Botnet Detection Market Progress Dictated by Rise in Need for Cyber-threat Control

Market Research Future has published a Half-Cooked Research Report on the Global Botnet Detection Market.


Market synopsis


Market Research Future (MRFR), in its latest the botnet detection world market report, states that the botnet detection market 2022 can expand at about 46.20% CAGR by 2030. As per MRFR analysis, the botnet detection market can generate an annual revenue of above USD 7.3 Billion by 2030. The high adoption of IoT tech and cloud, plus the rise in the Internet utility can spur the expansion of the market in the years to come. Across numerous enterprise, commercial or government, the Internet and the growing influence of computer networks can share the enterprise data. In addition, the rise in the adoption of IoT, the high number of web-connected devices, and the growing installation of devices with high security features can boost the expansion of the market. The networks of connected devices, such as smartphones, personal computers, and laptop are often prone to malware invasion.

The rise in need to remotely control these activities by bot headers or bot masters can spur the market growth. The rising significance botnets to control threat to networks can impel the market growth. On the contrary, the greater challenge encountered by the botnet detection market is the lack of awareness. The growing inclination of enterprises towards traditional botnet techniques and high sophistication solutions can counter the decrease in the expansion rate of the botnet detection market.


Market Segmentation


The segment study of the world botnet detection market are organization size, deployment, detection techniques, application, and vertical.


The deployment based segment of the botnet detection market are on-cloud and on-premise.


The organization size based segments of the botnet detection market are small and medium enterprises (SMEs) and large enterprise.


The application-based segments of the botnet detection market are mobile-based, web-based, and API based.


The detection technique based segments of the botnet detection market are anomaly detection, flow data monitoring, honeypots, and DNS log analysis. The flow data monitoring segment can gain high traction in the years to come.


The vertical based segments of the botnet detection market are transportation, healthcare, government & defense, BFSI, retail, media & entertainment, IT & telecom, and others.


Regional analysis


As per MRFR regional study, the botnet detection market in North America can head the global market in the years to come. The region can dominate the world botnet detection market across the review period. The chief factors that can influence the botnet detection market are the increase in cloud and IoT technology adoption, along with rise in utility of connected devices, such as smartphones and tabs that are under constant threat of botnet attacks. In addition, the well-established regions, such as the UK, followed by Canada are observed to spend a hefty amount on research and development of techniques that are used to detect botnet. This can fuel the growth of the botnet detection market in the region. In Asia Pacific, the significant rise of the botnet detection market can be contributed to the increased utility of botnet detection techniques across enterprises, in order to safeguard enterprise data, in the review period.


Key players


MRFR listed some prominent marketers of the world botnet detection market. They are PerimeterX, Inc. (US), Akamai Technologies (US), Intechnica Ltd (UK), Imperva (US), Distil Inc. (US), Shield Square (India), White Ops, Inc (US), Kasada Pty Ltd (Australia), Instart Logic Inc.(US), Shape Security (US), Datadome (France), Unbotify (Israel), AppsFlyer (US), InfiSecure Technologies Inc. (India), Variti International GmbH (Switzerland), and Mfilterit (India) among others. MRFR report elaborates on different influential forces of the market. 

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Report details
Companies Covered 15
Pages 100
Certified Global Research Member
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