies, and the broader shift toward software-first security consumption models
Recent tariff adjustments in the United States for 2025 have created cascading effects across procurement, supply chain management, and vendor strategy within the cybersecurity ecosystem. Elevated import levies on certain hardware components and networking equipment have sharpened focus on total cost of ownership and accelerated the transition toward software-centric and cloud-delivered security functions. Organizations with heavy on-premises footprints have confronted higher acquisition costs, prompting procurement teams to reassess refresh cycles, negotiate revised vendor terms, and explore second-source options to mitigate supply-chain exposure.
Vendors responded by increasing the emphasis on subscription models, offering virtualized or appliance-less deployment options, and accelerating partnerships with cloud service providers to preserve price competitiveness. These commercial adjustments have been accompanied by strategic product shifts; some vendors prioritized software adaptation that reduces dependency on tariff-affected hardware, while others expanded managed service offerings to offset capital expense spikes for customers. In addition, procurement timelines lengthened in sectors with stringent compliance or budgetary oversight, as stakeholders undertook scenario planning to understand long-term operational impacts. The cumulative outcome is a tangible reorientation toward flexible consumption models, deeper vendor-client commercial collaboration, and heightened scrutiny of supply chain resilience when evaluating IDS and IPS solutions.
Comprehensive segmentation insights that reveal how deployment mode, component architecture, end-user industry needs, and organizational scale shape IDS and IPS evaluation and procurement choices
Understanding segmentation dynamics illuminates how deployment preferences, component composition, end-user needs, and organizational scale drive divergent requirements for detection and prevention solutions. Deployment mode distinctions between cloud and on-premises environments are fundamental; cloud deployments bring expectations for rapid scalability and native integrations, while on-premises environments prioritize control and low-latency inspection. Within cloud environments there is further differentiation among hybrid models that blend on-premises control with cloud elasticity, private cloud deployments that emphasize isolation and bespoke policy controls, and public cloud environments that prioritize API-driven automation and provider-native integrations.
Component-level segmentation similarly influences buyer evaluation. Solutions that provide host-based capabilities address workload telemetry and kernel-level enforcement, whereas network-based solutions focus on east-west and north-south traffic inspection; within network approaches, anomaly-based detection emphasizes behavior and deviations while signature-based detection relies on known indicators of compromise. Services augment solutions in distinct ways: managed services deliver continuous operational oversight and threat hunting capabilities, while professional services support deployment, tuning, and incident response readiness. End-user verticals present discrete risk profiles and regulatory requirements; financial services and insurance demand high assurance and low false positives, government buyers prioritize auditability and sovereign controls, healthcare organizations require patient-data privacy and compliance alignment, IT and telecom sectors demand high-throughput and low-latency inspection, and retail operations emphasize point-of-sale and e-commerce transaction security. Organizational size further refines requirements: large enterprises typically invest in bespoke integration, in-house SOC capabilities, and hybrid architectures, while small and medium enterprises often prioritize turnkey cloud-delivered protections and managed service options to compensate for constrained security operations resources.
When these segmentation dimensions are considered together, they create a matrix of prioritized capabilities that inform architecture choices, vendor selection criteria, and operational commitments for implementation and lifecycle maintenance.
Key regional insights into how the Americas, Europe, Middle East & Africa, and Asia-Pacific each influence regulatory priorities, deployment preferences, and vendor engagement models for IDS and IPS
Regional dynamics materially influence how intrusion detection and prevention solutions are deployed, regulated, and supported. In the Americas, particularly in North America, there is strong adoption of cloud-native security products and a pronounced appetite for managed detection services; buyers in this region often prioritize innovation velocity, deep integrations with major cloud providers, and robust threat intelligence sharing. Commercial procurement in the Americas tends to favor flexible contracting and a willingness to pilot emerging technologies, which accelerates vendor roadmaps and operational maturity.
Europe, Middle East & Africa present a heterogenous landscape with diverse regulatory frameworks and interoperability challenges. Data protection regulations and national sovereignty concerns increase demand for private deployments, strong data residency guarantees, and demonstrable compliance controls. Buyers in this region also place a premium on explainable detection models and vendor transparency, as procurement committees must balance security efficacy with legal and privacy obligations. Managed services and regional partnerships are common routes to bridge capability gaps while ensuring compliance.
