Global Dark Web Monitoring Software Market Growth (Status and Outlook) 2024-2030

Global Dark Web Monitoring Software Market Growth (Status and Outlook) 2024-2030


Businesses use dark web monitoring software to identify mentions of their organization on deep web and dark web forums and marketplaces, particularly any mentions which include compromised business data being illegally shared or sold. Deep web references areas on the internet that are non-indexed pages; dark web refers to non-indexed, illicit sites and private communications which are only accessible via Tor and I2P. This software uses automated scanners, web crawlers, and scraping techniques to continually monitor and analyze in real time any leaked sensitive business information, such as customer lists or data, employee login credentials, trade secrets, proprietary technology, and other valuable datasets made available on illicit markets. Businesses use dark web monitoring to reduce business risk, detect data breaches early, and to protect their intellectual property and brand reputation. Most commonly, dark web monitoring software is deployed and managed by a company's IT team or security team. Many of these tools have integrations with ticketing systems to assist with distributing real-time alerts to the right parties for remediation.

The global Dark Web Monitoring Software market size is projected to grow from US$ 82 million in 2023 to US$ 149.8 million in 2030; it is expected to grow at a CAGR of 9.0% from 2024 to 2030.

LPI (LP Information)' newest research report, the “Dark Web Monitoring Software Industry Forecast” looks at past sales and reviews total world Dark Web Monitoring Software sales in 2023, providing a comprehensive analysis by region and market sector of projected Dark Web Monitoring Software sales for 2024 through 2030. With Dark Web Monitoring Software sales broken down by region, market sector and sub-sector, this report provides a detailed analysis in US$ millions of the world Dark Web Monitoring Software industry.

This Insight Report provides a comprehensive analysis of the global Dark Web Monitoring Software landscape and highlights key trends related to product segmentation, company formation, revenue, and market share, latest development, and M&A activity. This report also analyzes the strategies of leading global companies with a focus on Dark Web Monitoring Software portfolios and capabilities, market entry strategies, market positions, and geographic footprints, to better understand these firms’ unique position in an accelerating global Dark Web Monitoring Software market.

This Insight Report evaluates the key market trends, drivers, and affecting factors shaping the global outlook for Dark Web Monitoring Software and breaks down the forecast by Type, by Application, geography, and market size to highlight emerging pockets of opportunity. With a transparent methodology based on hundreds of bottom-up qualitative and quantitative market inputs, this study forecast offers a highly nuanced view of the current state and future trajectory in the global Dark Web Monitoring Software.

Some of the future market trends of Dark Web Monitoring Software are:

Increasing adoption of cloud-based dark web monitoring solutions: Cloud-based dark web monitoring solutions offer benefits such as scalability, flexibility, cost-effectiveness, and accessibility. As more organizations migrate their data to the cloud or adopt hybrid cloud environments, they will need cloud-based dark web monitoring solutions to ensure consistent and secure management of their data across different platforms.

Growing integration of AI and ML in dark web monitoring solutions: AI and ML technologies can enhance the capabilities and efficiency of dark web monitoring solutions by automating tasks such as data discovery, classification, quality assessment, policy enforcement, anomaly detection, and recommendation. As more organizations leverage AI and ML for their data-driven initiatives, they will need dark web monitoring solutions that can support and augment their AI and ML efforts.

Rising demand for self-service dark web monitoring solutions: Self-service dark web monitoring solutions enable users to access, analyze, and monitor their data without relying on IT or centralized teams. Self-service dark web monitoring solutions foster a culture of data democratization and empowerment within organizations. As more organizations adopt self-service analytics and BI tools, they will need self-service dark web monitoring solutions to ensure proper oversight and accountability of their data usage.

This report presents a comprehensive overview, market shares, and growth opportunities of Dark Web Monitoring Software market by product type, application, key players and key regions and countries.

Segmentation by type
Cloud Based
On Premises

Segmentation by application
Large Enterprises
SMEs

This report also splits the market by region:
Americas
United States
Canada
Mexico
Brazil
APAC
China
Japan
Korea
Southeast Asia
India
Australia
Europe
Germany
France
UK
Italy
Russia
Middle East & Africa
Egypt
South Africa
Israel
Turkey
GCC Countries

The below companies that are profiled have been selected based on inputs gathered from primary experts and analyzing the company's coverage, product portfolio, its market penetration.
LastPass
Alert Logic
Webhose.io
ID Agent
Recorded Future
Echosec Systems
Progress
ACID Technologies
Cyjax
Sixgill
DarkOwl
Breach Secure Now!
Digital Shadows
DigitalStakeout
Axur
ImmuniWeb
IntSights
LifeRaft
LogmeOnce
Massive Alliance
Terbium Labs
PhishLabs
SpyCloud
Vigilante ATI
ZeroFOX

Please note: The report will take approximately 2 business days to prepare and deliver.


*This is a tentative TOC and the final deliverable is subject to change.*
1 Scope of the Report
2 Executive Summary
3 Dark Web Monitoring Software Market Size by Player
4 Dark Web Monitoring Software by Regions
5 Americas
6 APAC
7 Europe
8 Middle East & Africa
9 Market Drivers, Challenges and Trends
10 Global Dark Web Monitoring Software Market Forecast
11 Key Players Analysis
12 Research Findings and Conclusion

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