ユーザーおよびエンティティ行動分析（UEBA）市場：タイプ別、展開タイプ別、地域別、2024年～2031年

ユーザーおよびエンティティ行動分析（UEBA）市場の評価、2024年～2031年

巧妙なサイバー攻撃の増加とIT環境の複雑化企業が高度な持続的脅威、ランサムウェア攻撃、内部脅威などに対処する中、UEBAソリューションは、異常や潜在的な侵害を検出するために行動パターンを研究することにより、可視性と洞察力を向上させる。同市場は2024年に10億3,554万米ドルを超え、2031年までに112億1,559万米ドルに達する見通しです。

さらに、人工知能（AI）と機械学習（ML）をUEBAシステムに統合することで、脅威の検出と対応における精度と有効性が高まる。さらに、データ保護とサイバーセキュリティに関する法的要件の増加により、企業は高度なセキュリティ・ソリューションへの投資を余儀なくされ、業界全体のUEBA需要が拡大し、2024年から2031年にかけてCAGR約40.50%で成長する見込みです。

ユーザーおよびエンティティ行動分析（UEBA）市場：定義/概要

UEBA（User and Entity Behavior Analytics）とは、組織の情報技術環境におけるユーザーやエンティティの行動を監視・評価するために、高度な分析と機械学習技術を適用することです。UEBAは、典型的な行動のベースラインを確立し、そこからの逸脱を特定することで、内部脅威、侵害されたアカウント、高度な持続的脅威などの潜在的なセキュリティ脅威の検出を支援します。その用途には、脅威検出の向上、インシデント対応の改善、サイバーセキュリティ態勢の全体的強化などがあります。AIと機械学習の進歩により、より複雑で正確な脅威検出が可能になると予測されており、UEBAの将来は楽観視されています。企業がサイバーセキュリティと規制コンプライアンスを優先する中、UEBAは実用的な洞察を提供し、変化するサイバー脅威から保護する上で重要な役割を果たすと思われます。

AIと機械学習の採用増加はユーザーおよびエンティティ行動分析（UEBA）市場を促進するか？

人工知能（AI）と機械学習（ML）の利用拡大が、ユーザーおよびエンティティ行動分析（UEBA）市場を推進しています。AIと機械学習技術は、大量のデータをより正確かつ効率的に分析できるようにすることで、UEBAソリューションの能力を向上させる。これらの技術により、内部脅威、侵害されたアカウント、高度な持続的脅威など、セキュリティ上の脆弱性の可能性を示唆するような小さな行動異常や動向を検出することが可能になります。その結果、企業はサイバーセキュリティの防御を強化し、高度なサイバー脅威を検知して対応するために、AIやMLを活用したUEBAソリューションへの依存を強めています。

2024年5月、データ分析で有名なSplunkは、同社のUEBAプラットフォームに強力な機械学習アルゴリズムを組み込むことを発表しました。この統合は、機械学習モデルを使用してユーザーとオブジェクトの挙動をリアルタイムで評価することで、脅威検出の精度と速度を高めようとしています。これらの改善は、AIとMLがいかにUEBAシステムに革命をもたらし、新たなサイバー脅威の検出と軽減をより効果的にしているかを示しています。

さらに、サイバーセキュリティ・オペレーションにおける拡張性と自動化の要件が、UEBAにおけるAIと機械学習の利用を後押ししています。企業が拡大し、IT環境がますます高度化するにつれて、ユーザーの行動を手動で監視・分析することは不可能になります。AIとMLテクノロジーは、膨大な量のデータを管理し、脅威検知業務を自動化するために必要なスケーラビリティを可能にします。

実装の複雑化はユーザーおよびエンティティ行動分析（UEBA）市場の成長を妨げるか？

実装の複雑化は、ユーザーおよびエンティティ行動分析（UEBA）業界の成長を阻害する可能性のある重要な要因です。UEBAソリューションの実装には、人工知能（AI）や機械学習（ML）などの新技術を既存のITインフラに統合することが必要であり、これは困難でリソース集約的なプロセスとなり得る。正しい行動洞察を得るために、組織はデータを確実に取得し、標準化し、効果的に分析しなければならないです。このような複雑さは、ITリソースの少ない小規模な組織がUEBAソリューションの導入を躊躇させ、市場全体の成長を遅らせる可能性があります。

