Anomaly Detection Market Size

Anomaly Detection Market Analysis

The anomaly detection market was valued at USD 5.78 billion in the previous year and is expected to register a CAGR of 16.22%, reaching USD 13.75 billion by the next five years during the forecast period. The traditional statistical approaches are being replaced with modern methods, such as Generative Adversarial Networks (GAN), variational autoencoders (Vaes), and Recurrent Neural Networks (RNNs), thereby enhancing the identification of anomalies across various systems. In addition, the adoption of anomaly detection systems has been increased by a growing demand for significant data storage devices and real-time analysis.

• Anomaly detection is the identification of anomalies that indicate unusual shifts in operations and processes rather than following predictable data or patterns. In addition to fraud detection, system health monitoring, and intrusion detection, anomaly detection can be used for other purposes.
• As the number of connected devices increases rapidly, the amount of data generated by these devices is enormous, making it a critical task to manage this information, which could lead to the loss of valuable information. Anomaly detection could overcome this gap, increasing market growth during the forecast period.
• The breach of data usually means identity theft to the consumer. Fraudsters can make fraudulent purchases, modify listing information, create false reviews, or change account data to take payments into their bank accounts once compromised.
• The market for anomaly detection As a result of this increase, it is expected to grow during the forecast period, and several connected devices are in sectors such as banking, financial services, health care, manufacturing, information technology, telecommunications, defense, and government.
• The main challenges to the growth of anomaly detection during that period are expected to be rising costs and competition from opensource alternatives, which would make it more difficult for organizations to adopt tools and solutions while there is also a lack of qualified workers in areas such as solution development and incidence of asymmetrical faults within Open Source models.
• The emergence of COVID-19, the lockdown, and the restrictions imposed forced many organizations to shift their traditional working methodologies to remote working. Security and risk managers must safeguard their organizations even more to ensure the resilience of online services and digital platforms against cybercrime. Organizations are increasingly adopting anomaly-based intrusion detection systems.