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市場調査レポート
商品コード
1335857
異常検知の世界市場規模、シェア、産業動向分析レポート:展開別、技術別、コンポーネント別(ソリューション(ネットワーク行動、ユーザー行動)、サービス)、エンドユーザー別、地域別展望、予測:2023年~2030年Global Anomaly Detection Market Size, Share & Industry Trends Analysis Report By Deployment, By Technology, By Component (Solution (Network Behavior, and User Behavior), and Services), By End-Use, By Regional Outlook and Forecast, 2023 - 2030 |
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異常検知の世界市場規模、シェア、産業動向分析レポート:展開別、技術別、コンポーネント別(ソリューション(ネットワーク行動、ユーザー行動)、サービス)、エンドユーザー別、地域別展望、予測:2023年~2030年 |
出版日: 2023年07月31日
発行: KBV Research
ページ情報: 英文 332 Pages
納期: 即納可能
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異常検知市場規模は2030年までに134億米ドルに達すると予測され、予測期間中のCAGRは15.9%の市場成長率で上昇する見込みです。
KBV Cardinalのマトリックスに示された分析によると、Microsoft Corporationが同市場におけるトップランナーです。Cisco Systems, Inc.、Broadcom, Inc.、Dell Technologies, Inc.などの企業は、この市場における主要なイノベーターです。2022年3月、シスコシステムズはネットアップと提携し、両社の顧客に自動化、ハイブリッドクラウド運用、可視化ソリューションを提供します。
市場成長要因
データ量と接続デバイスの増加
銀行、IT、ヘルスケア、金融、製造、政府・防衛などにおいて、接続デバイスの増加に伴い、異常検知の必要性が高まっています。様々な技術進歩に積極的に参加するIoTソリューションの普及は、IoT産業に大きな影響を与えています。クラウドベースのIoTデバイスの利用が増加し、さまざまな最終用途産業に最適なソリューションを提供するための競争が激化しているため、市場は急成長しています。さらに、IoT産業が巨大な発展を遂げた主な原因の1つは、ビジネスやセクターのデジタル化を政府がかなり試みていることです。
人工知能(AI)と機械学習(ML)の進歩
AIと機械学習技術の発展により、異常を検知する能力が大幅に向上しました。人工知能(AI)は、クラウドインフラストラクチャ、マイクロサービス、コンテナなどの適応可能なフレームワークを扱うのに人的リソースが不十分な場合に、自動化、リアルタイム分析、慎重さ、正確さ、自己学習など、多くの点で役立つ可能性があります。AIシステムとMLベースのソリューションの最大の利点の1つは、学習しながら学習し、反復するたびに、より良い、より正確な結果を提供する能力です。したがって、AIを搭載した異常検知ツールは、複雑なパターンを評価し、変化する環境に適応し、正確に異常を突き止めることができるため、市場の拡大に拍車がかかります。
市場抑制要因
誤報とシステム実装の問題
異常検知システムは、誤検知(または誤警報)を回避しながら真の異常を特定するための構築と調整が難しい場合があります。誤検知率が高ければ、システムの精度に対するユーザーの信頼が低下し、警告疲れにつながり、製品の普及を妨げる可能性があります。高すぎる偽陽性率は、警告疲れとシステムに対する信頼感の欠如を引き起こす可能性があり、低すぎる偽陰性率は、重大な異常に気づかずに放置する可能性があります。市場が拡大するためには、異常検知アルゴリズムの精度を向上させる必要があります。異常検知ツールを現在のワークフローやシステムに統合するのは困難で時間がかかります。レガシーシステムとの互換性の問題に直面している組織では、異常検知技術の導入が遅れる可能性があります。そのため、これらの要因が今後数年間の市場の成長を妨げる可能性があります。
展開の展望
導入形態によって、市場はクラウド型とオンプレミス型に区分されます。クラウドセグメントは、2022年の市場でかなりの収益シェアを獲得しました。クラウドベースの異常検知システムは、その適応性と拡張性において卓越しています。クラウドインフラストラクチャを利用することで、企業はニーズに応じて異常検知機能を容易に拡張したり縮小したりすることができます。データ処理とデータ量の要件は時間とともに変動するため、企業はクラウド・インフラストラクチャを利用することで、インフラに多額の費用をかけたり、キャパシティを計画したりする必要がないです。
テクノロジーの展望
テクノロジー別に見ると、市場は機械学習&人工知能、ビッグデータ分析、ビジネスインテリジェンス&データマイニングに分類されます。ビッグデータ分析分野は、2022年の市場で最大の売上シェアを記録しました。コネクテッドデバイスやデジタル技術の進歩に伴い、企業は複数のソースから大量のデータを生成・収集しています。こうしたデータは、非構造化、構造化、半構造化のいずれの形式でも入手可能であるため、手作業で不正を発見することは困難です。
