Increasing cybercrimes and rapid increase in generation of data volume is one of the significant factors influencing the market growth.
Anomaly Detection Market Size – USD 2.76 billion in 2019, Market Growth – CAGR of 15.3%, Market Trends – Escalating usage in software testing
The global anomaly detection market is expected to reach USD 8.80 Billion by 2027, according to a new report by Reports and Data. The escalating use of Internet of Thing (IoT) is among the major drivers of the anomaly detection market. The increasing usage of IoT has resulted in a rapid growth of threats and attacks, including denial of service, malicious operation, malicious control, data type probing, scan, spying, and wrong setup that may cause an IoT system failure. According to a research in 2018, about 15.0% of organizations have deployed artificial intelligence solutions, and it was estimated that approximately 31.0% would be incorporating AI solutions in the next year. Moreover, around 50.0% of organizations have observed an increase in fraud value since 2018; and nearly 25.0% of the lost revenues were never recovered.
The incidence of a data flow anomaly is frequently a sign of the presence of a programming error, and the detection of such anomalies may be used for the detection of errors and upgradation of software quality. Also, anomaly detection helps end-users to identify software bugs as soon as they occur, providing programmers new perceptibility into the behavior of the programs, including tracing hidden errors that corrupt the program’s outcomes or identifying rare corner cases in the logic sequence of programs.
Key participants include IBM, Hewlett Packard Enterprise, Dell Technologies, Trustwave Holding Inc., Wipro Limited, Teradata, Cisco Systems, Symantec Corporation, SAS Institute Inc., LogRythm Inc., and Securonix Inc., among others.
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Clinical studies have demonstrated that most COVID-19 patients suffer from the lung infection. Even though a chest CT scan has been found to be an excellent imaging method for diagnosing ling-related diseases, chest X-ray founds extensive application owing to its faster imaging time and noticeably lower cost than CT. Anomaly detection with the help of AI can assist radiologists in examining the vast amount of chest X-ray images for efficient and reliable COVID-19 screening.
Further key findings from the report suggest
- By component, the anomaly detection solutions contributed to a larger market share in 2019 and is likely to grow at a rate of 14.8% in the forecast period. An increase in unidentified malware compromising internal systems, devastating DDoS attacks, and other threats evading traditional security have resulted in network monitoring solutions furnished with robust AI solutions called Network Behavior Anomaly Detection. This solution permanently monitors network traffic, analyzing connectivity to seek anomalies and expose suspicious behavior allowing a response to yet unidentified security threats untraceable by other technologies.
- By deployment mode, the cloud held a larger market share in 2019, owing to several advantages such as cost-effectiveness, data-backup & restoration, scalability, and faster deployment, among others.
- By application, infusion detection held the largest market share in 2019. The market dominance of this method is owing to its ability to builds models of normal network behavior that are then used to identify new patterns that considerably move away from the profiles. Such anomalies may represent actual intrusions or just new behaviors that are required to be added to the profiles.
- By the end-user, the manufacturing industry is projected to grow at a rate of 15.8% in the forecast period. In manufacturing systems, reduction in downtime is critical, and anomaly detection lets predictive maintenance for a decrease in downtime issues. Of late, machine learning is being applied to detect anomaly in manufacturing processes.
- The Asia Pacific region is estimated to grow at the fastest rate of 16.6% in the forecast period, attributed to the developing IT sector in the countries comprising China, India, and Japan, among others.
- In February 2017, Hewlett Packard Enterprise (HPE), a leading market player, announced the acquisition of behavioral analytics firm, Niara, to aid businesses to detect and avert cyber-attacks on IoT devices deployed in the workplace. Niara offers a solution that uses machine learning (ML) and big data analytics to identify advanced cyber threats that have breached perimeter defenses, including firewalls.
To identify the key trends in the industry, click on the link below: https://www.reportsanddata.com/report-detail/anomaly-detection-market
For the purpose of this report, Reports and Data have segmented the global commercial drones market on the basis of component, deployment mode, application, end-users, and region:
Component Outlook (Revenue, USD Million; 2017-2027)
- Network Behavior Anomaly Detection
- User Behavior Anomaly Detection
Deployment Mode Outlook (Revenue, USD Million; 2017-2027)
Application Outlook (Revenue, USD Million; 2017-2027)
- Intrusion Detection
- Fraud Detection
- System Status Monitoring
- Fault Detection
End-Users Outlook (Revenue, USD Million; 2017-2027)
- IT & Telecom
- Government & Defense
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Regional Outlook (Revenue, USD Million; 2017-2027)
- North America
- Asia Pacific
- Latin America
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