異常検知ソリューションの世界市場規模：タイプ別、用途別、業界別、地域別、範囲および予測

異常検知ソリューションの市場規模と予測

異常検知ソリューション市場規模は、2024年に61億8,000万米ドルと評価され、2026年から2032年にかけて15.80%のCAGRで成長し、2032年には199億9,000万米ドルに達すると予測されます。

• 異常検知ソリューションは、データ中の通常とは異なるパターンや行動を認識する高度なシステムです。正常な動作のベースラインを確立することで、異常検知システムは、詐欺、サイバーセキュリティリスク、システム障害、または運用の非効率性を示す可能性のある変動を特定することができます。
• 異常検知技術は、業務効率とセキュリティを向上させるために多くの業界で広く利用されています。異常検知システムは、取引パターンを研究し、予想される行動からの逸脱を発見することで、不正取引や口座乗っ取りなどの潜在的な不正行為を検知することができます。
• 異常検知テクノロジーは、その機能と応用範囲が拡大しているため、今後、多くの業界でその利用が飛躍的に拡大することが予想されます。企業がIoTデバイス、クラウドコンピューティング、ビッグデータ環境など、さまざまなソースからより多くのデータを収集するにつれ、異常検知を強化する必要性が高まっています。

異常検知ソリューションの世界市場力学

世界の異常検知ソリューション市場を形成している主な市場力学は以下の通り：

主な市場促進要因

• サイバーセキュリティ脅威の増加：高度なサイバー攻撃やデータ漏洩の急増は、異常検知ソリューション市場の主要促進要因です。サイバー犯罪者は、セキュリティ・システムに侵入する革新的な手口で組織を標的にするようになっています。異常検知ソリューションは、不正アクセスや内部脅威などの脅威を示す予期せぬパターンや行動を検知するために不可欠です。
• 増大するデータ量：デジタルトランスフォーメーションとIoTデバイスによって企業が生成するデータの急激な増加には、優れた異常検知が必要です。膨大な量のデータが生成されるため、標準的な監視アプローチでは異常値や予期せぬパターンを特定することができなくなります。
• 規制遵守とデータ保護：GDPRやCCPAなどの規制やデータ保護ルールの増加により、異常検知システムの需要が高まっています。組織は、機密情報を保護し、データの完全性を維持するための強力なセキュリティ対策を講じることで、これらの規則に準拠しなければならないです。

主な課題

• 高い誤検知率：大きな問題の一つは、法的措置が誤って異常と認識された場合に発生する誤検知への対応です。この困難は、異常検知システムが感度と特異性の間で妥協しなければならないために発生します。誤検知率が高いと、ユーザーがアラートに対して鈍感になり、重大な脅威を見過ごしてしまうアラート疲労を引き起こす可能性があります。
• データ・プライバシーに関する懸念：異常検知システムは、通常のパターンからの逸脱を発見するために、膨大な量の機密データへのアクセスを頻繁に必要とします。このため、データのプライバシーとセキュリティの問題が発生します。プライバシーの脅威を軽減し、ユーザーの信頼を維持するためには、可能な限りデータの匿名化だけでなく、強力なデータの暗号化とアクセス制御を実装する必要があります。
• 既存システムとの統合：異常検知技術を既存のITアーキテクチャやシステムに統合することは困難です。特に現行システムが旧式であったり、独自の技術を使用していたりする場合は、互換性に懸念が生じる可能性があります。異常検知ソリューションが複数のソースからのデータを適切に監視・分析するためには、シームレスなインターフェイスが不可欠です。

