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Anomaly Detection Market by Component (Services, Solutions), Technology (Big Data Analytics, Data Mining & Business Intelligence, Machine Learning & Artificial Intelligence), Deployment Type, Vertical - Global Forecast 2025-2030

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Porter's Five Forces : ÀÌ»ó ŽÁö ½ÃÀåÀ» Ž»öÇÏ´Â Àü·« µµ±¸

Portre's Five Forces ÇÁ·¹ÀÓ¿öÅ©´Â ÀÌ»ó ŽÁö ½ÃÀå °æÀï ±¸µµ¸¦ ÀÌÇØÇϱâ À§ÇÑ Áß¿äÇÑ µµ±¸ÀÔ´Ï´Ù. Portre's Five Forces ÇÁ·¹ÀÓ¿öÅ©´Â ±â¾÷ÀÇ °æÀï·ÂÀ» Æò°¡Çϰí Àü·«Àû ±âȸ¸¦ ã±â À§ÇÑ ¸íÈ®ÇÑ ±â¹ýÀ» Á¦°øÇÕ´Ï´Ù. ÀÌ ÇÁ·¹ÀÓ¿öÅ©´Â ±â¾÷ÀÌ ½ÃÀå ³» ÆÇµµ¸¦ Æò°¡ÇÏ°í ½Å±Ô »ç¾÷ÀÇ ¼öÀͼºÀ» ÆÇ´ÜÇÏ´Â µ¥ µµ¿òÀÌ µË´Ï´Ù. ÀÌ·¯ÇÑ ÅëÂû·ÂÀ» ÅëÇØ ±â¾÷Àº ÀÚ»çÀÇ °­Á¡À» Ȱ¿ëÇϰí, ¾àÁ¡¿¡ ´ëóÇϸç, ÀáÀçÀûÀÎ °úÁ¦¸¦ ȸÇÇÇÒ ¼ö ÀÖÀ¸¸ç, º¸´Ù °­ÀÎÇÑ ½ÃÀå¿¡¼­ÀÇ Æ÷Áö¼Å´×À» È®º¸ÇÒ ¼ö ÀÖ½À´Ï´Ù.

PESTLE ºÐ¼® : ÀÌ»ó ŽÁö ½ÃÀå¿¡¼­ ¿ÜºÎ·ÎºÎÅÍÀÇ ¿µÇâ ÆÄ¾Ç

¿ÜºÎ °Å½Ã ȯ°æ ¿äÀÎÀº ÀÌ»ó ŽÁö ½ÃÀåÀÇ ¼º°ú ¿ªÇÐÀ» Çü¼ºÇÏ´Â µ¥ ¸Å¿ì Áß¿äÇÑ ¿ªÇÒÀ» ÇÕ´Ï´Ù. Á¤Ä¡Àû, °æÁ¦Àû, »çȸÀû, ±â¼úÀû, ¹ýÀû, ȯ°æÀû ¿äÀÎÀÇ ºÐ¼®Àº ÀÌ·¯ÇÑ ¿µÇâÀ» Ž»öÇÏ´Â µ¥ ÇÊ¿äÇÑ Á¤º¸¸¦ Á¦°øÇÕ´Ï´Ù. PESTLE ¿äÀÎÀ» Á¶»çÇÔÀ¸·Î½á ±â¾÷Àº ÀáÀçÀûÀÎ À§Çè°ú ±âȸ¸¦ ´õ Àß ÀÌÇØÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ ºÐ¼®À» ÅëÇØ ±â¾÷Àº ±ÔÁ¦, ¼ÒºñÀÚ ±âÈ£, °æÁ¦ µ¿ÇâÀÇ º¯È­¸¦ ¿¹ÃøÇÏ°í ¾ÕÀ» ³»´Ùº» Àû±ØÀûÀÎ ÀÇ»ç°áÁ¤À» ÇÒ Áغñ¸¦ ÇÒ ¼ö ÀÖ½À´Ï´Ù.