コンポーネントの展望
コンポーネントに基づき、市場はソリューションとサービスに二分されます。2022年の市場成長率は、サービス・セグメントに大きく依存しています。クラウドベースのセキュリティ・サービス・ソリューションには、一般的に異常検知サービスが組み込まれています。これらのサービスを利用することで、企業は異常検知業務のセットアップと保守を簡単かつ低コストで行うことができます。
ソリューションの展望
ソリューションは、ネットワーク動作とユーザー動作に分類されます。2022年の同市場では、ネットワーク振る舞い分野が最大の収益シェアを獲得しています。ネットワーク挙動異常検知の運用には、ネットワーク挙動分析が必要です。機械学習(ML)と人工知能(AI)は、他のセキュリティ技術ではアクセスできないネットワークインフラの領域に隠れた危険を特定し、ネットワーク担当者に警告を発するために、ネットワーク行動異常検知で使用されます。
最終用途の展望
エンドユーザー別に見ると、BFSI、小売、IT・通信、ヘルスケア、製造、政府・防衛、その他に分類されます。BFSIセグメントは、2022年の市場で最大の収益シェアを獲得しました。リスク管理はBFSI業界にとって極めて重要です。異常検知によって、市場リスク、オペレーショナルリスク、信用リスク、詐欺リスクなどの潜在的リスクを特定することが可能になります。金融取引、顧客行動、市場パターンの異常を特定することで、組織はリスクを評価・最小化し、インテリジェントな意思決定を行い、財務上の損失を防ぐことができます。
地域別展望
地域別に見ると、市場は北米、欧州、アジア太平洋、LAMEAで分析されます。北米セグメントは、2022年の市場で最も高い収益シェアを記録しました。北米大陸は、特にサイバーセキュリティに関して、急速に変化する不安定な環境にさらされています。デジタル技術の普及は、ビッグデータの発展とともに、企業による膨大なデータの生産と収集にもつながっています。異常検知は、保険、eコマース、金融、ヘルスケア分野での不正行為を発見するために不可欠です。取引データやユーザー行動のパターンや異常を監視することで、企業は積極的に不正行為を特定し、リスクを低減することができます。
List of Figures
The Global Anomaly Detection Market size is expected to reach $13.4 billion by 2030, rising at a market growth of 15.9% CAGR during the forecast period.
The digital economy has swiftly grown throughout the region of Asia Pacific as a result of a strong increase in e-commerce activity, online transactions, and digital services. Consequently, the Asia Pacific region will acquire approximately 1/4th share in the market by 2030. The need for anomaly detection has grown due to this expansion to identify and handle potential fraud, security flaws, and other anomalies in these digital transactions. The regional financial services sector is expanding rapidly because of growing banking services, fintech advancements, and a rise in digital payments. Anomaly detection is crucial for Anti-Money Laundering (AML) initiatives, fraud prevention, and legal compliance in this sector.
The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In June, 20223, Amazon Web Services Inc. expanded its partnership with Lacework Inc. to enhance security alerts and provide its clients an improved anomaly detection linked with Amazon Guard Duty findings. Additionally, In December, 2021, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company formed a collaboration with Pfizer, to develop a prototype solution for detecting abnormal data points in its drug product continuous clinical manufacturing platform for solid oral-dose medicines.
Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation is the forerunner in the Market. Companies such as Cisco Systems, Inc., Broadcom, Inc., Dell Technologies, Inc. are some of the key innovators in the Market. In March, 2022, Cisco Systems, Inc teamed up with NetApp to provide the joint customers of the two companies with automation, hybrid cloud operations, and visibility solutions.
Market Growth Factors
Increasing volume of data and connected devices
Anomaly detection is becoming increasingly necessary as the number of linked devices is increasing in banking, IT, healthcare, finance, manufacturing, and government & defense. The widespread use of IoT solutions that actively participate in various technological advancements significantly impacts the IoT industry. The market has seen an upsurge due to the increasing use of cloud-based IoT devices, which has increased competition to provide the best solutions to various end-use industries. Moreover, one of the main causes of the IoT industry's enormous development is considerable government attempts to digitalize businesses and sectors.
Artificial intelligence (AI) and machine learning (ML) advancements
The ability to detect anomalies has substantially increased because of developments in AI and machine learning techniques. Artificial intelligence (AI) may aid in many ways, including automation, real-time analysis, scrupulosity, accuracy, and self-learning, when human resources are insufficient to handle the adaptable framework of cloud infrastructure, microservices, and containers. One of the greatest benefits of AI systems as well as ML-based solutions, is their ability to learn as they go along and provide better and more accurate results with each iteration. Hence, AI-powered anomaly detection tools can evaluate complicated patterns, adapt to shifting surroundings, and accurately pinpoint anomalies, spurring market expansion.
Market Restraining Factors
Issues with false alarms and system implementation
Anomaly detection systems can be challenging to build and tune to identify true anomalies while avoiding false positives (or false alarms). High rates of false positives could reduce user confidence in the system's accuracy and lead to warning fatigue, which could prevent product uptake. False positive rates that are too high can cause alert fatigue and a lack of faith in the system, whereas false negative rates that are too low can leave serious anomalies unnoticed. For the market to expand, anomaly detection algorithms' accuracy must be improved. Integrating anomaly detection tools with current workflows and systems can be difficult and time-consuming. Implementing anomaly detection technology may be slowed down by organizations facing compatibility problems with legacy systems. Thus, these factors may hamper the market's growth in the coming years.
Deployment Outlook
Based on deployment, the market is segmented into cloud and on-premise. The cloud segment acquired a substantial revenue share in the market in 2022. Cloud-based anomaly detection systems are unsurpassed in their adaptability and scalability. Organizations may easily scale up or down anomaly detection capabilities in accordance with their needs because of cloud infrastructure. Because data processing and volume requirements fluctuate over time, organizations don't need to spend much money on infrastructure or plan for capacity with cloud infrastructure.
Technology Outlook
On the basis of technology, the market is classified into machine learning & artificial intelligence, big data analytics, and business intelligence & data mining. The big data analytics segment recorded the largest revenue share in the market in 2022. As connected devices and digital technology advance, businesses produce and collect large amounts of data from multiple sources. Manually finding irregularities can be challenging because this data is available in both unstructured, structured, and semi-structured, formats.
Component Outlook
Based on component, the market is bifurcated into solution and services. The services segment procured a considerable growth rate in the market in 2022. Cloud-based security service solutions commonly incorporate anomaly detection services. With the help of these services, enterprises can easily and affordably set up as well as maintain anomaly detection operations.
Solution Outlook
On the basis of the solution, the market is classified into network behavior and user behavior. The network behavior segment acquired the largest revenue share in the market in 2022. Network behavior analysis is required for the operation of network behavior anomaly detection. Machine learning (ML) and artificial intelligence (AI) are used in network behavior anomaly detection to identify hidden hazards in areas of network infrastructure where other security technologies cannot access them and to alert network personnel.
End-Use Outlook
By end-use, the market is characterized into BFSI, retail, IT & telecom, healthcare, manufacturing, government & defense, and others. The BFSI segment garnered the maximum revenue share in the market in 2022. Risk management is crucial to the BFSI industry. Anomaly detection makes it possible to identify potential risks, including market risk, operational risk, credit risk, and fraud risk. By identifying anomalies in financial transactions, customer behavior, or market patterns, organizations can assess and minimize risks, make intelligent decisions, and prevent financial losses.