さらに、セキュリティ情報・イベント管理（SIEM）プラットフォームなど、他のセキュリティ・システムとUEBAを統合することは、さらなる問題を引き起こす可能性があります。様々なセキュリティ対策間のシームレスな互換性を確保するには、高度な技術的知識と継続的なメンテナンスが必要となります。例えば、既存のSIEMシステムやその他のセキュリティ・アプリケーションとうまく連携するようにUEBAを設定することは難しく、統合の課題や運用コストの増大を招く可能性があります。このような複雑さは、導入スケジュールの長期化につながり、特に社内に必要な知識がない場合には、UEBAソリューションへの投資を思いとどまらせる可能性があります。

さらに、サイバー脅威の絶え間ない進化により、UEBAシステムを成功させるためには常に適応し、改善する必要があります。このため、AIやMLモデルの絶え間ない更新と微調整が必要となり、実装とメンテナンスのプロセスが複雑化します。特にサイバーセキュリティの専門チームを持たない組織では、こうした要求に対応するのに苦労するかもしれないです。

目次

第1章 イントロダクション

• 市場の定義
• 市場セグメンテーション
• 調査手法

第2章 エグゼクティブサマリー

• 主な調査結果
• 市場概要
• 市場ハイライト

第3章 市場概要

• 市場規模と成長の可能性
• 市場動向
• 市場促進要因
• 市場抑制要因
• 市場機会
• ポーターのファイブフォース分析

第4章 ユーザーおよびエンティティ行動分析（UEBA）市場：タイプ別

• ソリューション
• サービス

第5章 ユーザーおよびエンティティ行動分析（UEBA）市場：展開タイプ別

• オンプレミス
• クラウドベース

第6章 地域別分析

• 北米
• 米国
• カナダ
• メキシコ
• 欧州
• 英国
• ドイツ
• フランス
• イタリア
• アジア太平洋
• 中国
• 日本
• インド
• オーストラリア
• ラテンアメリカ
• ブラジル
• アルゼンチン
• チリ
• 中東・アフリカ
• 南アフリカ
• サウジアラビア
• アラブ首長国連邦

第7章 市場力学

• 市場促進要因
• 市場抑制要因
• 市場機会
• COVID-19の市場への影響

第8章 競合情勢

• 主要企業
• 市場シェア分析

第9章 企業プロファイル

• Splunk Inc.
• IBM Security（QRadar SIEM with UEBA module）
• Palo Alto Networks
• MacAfee
• Fortinet
• Cisco

第10章 市場の展望と機会

• 新興技術
• 今後の市場動向
• 投資機会

第11章 付録

• 略語リスト
• 出典と参考文献

User and Entity Behavior Analytics Market Valuation - 2024-2031

The rise of sophisticated cyber-attacks and the increasing complexity of IT environments. As enterprises deal with sophisticated persistent threats, ransomware attacks, and insider threats, UEBA solutions provide increased visibility and insights by studying behavioral patterns to detect anomalies and potential breaches growth surpassing USD 1035.54 Million in 2024 and reachingUSD 11215.59 Million by 2031.

Furthermore, integrating artificial intelligence (AI) and machine learning (ML) into UEBA systems increases their accuracy and efficacy in detecting and responding to threats. Furthermore, increasing legal requirements for data protection and cybersecurity force organizations to invest in advanced security solutions, driving up demand for UEBA across industries expansion is expected to grow at aCAGR of about 40.50% from 2024 to 2031.

User and Entity Behavior Analytics Market: Definition/ Overview

User and Entity Behavior Analytics (UEBA) is the application of advanced analytics and machine learning techniques to monitor and evaluate the behavior of users and entities in an organization's information technology environment. UEBA aids in the detection of potential security threats such as insider threats, compromised accounts, and advanced persistent threats by establishing baselines of typical activity and identifying deviations from them. Its applications include improved threat detection, better incident response, and a stronger overall cybersecurity posture. The future of UEBA seems optimistic, with predicted advances in AI and machine learning leading to more complex and accurate threat detection capabilities. As firms prioritize cybersecurity and regulatory compliance, UEBA will play an important role in providing actionable insights and protecting against changing cyber threats.