½ÃÀå Á¡À¯À² ºÐ¼® : ÀÌ»ó ŽÁö ½ÃÀå °æÀï ±¸µµ ÆÄ¾Ç

ÀÌ»ó ŽÁö ½ÃÀåÀÇ »ó¼¼ÇÑ ½ÃÀå Á¡À¯À² ºÐ¼®À» ÅëÇØ °ø±Þ¾÷üÀÇ ¼º°ú¸¦ Á¾ÇÕÀûÀ¸·Î Æò°¡ÇÒ ¼ö ÀÖ½À´Ï´Ù. ±â¾÷Àº ¼öÀÍ, °í°´ ±â¹Ý, ¼ºÀå·ü µîÀÇ ÁÖ¿ä ÁöÇ¥¸¦ ºñ±³ÇÔÀ¸·Î½á °æÀï»óÀÇ Æ÷Áö¼Å´×À» ¹àÈú ¼ö ÀÖ½À´Ï´Ù. ÀÌ ºÐ¼®¿¡ ÀÇÇØ ½ÃÀåÀÇ ÁýÁß, ´ÜÆíÈ­, ÅëÇÕÀÇ µ¿ÇâÀÌ ¹àÇôÁ® º¥´õ´Â °æÀïÀÌ °ÝÈ­µÇ´Â °¡¿îµ¥ ÀÚ»çÀÇ ÁöÀ§¸¦ ³ôÀÌ´Â Àü·«Àû ÀÇ»ç°áÁ¤À» ½Ç½ÃÇϱâ À§ÇØ ÇÊ¿äÇÑ Áö°ßÀ» ¾òÀ» ¼ö ÀÖ½À´Ï´Ù.

FPNV Æ÷Áö¼Å´× ¸ÅÆ®¸¯½º : ÀÌ»ó ŽÁö ½ÃÀå¿¡¼­ °ø±Þ¾÷üÀÇ ¼º´É Æò°¡

FPNV Æ÷Áö¼Å´× ¸ÅÆ®¸¯½º´Â ÀÌ»ó ŽÁö ½ÃÀå¿¡¼­ º¥´õ¸¦ Æò°¡ÇÏ´Â Áß¿äÇÑ µµ±¸ÀÔ´Ï´Ù. ÀÌ ¸ÅÆ®¸¯½º¸¦ ÅëÇØ ºñÁî´Ï½º Á¶Á÷Àº º¥´õÀÇ ºñÁî´Ï½º Àü·«°ú Á¦Ç° ¸¸Á·µµ¸¦ ¹ÙÅÁÀ¸·Î Æò°¡ÇÔÀ¸·Î½á ¸ñÇ¥¿¡ µû¸¥ ÃæºÐÇÑ Á¤º¸¸¦ ¹ÙÅÁÀ¸·Î ÀÇ»ç°áÁ¤À» ÇÒ ¼ö ÀÖ½À´Ï´Ù. 4°³ÀÇ »çºÐ¸éÀ» ÅëÇØ º¥´õ¸¦ ¸íÈ®Çϰí Á¤È®ÇÏ°Ô ¼¼±×¸ÕƮȭÇϰí, Àü·« ¸ñÇ¥¿¡ ÃÖÀûÀÎ ÆÄÆ®³Ê³ª ¼Ö·ç¼ÇÀ» ƯÁ¤ÇÒ ¼ö ÀÖ½À´Ï´Ù.

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ÀÌ»ó ŽÁö ½ÃÀåÀÇ Àü·« ºÐ¼®Àº ¼¼°è ½ÃÀå¿¡¼­ÀÇ ÇöÀå °­È­¸¦ ¸ñÇ¥·Î ÇÏ´Â ±â¾÷¿¡ ÇʼöÀûÀÔ´Ï´Ù. ÁÖ¿ä ÀÚ¿ø, ´É·Â, ½ÇÀû ÁöÇ¥¸¦ °ËÅäÇÔÀ¸·Î½á ±â¾÷Àº ¼ºÀå ±âȸ¸¦ ƯÁ¤ÇÏ°í °³¼±¿¡ ÀÓÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ Á¢±Ù ¹æ½ÄÀ» ÅëÇØ °æÀï Á¤¼¼ÀÇ °úÁ¦¸¦ ±Øº¹ÇÏ°í »õ·Î¿î ºñÁî´Ï½º ±âȸ¸¦ Ȱ¿ëÇÏ¿© Àå±âÀûÀÎ ¼º°øÀ» °ÅµÎ±â À§ÇÑ Ã¼Á¦¸¦ °®Ãâ ¼ö ÀÖ½À´Ï´Ù.

