市場調查報告書
商品編碼
1363862
全球異常檢測市場規模研究與預測,按類型(解決方案、服務)、最終用戶產業(BFSI、製造、醫療保健、IT 和電信等)、部署(本地、雲端)和區域分析,2023年-2030年Global Anomaly Detection Market Size study & Forecast, by Type (Solutions, Service), by End-user Industry (BFSI, Manufacturing, Healthcare, IT and Telecommunications, Others), by Deployment (On-premise, Cloud) and Regional Analysis, 2023-2030 |
預計2023年至2030年預測期內,全球異常檢測市場將以超過 15.30%的健康成長率成長。異常檢測是指識別資料集中明顯偏離預期行為或正常模式的模式或觀察結果的過程。它通常用於金融、網路安全、製造和醫療保健等各個領域,以檢測可能表明欺詐、錯誤或異常的異常或可疑活動。由於連接設備數量的增加以及機器學習和人工智慧的日益普及等因素,異常檢測市場日益擴大。異常檢測的目標是將正常行為與異常或異常行為區分開。檢測方法取決於資料的性質和特定問題領域。在2023年至2030年的預測期內,其重要性逐漸增加。
連接設備不斷從各種來源收集資料,例如環境感測器、機器感測器和穿戴式裝置。異常檢測演算法可以分析這些即時資料,以識別異常模式或與預期行為的偏差。根據Statista,到2030年,全球連網裝置數量將達到 170 億台,消費領域預計將在物聯網連網設備數量方面佔據主導地位。此外,預計到2025年,全球物聯網連接設備的總安裝量將達到 309 億台,而2021年為 138 億台。推動市場的另一個重要因素是機器學習和人工智慧的日益普及。機器學習和人工智慧技術透過模式識別、統計建模、整合方法和持續學習為異常檢測提供了強大的工具。這些技術增強了檢測複雜資料集中的異常的能力,提高了準確性並適應不斷變化的模式,使異常檢測在各個行業和應用程式中更加高效和有效。根據 Statista 的資料,2021年,Newsle 以 88.71%的市佔率引領全球機器學習產業,其次是 TensorFlow 和 Torch。此外,根據Next Move Strategy Consulting預測,未來十年人工智慧產業將快速成長。目前其價值約為 1,000 億美元,預計到2030年將增加一倍以上,達到近 2 兆美元。此外,網路安全案例數量的增加和雲端技術的不斷採用將為預測期內的市場創造利潤豐厚的成長前景。然而,異常檢測的高成本抑制了2023-2030年預測期內的市場成長。
全球異常檢測市場研究涵蓋的關鍵區域包括亞太地區、北美、歐洲、拉丁美洲以及中東和非洲。由於該地區智慧互聯設備和工業物聯網的使用增加,北美在2022年佔據市場主導地位。根據Statista,2020年,全球 59%的受訪者將基於 NetFlow 的分析器視為對抗分散式阻斷服務攻擊的非常有效的工具。由於連網設備和物聯網導致的異常現象增加等因素增加了系統侵入市場空間的可能性,預計亞太地區在預測期內將大幅成長。
研究的目的是確定近年來不同細分市場和國家的市場規模,並預測未來幾年的價值。本報告目的是涵蓋參與研究的國家內該行業的定性和定量方面。
本報告還提供了有關促進因素和挑戰等關鍵方面的詳細資訊,這些因素將決定市場的未來成長。此外,還涵蓋了利害關係人投資的微觀市場的潛在機會,以及對主要參與者的競爭格局和產品供應的詳細分析。
Global Anomaly Detection Market is anticipated to grow with a healthy growth rate of more than 15.30% over the forecast period 2023-2030. Anomaly detection refers to the process of identifying patterns or observations that deviate significantly from the expected behavior or normal patterns within a dataset. It is commonly used in various fields such as finance, cybersecurity, manufacturing, and healthcare to detect unusual or suspicious activities that may indicate fraud, errors, or anomalies. The Anomaly Detection market is expanding because of factors such as the increasing number of connected devices and the growing adoption of machine learning and artificial intelligence. The goal of anomaly detection is to separate normal behavior from abnormal or anomalous behavior. The detection methods, depending on the nature of the data and the specific problem domain. Its importance has progressively increased during the forecast period 2023-2030.
Connected devices continuously collect data from various sources, such as environmental sensors, machine sensors, and wearable devices. Anomaly detection algorithms can analyze this real-time data to identify unusual patterns or deviations from expected behavior. According to Statista, with 17 billion connected devices worldwide in 2030, the consumer sector is expected to dominate in terms of the number of Internet of Things connected devices. Furthermore, the total installed base of Internet of Things connected devices globally is predicted to reach 30.9 billion units by 2025, up from 13.8 billion units in 2021. Another important factor that drives the market is the increased adoption of machine learning and artificial intelligence. Machine learning and AI techniques provide powerful tools for anomaly detection by enabling pattern recognition, statistical modeling, ensemble methods, and continuous learning. These techniques enhance the ability to detect anomalies in complex datasets, improve accuracy, and adapt to changing patterns, making anomaly detection more efficient and effective across various industries and applications. As per Statista, Newsle led the global machine learning industry in 2021 with an 88.71% market share, followed by TensorFlow and Torch. In addition, According to Next Move Strategy Consulting, the artificial intelligence sector increase rapidly over the next decade. Its current worth of roughly USD 100 billion is predicted to more than double by 2030, reaching nearly USD 2 trillion. Also, the growing number of cybersecurity cases and rising adoption of cloud technology would create a lucrative growth prospectus for the market over the forecast period. However, the high cost of Anomaly Detection stifles market growth throughout the forecast period of 2023-2030.
The key regions considered for the Global Anomaly Detection Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the dominance of increased use of smart linked devices, and the Industrial Internet of Things in the region. According to Statista, In 2020, 59% of respondents worldwide rated NetFlow-based analyzers as a very effective tool against distributed denial of service assaults. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as an increase in anomalies as a result of connected devices and the Internet of Things has raised the possibility of a system intrusion in the market space.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.
The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below.
List of tables and figures and dummy in nature, final lists may vary in the final deliverable
List of tables and figures and dummy in nature, final lists may vary in the final deliverable