主要動向：

• 人工知能や機械学習との統合：最も重要な動向の1つは、異常検知ソフトウェアとAIおよび機械学習技術の組み合わせです。これらの最新テクノロジーは、システムが過去のデータから学習し、動向を発見し、新たな危険に動的に適応することを可能にすることで、異常を特定する精度と効率を向上させます。
• 分野横断的な採用の増加：異常検知技術は、従来のITやサイバーセキュリティ以外の分野でも広く利用されるようになっています。製造業、小売業、ヘルスケア業界では、業務効率の向上、不正行為の検出、患者ケアの質の向上のためにこれらのテクノロジーを活用しています。
• クラウドベースの異常検知ソリューション：クラウドコンピューティングの普及に伴い、クラウドベースの異常検知ソリューションの人気が高まっています。これらのソリューションは、拡張性、柔軟性、費用対効果を提供し、あらゆる規模の企業にとって魅力的なものとなっています。クラウドベースのシステムにより、企業はコストのかかるオンプレミスのインフラを必要とすることなく、大規模なデータセットの処理と分析を行うことができます。

目次

第1章 異常検知ソリューションの世界市場イントロダクション

• 市場のイントロダクション
• 調査範囲
• 前提条件

第2章 エグゼクティブサマリー

第3章 VERIFIED MARKET RESEARCHの調査手法

• データマイニング
• バリデーション
• 一次資料
• データソース一覧

第4章 異常検知ソリューションの世界市場展望

• 概要
• 市場力学
  • 促進要因
  • 抑制要因
  • 機会
• ポーターのファイブフォースモデル
• バリューチェーン分析

第5章 異常検知ソリューションの世界市場：タイプ別

• 概要
• 統計的異常検知
• 機械学習型異常検知
• ハイブリッド型異常検知

第6章 異常検知ソリューションの世界市場：用途別

• 概要
• ネットワークセキュリティ
• 不正検知
• リスク管理
• 侵入検知
• 機器ヘルスモニタリング
• その他

第7章 異常検知ソリューションの世界市場：業界別

• 概要
• 銀行、金融サービス、保険（BFSI）
• 小売、eコマース
• ヘルスケア
• ITおよび電気通信
• 製造業
• エネルギー・公益事業
• 政府・防衛
• その他

第8章 異常検知ソリューションの世界市場：地域別

• 概要
• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • その他欧州
• アジア太平洋
  • 中国
  • 日本
  • インド
  • その他アジア太平洋地域
• 世界のその他の地域
  • ラテンアメリカ
  • 中東・アフリカ

第9章 世界の異常検知ソリューション市場の競合情勢

• 概要
• 各社の市場シェア
• 主な発展戦略

第10章 企業プロファイル

• Splunk
• IBM
• Hewlett Packard Enterprise
• Cisco
• Microsoft
• Dell Technologies
• Broadcom
• SAS Institute
• Amazon Web Services
• Dynatrace

第11章 付録

• 関連調査

Anomaly Detection Solution Market Size And Forecast

Anomaly Detection Solution Market size was valued at USD 6.18 Billion in 2024 and is projected to reach USD 19.99 Billion by 2032, growing at a CAGR of 15.80% from 2026 to 2032.

• Anomaly detection solutions are advanced systems that recognize out-of-the-ordinary patterns or behaviors in data. By establishing a baseline of normal behavior, anomaly detection systems can identify variations that could signal fraud, cybersecurity risks, system failures, or operational inefficiencies.
• Anomaly detection technologies are widely used in many industries to improve operational efficiency and security. Anomaly detection systems can detect potentially fraudulent activity such as unauthorized transactions or account takeovers by studying transaction patterns and spotting deviations from expected behavior.
• Because of its rising capabilities and applications, the use of anomaly detection technologies is expected to grow dramatically across numerous industries in the future. As enterprises collect more data from a variety of sources including IoT devices, cloud computing, and big data environments, the need for enhanced anomaly detection grows.

