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Global Dark Web Intelligence Market to reach USD XX million by 2028.

Global Dark Web Intelligence Market Size study, By Component (Solution, Services), By Deployment Model (On-premise, Cloud), By Enterprise Size (Large Enterprises, SMEs), By End Use Industry (BFSI, Healthcare, Government, IT and Telecom, Manufacturing) and Regional Forecasts 2022-2028

Product Code: ICTNS-38080629
Publish Date: 30-08-2022
Page: 200

Global Dark Web Intelligence Market is valued approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2022-2028.

The Dark Web Intelligence solutions are used to proactively mitigate cyber frauds. These solutions are proven to substantially reduce losses. Dark web intelligence contains three sets of data feeds curated from the Dark and Deep Web, malware networks, botnets and other technical infrastructure used by cybercriminals and fraudsters to commit financial crime. The increasing incidences of extortion ransomware and rising digitization in business processes as well as Strategic initiatives from leading market players are factors that are accelerating the global market demand. For instance, according to Statista – in 2019, globally around 56.1% percent of businesses were victimized by ransomware and this number is further increased to 68.5 % in 2021. Furthermore, leading market players are coming up with new products to capitalize the growing demand for Dar web intelligence solutions. For instance, in November 2021, NICE Actimize, a NICE business launched its new IFM-X Dark Web Intelligence solution. This new solution is intended to safeguard financial institutions, protects customer accounts, and prevents fraud losses. Moreover, in December 2021, New York based Cobwebs Technologies, a leader leader in WEBINT (Web Intelligence), launched a new web intelligence solution designed to improve security in the public sector. Through continuous real-time monitoring, the solution discovers threats across all of the web’s layers to increase visibility, protection, and remediation. Also, growing adoption of multi-layered security across different industries and increasing emergence of remote and hybrid work culture are anticipated to act as a catalyzing factor for the market demand during the forecast period. However, a high cost of dark web intelligence platform coupled with lack of awareness regarding cyber-crime impede the growth of the market over the forecast period of 2022-2028.

The key regions considered for the global Dark Web Intelligence Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the growing dark web intelligence solutions and presence of leading market players. Whereas, Asia Pacific is anticipated to exhibit a significant growth rate over the forecast period 2022-2028. Factors such as the thriving growth of IT sector and increasing penetration of leading market players in the region, would create lucrative growth prospects for the global Dark Web Intelligence Market across the Asia pacific region.

Major market players included in this report are:
Alert Logic
Carbonite, Inc.
Digital Shadows

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 eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available 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:
By Component
By Deployment Model
By Enterprise Size
Large Enterprises
By End Use Industry
IT and Telecom
By Region:
North America

Asia Pacific
South Korea
Latin America
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Dark Web Intelligence Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. Global Dark Web Intelligence Market, by Region, 2020-2028 (USD Million)
1.2.2. Global Dark Web Intelligence Market, by Component, 2020-2028 (USD Million)
1.2.3. Global Dark Web Intelligence Market, by Deployment Model, 2020-2028 (USD Million)
1.2.4. Global Dark Web Intelligence Market, by Enterprise Size, 2020-2028 (USD Million)
1.2.5. Global Dark Web Intelligence Market, by End Use Industry, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Dark Web Intelligence Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Dark Web Intelligence Market Dynamics
3.1. Dark Web Intelligence Market Impact Analysis (2020-2028)
3.1.1. Market Drivers Increasing incidences of extortion ransomware Rising digitization in business processes. Strategic initiatives from leading market players.
3.1.2. Market Challenges High cost of dark web intelligence platform lack of awareness regarding cyber-crime.
3.1.3. Market Opportunities Growing adoption of multi-layered security across different industries. Increasing emergence of remote and hybrid work culture.
Chapter 4. Global Dark Web Intelligence Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Dark Web Intelligence Market, by Component
6.1. Market Snapshot
6.2. Global Dark Web Intelligence Market by Component, Performance – Potential Analysis
6.3. Global Dark Web Intelligence Market Estimates & Forecasts by Component 2018-2028 (USD Million)
6.4. Dark Web Intelligence Market, Sub Segment Analysis
6.4.1. Solution
6.4.2. Service
Chapter 7. Global Dark Web Intelligence Market, by Deployment Model
7.1. Market Snapshot
7.2. Global Dark Web Intelligence Market by Deployment Model, Performance – Potential Analysis
7.3. Global Dark Web Intelligence Market Estimates & Forecasts by Deployment Model 2018-2028 (USD Million)
7.4. Dark Web Intelligence Market, Sub Segment Analysis
7.4.1. On-premise
7.4.2. Cloud
Chapter 8. Global Dark Web Intelligence Market, by Enterprise Size
8.1. Market Snapshot
8.2. Global Dark Web Intelligence Market by Enterprise Size, Performance – Potential Analysis
8.3. Global Dark Web Intelligence Market Estimates & Forecasts by Enterprise Size 2018-2028 (USD Million)
8.4. Dark Web Intelligence Market, Sub Segment Analysis
8.4.1. Large Enterprises
8.4.2. SMEs
Chapter 9. Global Dark Web Intelligence Market, by End Use Industry
9.1. Market Snapshot
9.2. Global Dark Web Intelligence Market by End Use Industry, Performance – Potential Analysis
9.3. Global Dark Web Intelligence Market Estimates & Forecasts by End Use Industry 2018-2028 (USD Million)
9.4. Dark Web Intelligence Market, Sub Segment Analysis
9.4.1. BFSI
9.4.2. Healthcare
9.4.3. Government
9.4.4. IT and Telecom
9.4.5. Manufacturing
Chapter 10. Global Dark Web Intelligence Market, Regional Analysis
10.1. Dark Web Intelligence Market, Regional Market Snapshot
10.2. North America Dark Web Intelligence Market
10.2.1. U.S. Dark Web Intelligence Market Component estimates & forecasts, 2018-2028 Deployment Model estimates & forecasts, 2018-2028 Enterprise Size estimates & forecasts, 2018-2028 End Use Industry estimates & forecasts, 2018-2028
10.2.2. Canada Dark Web Intelligence Market
10.3. Europe Dark Web Intelligence Market Snapshot
10.3.1. U.K. Dark Web Intelligence Market
10.3.2. Germany Dark Web Intelligence Market
10.3.3. France Dark Web Intelligence Market
10.3.4. Spain Dark Web Intelligence Market
10.3.5. Italy Dark Web Intelligence Market
10.3.6. Rest of Europe Dark Web Intelligence Market
10.4. Asia-Pacific Dark Web Intelligence Market Snapshot
10.4.1. China Dark Web Intelligence Market
10.4.2. India Dark Web Intelligence Market
10.4.3. Japan Dark Web Intelligence Market
10.4.4. Australia Dark Web Intelligence Market
10.4.5. South Korea Dark Web Intelligence Market
10.4.6. Rest of Asia Pacific Dark Web Intelligence Market
10.5. Latin America Dark Web Intelligence Market Snapshot
10.5.1. Brazil Dark Web Intelligence Market
10.5.2. Mexico Dark Web Intelligence Market
10.6. Rest of The World Dark Web Intelligence Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Alert Logic Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
11.2.2. Blueliv
11.2.3. Carbonite, Inc.
11.2.4. DarkOwl
11.2.5. Digital Shadows
11.2.6. Echosec
11.2.7. Enigma
11.2.8. Flashpoint
11.2.9. IntSights
11.2.10. KELA
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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