ÀÌ º¸°í¼­´Â ÁÖ¿ä °ü½É ºÐ¾ß¸¦ Æ÷°ýÇÏ´Â ½ÃÀåÀÇ Á¾ÇÕÀûÀÎ ºÐ¼®À» Á¦°øÇÕ´Ï´Ù.

1. ½ÃÀå ħÅõ : ÇöÀç ½ÃÀå ȯ°æÀÇ »ó¼¼ÇÑ °ËÅä, ÁÖ¿ä ±â¾÷ÀÇ ±¤¹üÀ§ÇÑ µ¥ÀÌÅÍ, ½ÃÀå µµ´Þ¹üÀ§ ¹× Àü¹ÝÀûÀÎ ¿µÇâ·ÂÀ» Æò°¡ÇÕ´Ï´Ù.

2. ½ÃÀå °³Ã´µµ : ½ÅÈï ½ÃÀåÀÇ ¼ºÀå ±âȸ¸¦ ÆÄ¾ÇÇÏ°í ±âÁ¸ ºÐ¾ßÀÇ È®Àå °¡´É¼ºÀ» Æò°¡ÇÏ¸ç ¹Ì·¡ ¼ºÀåÀ» À§ÇÑ Àü·«Àû ·Îµå¸ÊÀ» Á¦°øÇÕ´Ï´Ù.

3. ½ÃÀå ´Ù¾çÈ­ : ÃÖ±Ù Á¦Ç° Ãâ½Ã, ¹Ì°³Ã´ Áö¿ª, ¾÷°èÀÇ ÁÖ¿ä Áøº¸, ½ÃÀåÀ» Çü¼ºÇÏ´Â Àü·«Àû ÅõÀÚ¸¦ ºÐ¼®ÇÕ´Ï´Ù.

4. °æÀï Æò°¡ ¹× Á¤º¸ : °æÀï ±¸µµ¸¦ öÀúÈ÷ ºÐ¼®ÇÏ¿© ½ÃÀå Á¡À¯À², »ç¾÷ Àü·«, Á¦Ç° Æ÷Æ®Æú¸®¿À, ÀÎÁõ, ±ÔÁ¦ ´ç±¹ ½ÂÀÎ, ƯÇã µ¿Çâ, ÁÖ¿ä ±â¾÷ÀÇ ±â¼ú Áøº¸ µîÀ» °ËÁõÇÕ´Ï´Ù.

5. Á¦Ç° °³¹ß ¹× Çõ½Å : ¹Ì·¡ ½ÃÀå ¼ºÀåÀ» °¡¼ÓÇÒ °ÍÀ¸·Î ¿¹»óµÇ´Â ÃÖ÷´Ü ±â¼ú, ¿¬±¸°³¹ß Ȱµ¿, Á¦Ç° Çõ½ÅÀ» °­Á¶ÇÕ´Ï´Ù.

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4. ÁÖ¿ä º¥´õÀÇ ½ÃÀå Á¡À¯À² ¹× °æÀï Æ÷Áö¼ÇÀº?

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  • Accenture PLC
  • Anodot Ltd.
  • Aqueduct Technologies, Inc.
  • Cisco Systems, Inc.
  • Cynet
  • Dell Technologies Inc.
  • General Vision Inc.
  • GreyCortex sro
  • Gurucul
  • Happiest Minds Technologies Pvt. Ltd.
  • Hewlett Packard Enterprise Company
  • International Business Machines Corporation
  • LogRhythm, Inc.
  • Progress Software Corporation
  • Rapid7, Inc.
AJY 24.12.13

The Anomaly Detection Market was valued at USD 3.92 billion in 2023, expected to reach USD 4.28 billion in 2024, and is projected to grow at a CAGR of 9.74%, to USD 7.52 billion by 2030.