Global Anomaly Detection Solution Market Dynamics

The key market dynamics that are shaping the global Anomaly Detection Solution Market include:

Key Market Drivers:

• Increasing Cybersecurity Threats: The surge in sophisticated cyberattacks and data breaches is a key driver of the Anomaly Detection Solution Market. Cybercriminals are increasingly targeting organizations with innovative tactics for breaching security systems. Anomaly detection solutions are critical for detecting unexpected patterns or behaviors that could indicate a threat such as unauthorized access or insider threats.
• Growing Volume of Data: The exponential rise of data generated by businesses, fueled by digital transformation and IoT devices, needs excellent anomaly detection. With massive amounts of data being generated, standard monitoring approaches become ineffective at identifying outliers and unexpected patterns.
• Regulatory Compliance and Data Protection: Rising regulatory regulations and data protection rules such as GDPR and CCPA are increasing demand for anomaly detection systems. Organizations must comply with these rules by putting in place strong security measures to secure sensitive information and maintain data integrity.

Key Challenges:

• High False Positive Rates: One major problem is handling false positives which occur when legal actions are wrongly identified as anomalies. This difficulty occurs because anomaly detection systems must strike a compromise between sensitivity and specificity. High false positive rates can cause alert fatigue in which users get desensitized to alerts and may overlook serious threats.
• Concerns about Data Privacy: Anomaly detection systems frequently require access to vast amounts of sensitive data to spot deviations from regular patterns. This presents issues of data privacy and security. To alleviate privacy threats and retain user trust, strong data encryption and access controls must be implemented as well as data anonymization when possible.
• Integration with Existing Systems: Integrating anomaly detection technologies into existing IT architecture and systems can be difficult. Compatibility concerns may develop, especially if the current systems are antiquated or involve proprietary technologies. A seamless interface is critical to ensuring that the anomaly detection solution can properly monitor and analyze data from several sources.

Key Trends:

• Integration with Artificial Intelligence and Machine Learning: One of the most significant trends is the combination of anomaly detection software with AI and machine learning technologies. These modern technologies improve the accuracy and efficiency of identifying anomalies by allowing systems to learn from historical data, spot trends, and dynamically adapt to emerging dangers.
• Increased Adoption across Fields: Anomaly detection technologies are being more widely used in fields other than traditional IT and cybersecurity. Manufacturing, retail, and healthcare industries are utilizing these technologies to increase operational efficiency, fraud detection, and patient care quality.
• Cloud-based Anomaly Detection Solutions: Cloud-based anomaly detection solutions have grown in popularity as cloud computing has become more prevalent. These solutions provide scalability, flexibility, and cost-effectiveness making them appealing to enterprises of all sizes. Cloud-based systems enable enterprises to process and analyze big datasets without requiring costly on-premises infrastructure.

Global Anomaly Detection Solution Market Regional Analysis

Here is a more detailed regional analysis of the global Anomaly Detection Solution Market:

North America:

• The North American region dominates the Anomaly Detection Solution Market with the United States taking the lead. This supremacy stems mostly from the region's advanced technological infrastructure, high adoption rates of AI and machine learning technologies, and severe regulatory requirements across multiple industries. The growing emphasis on cybersecurity is a major driving force in the North American Anomaly Detection Solution Market.
• According to the FBI's Internet Crime Report, the Internet Crime Complaint Center (IC3) received 847,376 complaints in 2021 with a potential loss of $6.9 billion. This is a 7% rise over 2020, highlighting the growing demand for improved anomaly detection systems to identify and mitigate cybersecurity risks.
• The banking industry also contributes significantly to market growth with anomaly detection playing an important role in fraud prevention and anti-money laundering initiatives. According to the Banking Crimes Enforcement Network, banking institutions filed 19% more Suspicious Activity Reports (SARs) between 2019 and 2020, totaling more than 2.5 million reports. Furthermore, government measures are boosting industry expansion.