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Will Rising Adoption of AI and Machine Learning Drive the User And Entity Behavior Analytics Market?

The growing use of artificial intelligence (AI) and machine learning (ML) is propelling the user and entity behavior analytics (UEBA) market. AI and machine learning technologies improve UEBA solutions' capabilities by allowing for more accurate and efficient analysis of large amounts of data. These technologies allow for the detection of small behavioral anomalies and trends that could suggest possible security vulnerabilities, such as insider threats, compromised accounts, and advanced persistent threats. As a result, enterprises are increasingly relying on AI and ML-powered UEBA solutions to bolster their cybersecurity defenses and detect and respond to advanced cyber threats.

In May 2024, Splunk, a renowned data analytics company, announced the inclusion of powerful machine learning algorithms into its UEBA platform. This integration seeks to increase threat detection accuracy and speed by using machine learning models to assess user and object behavior in real time. These improvements show how AI and ML are revolutionizing UEBA systems, making them more effective at detecting and mitigating emerging cyber threats.

Furthermore, the requirement for scalability and automation in cybersecurity operations drives the use of AI and machine learning in UEBA. As firms expand and their IT environments get increasingly sophisticated, manual monitoring and analysis of user behavior becomes impossible. AI and ML technologies enable the scalability needed to manage enormous amounts of data and automate threat detection operations.

Will Rising Complexity of Implementation Hinder the Growth of the User And Entity Behavior Analytics Market?

The increasing complexity of implementation is a significant factor that may impede the growth of the user and entity behavior analytics (UEBA) industry. Implementing UEBA solutions entails integrating new technologies such as artificial intelligence (AI) and machine learning (ML) with existing IT infrastructure, which can be a difficult and resource-intensive process. To obtain correct behavioral insights, organizations must ensure that their data is captured, standardized, and analyzed effectively. This complexity may dissuade smaller organizations with fewer IT resources from implementing UEBA solutions, delaying overall market growth.

Furthermore, integrating UEBA with other security systems, such as Security Information and Event Management (SIEM) platforms, may provide additional issues. Ensuring seamless compatibility between various security measures necessitates a high level of technical knowledge and continual maintenance. For instance, configuring UEBA to function successfully with existing SIEM systems and other security applications might be difficult, resulting in integration challenges and higher operational expenses. This complexity can lead to lengthier implementation timelines and dissuade firms from investing in UEBA solutions, especially if they lack the required in-house knowledge.

Furthermore, the continual evolution of cyber threats necessitates that UEBA systems constantly adapt and improve to be successful. This needs constant updates and fine-tuning of AI and ML models, adding complexity to the implementation and maintenance processes. Organizations may struggle to keep up with these demands, particularly if they do not have dedicated cybersecurity teams.

Category-Wise Acumens

Will Rising Demand for Comprehensive Software Platforms Drive the User And Entity Behavior Analytics Market?

The growing demand for comprehensive software platforms is a key driver of the user and entity behavior analytics (UEBA) industry. Organizations are increasingly looking for integrated solutions that include advanced threat detection and response capabilities on a single platform. These sophisticated software solutions integrate a variety of security technologies, including machine learning, behavioral analytics, and real-time monitoring, to provide a full picture of potential risks. The need for a unified approach to cybersecurity grows as cyber threats become more complex, prompting organizations to invest in UEBA solutions that can seamlessly integrate with their existing security infrastructure while providing robust protection against sophisticated attacks.

Furthermore, the growing volume of data generated by modern IT settings needs powerful analytics and automation capabilities, which comprehensive UEBA solutions can deliver. These platforms use artificial intelligence (AI) and machine learning (ML) to process and analyze enormous datasets in real time, looking for patterns and abnormalities that could indicate malicious behavior.

Scalability and ease of management are further motivators for the adoption of complete software systems. As businesses grow and their IT infrastructures get more sophisticated, managing several independent security systems becomes more difficult. Comprehensive UEBA solutions make this easier by providing a consolidated solution that unifies several security activities, lowering administrative burdens and increasing operational efficiency. For instance, in July 2024, Microsoft announced the merging of Azure Sentinel with UEBA capabilities, resulting in a unified security management system that scales with an organization's requirements. This integration enables enterprises to streamline their security operations, making it easier to manage and respond to threats in big, distributed systems.

