市場調查報告書
商品編碼
1335857
全球異常偵測的全球市場規模、佔有率和行業趨勢分析報告:按部署、按技術、按組件(解決方案(網路行為、用戶行為)、服務)、按最終用戶、按地區、前景和預測:2023-2030Global 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 |
到 2030 年,異常偵測市場規模預計將達到 134 億美元,預測期內市場年複合成長率率為 15.9%。
根據 KBV Cardinal 矩陣中的分析,微軟公司是該市場的領導者。 Cisco Systems, Inc.、Broadcom, Inc. 和 Dell Technologies, Inc. 等公司是該市場的主要創新者。 2022 年 3 月,思科系統公司將與 NetApp 合作,為兩家公司的客戶提供自動化、混合雲端營運和視覺性解決方案。
市場成長要素
資料量和連接設備的增加
隨著銀行、IT、醫療保健、金融、製造、政府和國防等領域連接設備數量的增加,對異常偵測的需求也不斷增加。積極參與各種技術進步的物聯網解決方案的普及,對物聯網產業產生了巨大影響。由於雲端基礎的物聯網設備的使用不斷增加,以及為各種最終用途行業提供最佳解決方案的競爭日益激烈,該市場正在快速成長。此外,物聯網產業龐大發展的主要原因之一是各國政府正在大力嘗試將企業和部門數位。
人工智慧 (AI) 和機器學習 (ML) 的進步
人工智慧和機器學習技術的進步顯著提高了我們偵測異常的能力。當人力資源不足以處理雲端基礎設施、微服務和容器等適應性框架時,可以使用人工智慧(AI),例如自動化、即時分析、謹慎性、準確性和自學習,可以幫助很多方法。人工智慧系統和基於機器學習的解決方案的最大好處之一是它們能夠邊學習邊學習,並在每次迭代中提供更好、更準確的結果。因此,人工智慧驅動的異常偵測工具可以評估複雜的模式,適應不斷變化的環境,並精確地找出異常,從而推動市場擴張。
市場抑制因素
錯誤訊息和系統實施問題
異常偵測系統可能難以建構和調整以識別真正的異常,同時避免偵測(或誤報)。高偵測率會降低使用者對系統準確性的信心,導致警告疲勞,並阻礙產品普及。誤報率太高可能會導致警告疲勞和對系統缺乏信心,而誤報率太低可能會導致重大異常被忽視。為了擴大市場,必須提高異常偵測演算法的準確性。將異常偵測工具整合到目前的工作流程和系統中可能既困難又耗時。面臨與遺留系統的相容性問題的組織可能會延遲異常偵測技術的採用。因此,這些要素可能會阻礙未來幾年的市場成長。
發展前景
根據實施型態,市場分為雲端類型和本地類型。 2022 年,雲端細分市場在市場中佔據了重要的收入佔有率。雲端基礎的異常偵測系統具有出色的適應性和擴充性。透過利用雲端基礎設施,企業可以根據自己的需求輕鬆擴展或縮減異常偵測功能。資料處理和資料量需求隨著時間的推移而變化,因此透過利用雲端基礎設施,企業不必在基礎設施或容量規劃上花費大量資金。
技術展望
依技術分類,市場分為機器學習和人工智慧、巨量資料分析、商業智慧和資料探勘。巨量資料分析領域在 2022 年創下了最大的市場銷售佔有率。隨著互聯設備和數數位技術的進步,企業正在從多個來源產生和收集大量資料。這些資料以非結構化、結構化和半結構化格式提供,因此很難手動偵測詐欺。
組件展望
根據組件,市場分為解決方案和服務。 2022年的市場成長率高度依賴服務領域。雲端基礎的安全服務解決方案通常包括異常偵測服務。這些服務使公司能夠輕鬆且廉價地設定和維護異常偵測操作。
解決方案展望
解決方案分為網路行為和使用者行為。 2022年,在同一市場中,網路行為領域將佔據最大的收入佔有率。網路行為異常偵測需要網路行為分析。機器學習(ML)和人工智慧(AI)用於網路行為異常偵測,以識別網路基礎設施中其他安全技術無法存取的區域中的隱患,並向網路負責人。
最終用途展望
依最終用戶分類,可分為 BFSI、零售、IT/通訊、醫療保健、製造、政府/國防等。 BFSI 細分市場在 2022 年獲得了最大的市場收入佔有率。風險管理對於 BFSI 產業極為重要。異常偵測可協助您識別市場風險、操作風險、信用風險、詐騙風險等潛在風險。透過識別金融交易、客戶行為和市場模式中的異常情況,組織可以評估和最小化風險,做出明智的決策並防止財務損失。
區域展望
從區域來看,我們對北美、歐洲、亞太地區和拉丁美洲地區的市場進行了分析。 2022 年,北美市場收入佔有率最高。北美大陸面臨著快速變化和不穩定的環境,特別是在網路安全方面。數位科技的普及以及巨量資料的發展也導致企業產生和收集大量資料。異常偵測對於發現保險、電子商務、金融和領域領域的詐欺至關重要。透過監控交易資料和使用者行為的模式和異常情況,公司可以主動識別詐欺並降低風險。
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
List of Figures