市场调查报告书
商品编码
1363862
全球异常检测市场规模研究与预测,按类型(解决方案、服务)、最终用户产业(BFSI、製造、医疗保健、IT 和电信等)、部署(本地、云端)和区域分析,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 |
预计 2023 年至 2030 年预测期内,全球异常检测市场将以超过 15.30% 的健康成长率成长。异常检测是指识别资料集中明显偏离预期行为或正常模式的模式或观察结果的过程。它通常用于金融、网路安全、製造和医疗保健等各个领域,以检测可能表明欺诈、错误或异常的异常或可疑活动。由于连接设备数量的增加以及机器学习和人工智慧的日益普及等因素,异常检测市场正在扩大。异常检测的目标是将正常行为与异常或异常行为区分开。检测方法取决于资料的性质和特定问题领域。在 2023 年至 2030 年的预测期内,其重要性逐渐增加。
连接设备不断从各种来源收集资料,例如环境感测器、机器感测器和穿戴式装置。异常检测演算法可以分析这些即时资料,以识别异常模式或与预期行为的偏差。据 Statista 称,到 2030 年,全球连网装置数量将达到 170 亿台,消费领域预计将在物联网连网设备数量方面占据主导地位。此外,预计到 2025 年,全球物联网连接设备的总安装量将达到 309 亿台,而 2021 年为 138 亿台。推动市场的另一个重要因素是机器学习和人工智慧的日益普及。机器学习和人工智慧技术透过模式识别、统计建模、整合方法和持续学习为异常检测提供了强大的工具。这些技术增强了检测复杂资料集中的异常的能力,提高了准确性并适应不断变化的模式,使异常检测在各个行业和应用程式中更加高效和有效。根据 Statista 的数据,2021 年,Newsle 以 88.71% 的市占率引领全球机器学习产业,其次是 TensorFlow 和 Torch。此外,根据Next Move Strategy Consulting预测,未来十年人工智慧产业将快速成长。目前其价值约为 1,000 亿美元,预计到 2030 年将增加一倍以上,达到近 2 兆美元。此外,网路安全案例数量的增加和云端技术的不断采用将为预测期内的市场创造利润丰厚的成长前景。然而,异常检测的高成本抑制了 2023-2030 年预测期内的市场成长。
全球异常检测市场研究考虑的关键区域包括亚太地区、北美、欧洲、拉丁美洲以及中东和非洲。由于该地区智慧互联设备和工业物联网的使用增加,北美在 2022 年占据市场主导地位。据 Statista 称,2020 年,全球 59% 的受访者将基于 NetFlow 的分析器视为对抗分散式阻断服务攻击的非常有效的工具。由于连网设备和物联网导致的异常现象增加等因素增加了系统侵入市场空间的可能性,预计亚太地区在预测期内将大幅成长。
研究的目的是确定近年来不同细分市场和国家的市场规模,并预测未来几年的价值。该报告旨在纳入参与研究的国家内该行业的定性和定量方面。
该报告还提供了有关驱动因素和挑战等关键方面的详细信息,这些因素将决定市场的未来成长。此外,它还纳入了利害关係人投资的微观市场的潜在机会,以及对主要参与者的竞争格局和产品供应的详细分析。 。
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