Anomaly detection refers to identifying rare items, events, or observations that diverge significantly from the majority of the data. It plays a crucial role in sectors like IT, finance, healthcare, and security by detecting outliers that may indicate critical situations requiring immediate attention. The necessity of anomaly detection lies in its ability to identify potential threats, operational bottlenecks, or opportunities by indicating deviations such as fraudulent transactions, network breaches, or equipment failures. Quickly expanding applications in predictive maintenance, fraud detection, and network security have increased the end-use scope. Influencing growth factors include the rise in data-driven decision-making, adoption of AI and machine learning, and increasing complexity of operational environments demanding proactive assessment tools. Latest potential opportunities include integration with IoT technologies and advancing AI capabilities, which can enhance accuracy and real-time data analysis.

KEY MARKET STATISTICS
Base Year [2023] USD 3.92 billion
Estimated Year [2024] USD 4.28 billion
Forecast Year [2030] USD 7.52 billion
CAGR (%) 9.74%

However, limitations such as handling high-dimensional data, managing false positives, and scalability present challenges. Moreover, continuous evolution in data patterns and sophisticated threats can complicate model development and maintenance. Thus, staying updated with advanced algorithms and computational resources is vital. Innovation and research opportunities are abundant, particularly in enhancing algorithm efficiency, reducing computational costs, and improving user interfaces for easier anomaly visualization. Furthermore, developing domain-specific models may provide significant insights for businesses, enhancing targeted deployment in various sectors. Nature of the market indicates a high growth trajectory fueled by digital transformation and increased awareness about business intelligence tools. Investing in collaborative platforms involving both tech and domain experts can accelerate innovation. Companies must strategically leverage partnerships and invest in R&D to tailor solutions to emerging use cases and complex market dynamics while navigating the regulatory environment.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Anomaly Detection Market

The Anomaly Detection Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

  • Market Drivers
    • Proliferation in the number of connected devices coupled rise in the fraudulent activities and cyber-attacks
    • Growing adoption of anomaly detection solutions in software testing
  • Market Restraints
    • High cost of anomaly detection tools
  • Market Opportunities
    • Development of technologies such as big data analytics, machine learning, artificial intelligence
    • Presence of major sustainable economies investing constantly in R&D activities
  • Market Challenges
    • Availability of open-source alternatives

Porter's Five Forces: A Strategic Tool for Navigating the Anomaly Detection Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Anomaly Detection Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Anomaly Detection Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Anomaly Detection Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Anomaly Detection Market

A detailed market share analysis in the Anomaly Detection Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Anomaly Detection Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Anomaly Detection Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the Anomaly Detection Market

A strategic analysis of the Anomaly Detection Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the Anomaly Detection Market, highlighting leading vendors and their innovative profiles. These include Accenture PLC, Anodot Ltd., Aqueduct Technologies, Inc., Cisco Systems, Inc., Cynet, Dell Technologies Inc., General Vision Inc., GreyCortex s.r.o., Gurucul, Happiest Minds Technologies Pvt. Ltd., Hewlett Packard Enterprise Company, International Business Machines Corporation, LogRhythm, Inc., Progress Software Corporation, and Rapid7, Inc..

Market Segmentation & Coverage

This research report categorizes the Anomaly Detection Market to forecast the revenues and analyze trends in each of the following sub-markets:

  • Based on Component, market is studied across Services and Solutions. The Services is further studied across Managed Services and Professional Services. The Solutions is further studied across Network Behavior Anomaly Detection and User Behavior Anomaly Detection. The Network Behavior Anomaly Detection is further studied across Network Intelligence & Security, Network Traffic Analysis, and Risk Mitigation & Management. The User Behavior Anomaly Detection is further studied across Data Loss Prevention, Identity & Access Management, Security Information & Event Management, and Threat Intelligence & Management.
  • Based on Technology, market is studied across Big Data Analytics, Data Mining & Business Intelligence, and Machine Learning & Artificial Intelligence.
  • Based on Deployment Type, market is studied across Cloud and On-Premises.
  • Based on Vertical, market is studied across Banking, Financial Services, & Insurance, Defense & Government, Healthcare, Information Technology & Telecom, and Retail & Manufacturing.
  • Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Proliferation in the number of connected devices coupled rise in the fraudulent activities and cyber-attacks
      • 5.1.1.2. Growing adoption of anomaly detection solutions in software testing
    • 5.1.2. Restraints
      • 5.1.2.1. High cost of anomaly detection tools
    • 5.1.3. Opportunities
      • 5.1.3.1. Development of technologies such as big data analytics, machine learning, artificial intelligence
      • 5.1.3.2. Presence of major sustainable economies investing constantly in R&D activities
    • 5.1.4. Challenges
      • 5.1.4.1. Availability of open-source alternatives
  • 5.2. Market Segmentation Analysis
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. Anomaly Detection Market, by Component