Asia-Pacific combines rapid cloud adoption with varying maturity across markets. Leading markets in this region show high uptake of automated and AI-augmented detection tools, often influenced by growth in digital services and telecom modernization. However, supply-chain considerations and localization requirements mean that some customers prefer hybrid or private deployments. Across the region, channel ecosystems and local integrators play a pivotal role in tailoring solutions to language, regulatory, and operational contexts, making ecosystem partnerships a critical factor for vendor success.
A strategic overview of vendor dynamics, partnership ecosystems, and services-led differentiation that drive competitive advantage in detection and prevention platforms
Competitive dynamics among leading vendors reflect a balance between platform integration, specialization, and services-led differentiation. Many companies are broadening their portfolios to offer combined detection and prevention capabilities that span host and network telemetry, while simultaneously investing in APIs and connectors to ensure interoperability with cloud providers and orchestration platforms. Strategic partnerships with hyperscalers and SIEM or SOAR vendors have become essential to provide end-to-end detection-to-response workflows and to embed intelligence into continuous protection pipelines.
At the same time, a cohort of specialized vendors continues to differentiate through deep technical competencies, such as kernel-level host visibility, high-fidelity anomaly detection, or low-latency inline prevention. These specialists often target complex environments where precision and performance are non-negotiable. Services-led companies and managed service providers have expanded their offerings to include threat hunting, continuous tuning, and compliance reporting, enabling clients with limited SOC capacity to achieve near-enterprise levels of protection. Consolidation activity and strategic investment in R&D are enabling firms to accelerate feature parity, but meaningful differentiation increasingly depends on the quality of threat intelligence, the maturity of automation playbooks, and the strength of integration ecosystems that reduce operational overhead for security teams.
Actionable, prioritized recommendations for security and IT leaders to accelerate adoption, optimize operations, and reduce risk through targeted architecture, telemetry, and governance changes
Leaders seeking to strengthen detection and prevention postures should prioritize an agenda that balances technical rigor with pragmatic operational change. First, adopt a workload- and identity-centric approach that aligns detection rules and prevention policies to runtime context rather than rigid network zones. This alignment reduces false positives and improves the relevance of alerts while enabling more precise enforcement during lateral movement scenarios. Second, invest in telemetry consolidation and normalization so that host, network, and cloud logs are correlated within a single pane of glass; this reduces mean time to detection and improves investigator efficiency.
Third, favor solutions that offer flexible deployment modes and APIs for orchestration, enabling policies to be enforced consistently across hybrid and multi-cloud environments. Fourth, build a phased adoption plan that pairs technical pilots with measurable operational objectives, such as reduction in alert triage time or improvement in containment speed, and use these metrics to guide scaling decisions. Fifth, where internal SOC capacity is constrained, leverage managed detection and response services or co-managed models to accelerate time to value while retaining oversight. Finally, integrate procurement and legal stakeholders early in vendor evaluations to ensure contract terms, data handling practices, and SLAs align with regulatory and operational requirements, thereby reducing friction during implementation and lifecycle adjustments.
Transparent research methodology describing interview-based evidence, technical validation, vendor evaluation, and data triangulation used to produce practical and verifiable insights for decision-makers
The research methodology integrates qualitative and quantitative approaches to produce robust, validated insights that reflect operational realities. Primary interviews with security leaders, SOC managers, and technical architects provided frontline perspectives on deployment challenges, vendor performance, and integration bottlenecks. These interviews were complemented by structured vendor assessments that evaluated technical architecture, integration capabilities, and service models. Technical validation included hands-on testing of detection efficacy, false positive rates, and performance overhead in representative environments to ensure practical relevance.
Data triangulation techniques were applied to reconcile findings from interviews, technical assessments, and publicly available documentation, producing a coherent view of capability trends and buyer priorities. Scenario analysis helped model implications of supply-chain and regulatory shifts on procurement and deployment strategies. Throughout the process, findings were reviewed with independent practitioners for plausibility checks and to surface alternative interpretations. This mixed-method approach ensures that recommendations are grounded in operational evidence, technical validation, and stakeholder realities.