The services category, on the other hand, is expanding at the highest rate, owing to the growing demand for specialist assistance in establishing, administering, and optimizing UEBA systems. Organizations need expert help to efficiently implement these complex solutions and continuously improve their security posture, resulting in a significant increase of the services industry.

Will Rising Usage of On -Premises Propel the Growth of User And Entity Behavior Analytics Market?

The increasing use of on-premises solutions is driving the growth of the user and entity behavior analytics (UEBA) industry. Large corporations and organizations in highly regulated areas like finance, healthcare, and government prefer on-premises implementation since data security and compliance are critical. These firms prefer on-premises solutions because they provide direct control over their data and security infrastructure, ensuring compliance with demanding regulatory standards and lowering the risk of data breaches. The demand for on-premises UEBA solutions is driving market expansion, as businesses want to use advanced analytics and behavioral insights while maintaining complete data sovereignty.

The growing complexity of cyber threats, as well as the necessity for comprehensive security measures, are contributing to an increase in demand for on-premises UEBA solutions. As cyberattacks get increasingly complex, organizations must use advanced analytics and real-time monitoring to successfully identify and neutralize risks. On-premises UEBA systems provide the performance and dependability required to process huge amounts of security data and give actionable insights quickly. The ability to maintain tight control over security infrastructure and data enables enterprises to ensure that their UEBA systems are always up to date and capable of guarding against emerging threats. The growing demand for advanced, dependable, and configurable security solutions is driving the growth of the UEBA market through greater use of on-premises deployments.

The cloud-based category, on the other hand, is expanding at a rapid pace, thanks to its flexibility, scalability, and low cost. The growing adoption of cloud technologies, as well as the demand for remote monitoring and control of security analytics, are driving the rapid expansion of cloud-based UEBA solutions, particularly among small to medium-sized enterprises and companies with hybrid or totally remote workforces.

Country/Region-wise

Will Rising Advanced Technological Infrastruce in North America Drive the User And Entity Behavior Analytics Market?

The robust technical infrastructure in North America is a major driver of the user and entity behavior analytics (UEBA) market. The region has a strong IT ecosystem, defined by widespread use of cutting-edge technologies like artificial intelligence (AI) and machine learning (ML). This architecture enables the integration and deployment of advanced UEBA solutions that employ AI and ML to monitor user and entity activity patterns and detect possible security issues. Organizations in North America are increasingly investing in UEBA to strengthen their cybersecurity posture, threat detection capabilities, and risk mitigation for complex cyber-attacks.

North America is committed to improving its cybersecurity infrastructure. For instance, in June 2024, IBM announced a significant expansion of its cybersecurity offerings, which included improvements to its QRadar UEBA platform. This expansion underscores the company's commitment to integrate sophisticated analytics and AI-powered insights to better threat identification and response. Such investments by large technology companies highlight the significance of strong technological infrastructure in driving the adoption and expansion of UEBA solutions in the region.

Furthermore, the growing regulatory requirements for data protection and cybersecurity in North America are driving up demand for UEBA solutions. Companies must implement advanced security solutions to comply with rules like GDPR and CCPA, which need robust threat detection and response capabilities. The ongoing transformation of North America's technical landscape, combined with strong regulatory requirements, is projected to fuel the region's UEBA market expansion, confirming its position as a worldwide cybersecurity leader.

Will Rising Cybersecurity Threats in Asia-Pacific Propel the User And Entity Behavior Analytics Market?

The rising cybersecurity concerns in the Asia-Pacific region are driving the user and entity behavior analytics (UEBA) market. As digital transformation increases across the region's various industries, there is an increase in cyber-attacks on sensitive information and key infrastructure. The rise of sophisticated cyber dangers, such as advanced persistent threats (APTs) and ransomware assaults, is prompting enterprises to implement advanced security solutions like UEBA. These solutions leverage AI and machine learning to evaluate user and entity activity, detect anomalies, and respond to possible threats in real time, increasing the region's overall cybersecurity resilience.