Asia Pacific:

• The Asia Pacific region is the fastest-growing region in the Anomaly Detection Solution Market with China and India at the forefront. This rapid expansion is being fueled by the region's growing digital transformation and increased emphasis on cybersecurity across all sectors. The growing worry about cybersecurity risks is a significant driver of the Asia Pacific Anomaly Detection Solution Market.
• According to the China Internet Network Information Center (CNNIC), China had 1.05 billion internet users as of June 2022 indicating a large digital environment necessitating strong security measures. The Indian Computer Emergency Response Team (CERT-In) recorded more than 1.4 million cybersecurity incidents in 2021, a considerable increase from prior years underlining the critical need for improved threat detection technologies.
• The finance sector's digital transformation is also driving market expansion. According to the Monetary Authority of Singapore, 94% of Singapore's financial institutions have implemented cloud-based services by 2020 highlighting the need for sophisticated anomaly identification in financial transactions. Furthermore, government measures are promoting market growth.

Global Anomaly Detection Solution Market: Segmentation Analysis

The Global Anomaly Detection Solution Market is Segmented based on Type, Application, Industry Vertical, and Geography.

Anomaly Detection Solution Market, By Type

• Statistical Anomaly Detection
• Machine Learning Anomaly Detection
• Hybrid Anomaly Detection

Based on Type, the Global Anomaly Detection Solution Market is bifurcated into Statistical Anomaly Detection, Machine Learning Anomaly Detection, and Hybrid Anomaly Detection. Machine learning anomaly detection is the dominant type in the global Anomaly Detection Solution Market. This dominance stems from machine learning's ability to analyze large volumes of data and detect complex patterns that traditional statistical methods may miss. Machine learning algorithms can continuously learn and adapt from new data improving accuracy over time and handling dynamic and evolving datasets more effectively.

Anomaly Detection Solution Market, By Application

• Network Security
• Fraud Detection
• Risk Management
• Intrusion Detection
• Equipment Health Monitoring
• Others

Based on Application, the Global Anomaly Detection Solution Market is bifurcated into Network Security, Fraud Detection, Risk Management, Intrusion Detection, Equipment Health Monitoring, and Others. In the global Anomaly Detection Solution Market, network security is the dominant application. The primary driver of this dominance is the increasing frequency and sophistication of cyberattacks which necessitate robust anomaly detection systems to protect networks from potential breaches and threats. Network security solutions leverage anomaly detection to identify unusual patterns that may indicate malicious activity, unauthorized access, or potential vulnerabilities.

Anomaly Detection Solution Market, By Industry Vertical

• Banking, Financial Services, and Insurance (BFSI)
• Retail and E-commerce
• Healthcare
• IT and Telecom
• Manufacturing
• Energy and Utilities
• Government and Defense
• Others

Based on Industry Vertical, the Global Anomaly Detection Solution Market is bifurcated into Banking, Financial Services, and Insurance (BFSI), Retail and E-commerce, Healthcare, IT and Telecom, Manufacturing, Energy and Utilities, Government and Defense, and Others. In the global Anomaly Detection Solution Market, banking, financial services, and insurance (BFSI) are the dominant industry verticals. This dominance is driven by the sector's high vulnerability to fraud, cyber-attacks, and financial anomalies. Financial institutions face complex regulatory requirements and significant financial risks making robust anomaly detection crucial for identifying fraudulent transactions, managing risk, and ensuring compliance.

Key Players

The "Global Anomaly Detection Solution Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are Splunk, IBM, Hewlett Packard Enterprise, Cisco, Microsoft, Dell Technologies, Broadcom, SAS Institute, Amazon Web Services, and Dynatrace.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Global Anomaly Detection Solution Market Key Developments

• In September 2023, Splunk announced that it would acquire Sumo Logic, a firm that specializes in cloud-native monitoring and observability solutions, such as anomaly detection. This acquisition seeks to improve Splunk's capabilities in real-time data analytics and security by incorporating Sumo Logic's powerful anomaly detection tools into the platform.
• In July 2023, IBM purchased Databand.ai, a major provider of data observability and anomaly detection technologies. This acquisition is part of IBM's overall effort to improve its data and AI capabilities. By incorporating Databand AI's technology, IBM hopes to improve its data management and anomaly detection features, giving more complete solutions for organizations to monitor and assure the quality of their data, resulting in more reliable and efficient decision-making processes.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL ANOMALY DETECTION SOLUTION MARKET