  • 6.1. Introduction
  • 6.2. Services
    • 6.2.1. Managed Services
    • 6.2.2. Professional Services
  • 6.3. Solutions
    • 6.3.1. Network Behavior Anomaly Detection
      • 6.3.1.1. Network Intelligence & Security
      • 6.3.1.2. Network Traffic Analysis
      • 6.3.1.3. Risk Mitigation & Management
    • 6.3.2. User Behavior Anomaly Detection
      • 6.3.2.1. Data Loss Prevention
      • 6.3.2.2. Identity & Access Management
      • 6.3.2.3. Security Information & Event Management
      • 6.3.2.4. Threat Intelligence & Management

7. Anomaly Detection Market, by Technology

  • 7.1. Introduction
  • 7.2. Big Data Analytics
  • 7.3. Data Mining & Business Intelligence
  • 7.4. Machine Learning & Artificial Intelligence

8. Anomaly Detection Market, by Deployment Type

  • 8.1. Introduction
  • 8.2. Cloud
  • 8.3. On-Premises

9. Anomaly Detection Market, by Vertical

  • 9.1. Introduction
  • 9.2. Banking, Financial Services, & Insurance
  • 9.3. Defense & Government
  • 9.4. Healthcare
  • 9.5. Information Technology & Telecom
  • 9.6. Retail & Manufacturing

10. Americas Anomaly Detection Market

  • 10.1. Introduction
  • 10.2. Argentina
  • 10.3. Brazil
  • 10.4. Canada
  • 10.5. Mexico
  • 10.6. United States

11. Asia-Pacific Anomaly Detection Market

  • 11.1. Introduction
  • 11.2. Australia
  • 11.3. China
  • 11.4. India
  • 11.5. Indonesia
  • 11.6. Japan
  • 11.7. Malaysia
  • 11.8. Philippines
  • 11.9. Singapore
  • 11.10. South Korea
  • 11.11. Taiwan
  • 11.12. Thailand
  • 11.13. Vietnam

12. Europe, Middle East & Africa Anomaly Detection Market

  • 12.1. Introduction
  • 12.2. Denmark
  • 12.3. Egypt
  • 12.4. Finland
  • 12.5. France
  • 12.6. Germany
  • 12.7. Israel
  • 12.8. Italy
  • 12.9. Netherlands
  • 12.10. Nigeria
  • 12.11. Norway
  • 12.12. Poland
  • 12.13. Qatar
  • 12.14. Russia
  • 12.15. Saudi Arabia
  • 12.16. South Africa
  • 12.17. Spain
  • 12.18. Sweden
  • 12.19. Switzerland
  • 12.20. Turkey
  • 12.21. United Arab Emirates
  • 12.22. United Kingdom

13. Competitive Landscape

  • 13.1. Market Share Analysis, 2023
  • 13.2. FPNV Positioning Matrix, 2023
  • 13.3. Competitive Scenario Analysis
  • 13.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. Accenture PLC
  • 2. Anodot Ltd.
  • 3. Aqueduct Technologies, Inc.
  • 4. Cisco Systems, Inc.
  • 5. Cynet
  • 6. Dell Technologies Inc.
  • 7. General Vision Inc.
  • 8. GreyCortex s.r.o.
  • 9. Gurucul
  • 10. Happiest Minds Technologies Pvt. Ltd.
  • 11. Hewlett Packard Enterprise Company
  • 12. International Business Machines Corporation
  • 13. LogRhythm, Inc.
  • 14. Progress Software Corporation
  • 15. Rapid7, Inc.
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