The Asia-Pacific region is increasingly focused on addressing cybersecurity risks. In July 2024, Cisco announced a strategic collaboration with a prominent cybersecurity business to strengthen its SecureX platform with sophisticated UEBA capabilities. This alliance intends to address rising cyber threats in Asia-Pacific by combining behavioral analytics with Cisco security solutions. Such activities underscore the critical need for sophisticated threat detection and response systems, which is driving the adoption of UEBA solutions throughout the area.

Furthermore, legal concerns and the rising complexity of cyber threats are driving up demand for UEBA solutions in Asia Pacific. Governments and regulatory bodies are enacting stronger data protection laws and cybersecurity rules, requiring businesses to invest in advanced security systems. For instance, in August 2024, the Australian government issued new legislation mandating firms to improve their cybersecurity defences. This regulatory shift, combined with a developing threat landscape, is hastening the adoption of UEBA solutions in Asia-Pacific, as businesses strive to increase threat detection capabilities and maintain compliance with changing security standards.

Competitive Landscape

The competitive landscape of the user and entity behavior analytics (UEBA) market is characterized by a dynamic environment with a mix of emerging players and established technology vendors. The market is driven by increasing cybersecurity threats and the need for advanced threat detection and response capabilities. Companies are leveraging advancements in artificial intelligence (AI) and machine learning (ML) to enhance the accuracy and efficiency of their UEBA solutions. Additionally, there is a growing emphasis on integrating UEBA with other security information and event management (SIEM) systems and broader security frameworks to offer more comprehensive threat intelligence and analysis. This integration facilitates better detection of sophisticated attacks and insider threats, contributing to the evolving competitive dynamics of the market.

Some of the prominent players operating in the user and entity behavior analytics market include:

Splunk, Inc.

IBM Security (QRadar SIEM with UEBA module)

Palo Alto Networks

MacAfee

Fortinet

Latest Developments

In January 2024, Exabeam, a cybersecurity startup that specializes in UEBA, has introduced "Exabeam IoT Sentinel," the industry's first UEBA solution intended exclusively for Internet of Things (IoT) devices. This revolutionary tool employs machine learning algorithms to build baseline behavior patterns for diverse IoT devices and detect anomalies that may indicate security breaches or device compromise. The solution addresses the growing security risks associated with the proliferation of IoT devices in business networks. Exabeam IoT Sentinel connects with the company's existing UEBA technology, allowing for a comprehensive picture of both user and device behavior.

In December 2023, BASF, a multinational chemical business, and Terramera, an agricultural technology company specializing in computational chemistry, have launched a research collaboration aimed at understanding the molecular mechanisms of humic compounds in plant growth promotion. The cooperation intends to employ Terramera's computational biology platform to find the most effective humic chemicals and enhance their formulations.

TABLE OF CONTENTS

1. Introduction

• Market Definition
• Market Segmentation
• Research Methodology

2. Executive Summary

• Key Findings
• Market Overview
• Market Highlights

3. Market Overview

• Market Size and Growth Potential
• Market Trends
• Market Drivers
• Market Restraints
• Market Opportunities
• Porter's Five Forces Analysis

4. User And Entity Behavior Analytics Market, By Type

• Solutions
• Services

5. User And Entity Behavior Analytics Market, By Deployment Type

• On-premises
• Cloud-based

6. Regional Analysis

• North America
• United States
• Canada
• Mexico
• Europe
• United Kingdom
• Germany
• France
• Italy
• Asia-Pacific
• China
• Japan
• India
• Australia
• Latin America
• Brazil
• Argentina
• Chile
• Middle East and Africa
• South Africa
• Saudi Arabia
• UAE

7. Market Dynamics

• Market Drivers
• Market Restraints
• Market Opportunities
• Impact of COVID-19 on the Market

8. Competitive Landscape

• Key Players
• Market Share Analysis

9. Company Profiles

• Splunk Inc.
• IBM Security (QRadar SIEM with UEBA module)
• Palo Alto Networks
• MacAfee
• Fortinet
• Cisco

10. Market Outlook and Opportunities

• Emerging Technologies
• Future Market Trends
• Investment Opportunities

11. Appendix

• List of Abbreviations
• Sources and References