• 1.1 INTRODUCTION of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL ANOMALY DETECTION SOLUTION MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL ANOMALY DETECTION SOLUTION MARKET, BY TYPE

• 5.1 Overview
• 5.2 Statistical Anomaly Detection
• 5.3 Machine Learning Anomaly Detection
• 5.4 Hybrid Anomaly Detection

6 GLOBAL ANOMALY DETECTION SOLUTION MARKET, BY APPLICATION

• 6.1 Overview
• 6.2 Network Security
• 6.3 Fraud Detection
• 6.4 Risk Management
• 6.5 Intrusion Detection
• 6.6 Equipment Health Monitoring
• 6.7 Others

7 GLOBAL ANOMALY DETECTION SOLUTION MARKET, BY INDUSTRY VERTICAL

• 7.1 Overview
• 7.2 Banking, Financial Services, and Insurance (BFSI)
• 7.3 Retail and E-commerce
• 7.4 Healthcare
• 7.5 IT and Telecom
• 7.6 Manufacturing
• 7.7 Energy and Utilities
• 7.8 Government and Defense
• 7.9 Others

8 GLOBAL ANOMALY DETECTION SOLUTION MARKET, BY GEOGRAPHY

• 8.1 Overview
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
  • 8.2.3 Mexico
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 U.K.
  • 8.3.3 France
  • 8.3.4 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Rest of Asia Pacific
• 8.5 Rest of the World
  • 8.5.1 Latin America
  • 8.5.2 Middle East and Africa

9 GLOBAL ANOMALY DETECTION SOLUTION MARKET COMPETITIVE LANDSCAPE

• 9.1 Overview
• 9.2 Company Market Share
• 9.3 Key Development Strategies

10 COMPANY PROFILES

• 10.1 Splunk
  • 10.1.1 Overview
  • 10.1.2 Financial Performance
  • 10.1.3 Product Outlook
  • 10.1.4 Key Developments
• 10.2 IBM
  • 10.2.1 Overview
  • 10.2.2 Financial Performance
  • 10.2.3 Product Outlook
  • 10.2.4 Key Developments
• 10.3 Hewlett Packard Enterprise
  • 10.3.1 Overview
  • 10.3.2 Financial Performance
  • 10.3.3 Product Outlook
  • 10.3.4 Key Developments
• 10.4 Cisco
  • 10.4.1 Overview
  • 10.4.2 Financial Performance
  • 10.4.3 Product Outlook
  • 10.4.4 Key Developments
• 10.5 Microsoft
  • 10.5.1 Overview
  • 10.5.2 Financial Performance
  • 10.5.3 Product Outlook
  • 10.5.4 Key Developments
• 10.6 Dell Technologies
  • 10.6.1 Overview
  • 10.6.2 Financial Performance
  • 10.6.3 Product Outlook
  • 10.6.4 Key Developments
• 10.7 Broadcom
  • 10.7.1 Overview
  • 10.7.2 Financial Performance
  • 10.7.3 Product Outlook
  • 10.7.4 Key Developments
• 10.8 SAS Institute
  • 10.8.1 Overview
  • 10.8.2 Financial Performance
  • 10.8.3 Product Outlook
  • 10.8.4 Key Developments
• 10.9 Amazon Web Services
  • 10.9.1 Overview
  • 10.9.2 Financial Performance
  • 10.9.3 Product Outlook
  • 10.9.4 Key Developments
• 10.10 Dynatrace
  • 10.10.1 Overview
  • 10.10.2 Financial Performance
  • 10.10.3 Product Outlook
  • 10.10.4 Key Developments

11 Appendix

• 11.1 Related Research