Regional Outlook
Region wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment recorded the highest revenue share in the market in 2022. The continent of North America is subject to an unstable environment that is changing quickly, especially regarding cybersecurity. The proliferation of digital technology, along with the development of big data, has also led to huge data production and collection by companies. Anomaly detection is essential for spotting fraudulent activities in the insurance, e-commerce, financial, and healthcare sectors. By monitoring patterns and anomalies in transactional data or user behavior, businesses can proactively identify and lower the risk of fraud.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., Broadcom, Inc., Cisco Systems, Inc., Dell Technologies, Inc., Dynatrace, Inc., Happiest Minds Technologies Limited, Hewlett Packard Enterprise Company, IBM Corporation, Microsoft Corporation and SAS Institute, Inc.
Recent Strategies Deployed in Anomaly Detection Market
Partnerships, Collaboration and Agreements:
Jun-2023: Amazon Web Services Inc. expanded its partnership with Lacework Inc., a cloud security company. Lacework would integrate its services with AWS Security Hub to enhance security alerts and provide its clients an improved anomaly detection linked with Amazon GuardDuty findings.
May-2023: Amazon Web Services joined hands with Elastic, distributed, free, and open search and analytics engine for all types of data. The collaboration aims at offering a seamless user experience for Elastic Cloud on AWS. Moreover, it would support its client's global cloud adoption journey and help boost their digital transformation.
Nov-2022: Happiest Minds Technologies Limited formed a collaboration with ServiceNow, a software company that provides a cloud-based platform for automating IT management workflows. With this collaboration, the company aims to enhance its IT service offerings globally.
May-2022: IBM Corporation signed an agreement with Amazon Web Services (AWS), a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments. This agreement would deliver IBM's clients easy and rapid access to IBM Software that covers Data and AI, Security, Sustainability, and Automation abilities.
Mar-2022: Cisco Systems, Inc teamed up with NetApp, a data management solutions provider. The partnership would provide the joint customers of the two companies with automation, hybrid cloud operations, and visibility solutions.
Dec-2021: Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company formed a collaboration with Pfizer, an American multinational pharmaceutical and biotechnology corporation. The company would apply its analytics, machine learning, computing, storage, security, and cloud data warehousing capabilities to Pfizer laboratory, clinical manufacturing, and clinical supply chain efforts. Furthermore, the company aimed to develop a prototype solution for detecting abnormal data points in its drug product continuous clinical manufacturing platform for solid oral-dose medicines.
Aug-2021: IBM teamed up with Black & Veatch, an engineering, procurement, consulting, and construction company. The collaboration integrates Black & Veatch Asset Management Services (AMS) and digital analytics with IBM Maximo Application Suite to enhance the performance of assets and extend their lifespans.
Product Launch and Product Expansions:
Mar-2021: Amazon Web Services revealed Amazon Lookout for Metrics, an anomaly detection service, to monitor the health of its client's businesses. The new service aims at opening machine learning technology to more manufacturing plants by removing barriers involved in developing, training, deploying, monitoring, and fine-tuning computer vision models.
Acquisitions and Merger:
Mar-2023: Cisco Systems, Inc completed the acquisition of Lightspin Technologies Ltd., a security software provider based in Israel. The acquisition would enhance Cisco's ability to deliver secure solutions for cloud environments to their customers.
Jul-2022: IBM took over Databand.ai, a leading provider of data observability software. This acquisition aimed to provide IBM with the most comprehensive set of observability offerings for IT across applications, data, and machine learning and would continue to provide IBM's customers and partners with the technology they require to provide trustworthy data and AI at scale.
Mar-2022: Microsoft took over Nuance Communications, a leader in conversational AI and ambient intelligence industries. This acquisition aimed to bring together Nuance's best-in-class conversational AI and ambient intelligence with Microsoft's secure as well as trusted industry cloud offerings. Also, this acquisition would help providers offer more affordable, effective, and accessible healthcare, and help businesses in every industry create more personalized and meaningful customer experiences.
Market Segments covered in the Report:
By Deployment
By Technology
By Component
By End-Use
By Geography
Companies Profiled
Unique Offerings from KBV Research