A concise conclusion synthesizing strategic imperatives for aligning detection and prevention investments with operational resilience, integration priorities, and regulatory realities
The convergence of cloud-native adoption, evolving threat techniques, and shifting commercial conditions requires organizations to reframe how they evaluate intrusion detection and prevention capabilities. Detection and prevention must be assessed not only on technical effectiveness but also on their ability to integrate with orchestration tooling, to scale across hybrid estates, and to minimize operational overhead. Regulatory and procurement pressures further necessitate flexible consumption models and vendor transparency around data handling and supply-chain dependencies.
For security leaders, the path forward involves prioritizing integration-first solutions, strengthening telemetry and context enrichment, and adopting consumption models that match operational maturity. Organizations that combine technical rigor with pragmatic adoption playbooks will be better positioned to reduce dwell time, accelerate incident response, and maintain developer productivity. Ultimately, IDS and IPS investments should be measured by their contribution to risk reduction, operational sustainability, and the ability to support evolving application architectures.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
180 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Integration of machine learning driven analytics for real time threat detection across multi cloud platforms
- 5.2. Adoption of zero trust security frameworks to enhance cloud based intrusion prevention and response capabilities
- 5.3. Deployment of container and Kubernetes native IDS IPS solutions for microservices and dynamic workloads
- 5.4. Consolidation of cloud IDS IPS functionality into unified SASE and secure access service edge architectures
- 5.5. Automated compliance and audit reporting through continuous monitoring of cloud IDS IPS events and logs
- 5.6. API and serverless workload protection integrated with intrusion detection to address modern cloud application threats
- 5.7. Edge computing and IoT device traffic inspection using distributed cloud based IDS IPS services for low latency detection
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Cloud IDS IPS Market, by Component
- 8.1. Services
- 8.1.1. Managed
- 8.1.2. Professional
- 8.2. Solution
- 8.2.1. Host Based
- 8.2.2. Network Based
- 8.2.2.1. Anomaly Based
- 8.2.2.2. Signature Based
- 9. Cloud IDS IPS Market, by Organization Size
- 9.1. Large Enterprises
- 9.2. Small And Medium Enterprises
- 10. Cloud IDS IPS Market, by End User
- 10.1. BFSI
- 10.2. Government
- 10.3. Healthcare
- 10.4. IT And Telecom
- 10.5. Retail
- 11. Cloud IDS IPS Market, by Deployment Mode
- 11.1. Cloud
- 11.1.1. Hybrid
- 11.1.2. Private
- 11.1.3. Public
- 11.2. On-Premises
- 12. Cloud IDS IPS Market, by Region
- 12.1. Americas
- 12.1.1. North America
- 12.1.2. Latin America
- 12.2. Europe, Middle East & Africa
- 12.2.1. Europe
- 12.2.2. Middle East
- 12.2.3. Africa
- 12.3. Asia-Pacific
- 13. Cloud IDS IPS Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
- 14. Cloud IDS IPS Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
- 15. Competitive Landscape
- 15.1. Market Share Analysis, 2024
- 15.2. FPNV Positioning Matrix, 2024
- 15.3. Competitive Analysis
- 15.3.1. Alteryx, Inc.
- 15.3.2. Amazon Web Services, Inc.
- 15.3.3. AT&T Inc.
- 15.3.4. Check Point Software Technologies Ltd.
- 15.3.5. Cisco Systems, Inc.
- 15.3.6. Cloud Carib
- 15.3.7. FireEye, Inc.
- 15.3.8. Fortinet, Inc.
- 15.3.9. Fortra, LLC
- 15.3.10. Google LLC by Alphabet Inc.
- 15.3.11. Hillstone Networks
- 15.3.12. Intel Corporation
- 15.3.13. International Business Machines Corporation
- 15.3.14. Juniper Networks, Inc.
- 15.3.15. Lumen Technologies
- 15.3.16. McAfee LLC
- 15.3.17. Metaflows, Inc.
- 15.3.18. Microsoft Corporation
- 15.3.19. New H3C Technologies Co., Ltd.
- 15.3.20. NTT Global Networks Incorporated
- 15.3.21. Oracle Corporation
- 15.3.22. Palo Alto Networks, Inc.
- 15.3.23. Radware Ltd.
- 15.3.24. Secureworks, Inc.
- 15.3.25. Sophos Ltd.
- 15.3.26. Trellix by Musarubra US LLC
- 15.3.27. Trend Micro Incorporated
- 15.3.28. Vectra AI, Inc.
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