Summary

The Generative AI cybersecurity market is estimated to accrue a market value of USD 7.1 billion in 2024 and reach USD 40.1 billion by 2030, at a compound annual growth rate (CAGR) of 33.4% between 2024–2030. The generative AI cybersecurity market is rapidly expanding because of two considerations. On one hand, enterprises are increasingly implementing generative AI-powered security solutions to improve threat detection and response capabilities, resulting in a greatly improved overall security posture. The other major driving factor is booming use of generative AI in several industries which has resulted in the establishment of a unique market area devoted to safeguarding AI systems. These include protecting training data, preventing model tampering, and verifying the accuracy of AI-generated results.
“By offering, cybersecurity software for generative AI segment is expected to register the fastest market growth rate during the forecast period.”
Several significant factors have contributed to the continued adoption of cybersecurity software for generative AI. As generative AI technology gets more widely used, its potential flaws and the value of the data it handles make it an appealing target for cyber criminals. Enterprises are increasingly becoming dependent on generative AI for a variety of applications, ranging from content generation to decision-making processes, highlighting the necessity for strong security measures. The advanced nature of these generative models, specially LLMs, necessitates specialized security protocols that can efficiently reduce hazards. This growing reliance on generative AI, combined with increased awareness of cybersecurity vulnerabilities, is propelling the rapid growth of this section of the AI cybersecurity market.
“By security type, network security segment is expected to account for the largest market share during the forecast period.”
As more firms integrate generative AI into their networks, the complexity and volume of data processed has increased, making these networks excellent targets for cyber-attacks. This has led to a rapid rise of network security within the generative AI cybersecurity market, making it the largest segment by security type. The sensitive nature of the information handled by AI systems—ranging from personal data to confidential company insights—requires enhanced security measures. Furthermore, as remote work and cloud computing become the norm, protecting these interconnected systems from intrusions has never been more important. The increased awareness of possible risks, combined with the critical requirement to protect AI-driven processes, pulls the network security segment to the forefront of cybersecurity market.
“By Region, North America to have the largest market share in 2024, and Asia Pacific is slated to grow at the fastest rate during the forecast period.”
High frequency of cyber threats, substantial investment in AI research, and an established technical infrastructure has pushed North America as the regional leader in the deployment of generative AI in cybersecurity. The region's thriving tech scene, which includes centers like Silicon Valley, has encouraged creativity and attracted sizeable investments for firms in cybersecurity and artificial intelligence. US based vendors, such as IBM and AWS, are developing cybersecurity guardrails to protect generative AI infrastructure. On the other hand, companies such as Sophos and Palo Alto have infused generative AI into their cybersecurity products for increased threat protection. The US government has also recognized generative AI as an important tool for national security, initiating programs like the National AI Initiative Act.
Asia Pacific is the fastest growing regional market due to digital transformation and massive investments in integrating AI with cybersecurity. China, India and Australia are leading the charge, with China’s security spend expected to exceed USD 50 billion by 2026. The region is also experiencing a huge volume of attacks - over 1,800 cyberattacks per organization in early 2023. Government support and investment in innovation is helping organizations integrate generative AI into their cybersecurity frameworks. This combination of high threat, investment and regulation makes Asia Pacific the adopter of new cybersecurity technologies.
Breakdown of primaries
In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the Generative AI cybersecurity market.
 By Company: Tier I – 27%, Tier II – 48%, and Tier III – 25%
 By Designation: C-Level Executives – 22%, D-Level Executives – 45%, and others – 33%
 By Region: North America – 40%, Europe – 29%, Asia Pacific – 21%, Middle East & Africa – 4%, and Latin America – 6%
The report includes the study of key players offering Generative AI cybersecurity solutions. It profiles major vendors in the Generative AI cybersecurity market. The major players in the Generative AI cybersecurity market include Microsoft (US), IBM (US), Google (US), SentinelOne (US), AWS (US), NVIDIA (US), Cisco (US), CrowdStrike (US), Fortinet (US), Zscaler (US), Trend Micro (Japan), Palo Alto Networks (US), BlackBerry (Canada), Darktrace (UK), F5 (US), Okta (US), Sangfor (China), SecurityScorecard (US), Sophos (UK), Broadcom (US), Trellix (US), Veracode (US), LexisNexis (US), Abnormal Security (US), Adversa AI (Israel), Aquasec (US), BigID (US), Checkmarx (US), Cohesity (US), Credo AI (US), Cybereason (US), DeepKeep (Israel), Elastic NV (US), Flashpoint (US), Lakera (US), MOSTLY AI (Austria), Recorded Future (US), Secureframe (US), Skyflow (US), SlashNext (US), Snyk (US), Tenable (US), TrojAI (Canada), VirusTotal (Spain), XenonStack (UAE), and Zerofox (US).
Research coverage
This research report categorizes the Generative AI cybersecurity Market by Offering (Software and Services), by Software Type (Generative AI-based Cybersecurity Software, Cybersecurity Software for Generative AI), by Software Deployment Mode [Cloud and On-premises]), by Services (Professional Services [Training & Consulting, System Integration & Implementation, and Support & Maintenance] and Managed Services), by Generative AI-based Cybersecurity (Threat Detection & Intelligence Software, Risk Assessment Software, Exposure Management Software, Phishing Simulation & Prevention Software, Remediation Guidance Software, Threat Hunting Platforms, Code Analysis Software), by Cybersecurity for Generative AI (Generative AI Training Data Security, Generative AI Model Security, Generative AI Infrastructure Security, Generative AI Application Security), by Security Type (Database Security, Network Security, Endpoint Security, and Application Security), by End-user (enterprise end-users, cloud hyper scalers, generative AI providers, managed security service providers), and by Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the generative AI cybersecurity market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions, and services; key strategies; contracts, partnerships, agreements, new product & service launches, mergers and acquisitions, and recent developments associated with the generative AI cybersecurity market. Competitive analysis of upcoming startups in the generative AI cybersecurity market ecosystem is covered in this report.
Key Benefits of Buying the Report
The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall generative AI cybersecurity market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
• Analysis of key drivers (increased adoption of generative AI driving demand for cybersecurity solutions, Pressing demand of AI-powered security driving the generative AI cybersecurity market, stricter data regulations and compliance laws fueling demand for secure AI systems, and rising cyber threats spurring demand for generative AI cybersecurity solutions), restraints (rising privacy concerns hindering generative AI cybersecurity adoption, lack of combined AI-cybersecurity expertise stifling generative AI cybersecurity market growth, and high deployment costs of advanced generative AI security solutions prohibiting smaller organizations), opportunities (advancing AI research fueling development of more powerful cybersecurity solutions, scalable and customizable generative AI cybersecurity solutions unlocking wider market adoption, AI-cybersecurity collaboration fostering innovation and market growth for generative AI security solutions), and challenges (ethical and legal concerns around misuse and accountability hindering AI adoption in cybersecurity, evolving cyber threats demanding continuous advancements in AI security solutions, and high-quality data scarcity limiting effectiveness of generative AI cybersecurity solutions).
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the Generative AI cybersecurity market.
• Market Development: Comprehensive information about lucrative markets – the report analyses the Generative AI cybersecurity market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the Generative AI cybersecurity market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Microsoft (US), IBM (US), Google (US), SentinelOne (US), AWS (US), NVIDIA (US), Cisco (US), CrowdStrike (US), Fortinet (US), Zscaler (US), Trend Micro (Japan), Palo Alto Networks (US), BlackBerry (Canada), Darktrace (UK), F5 (US), Okta (US), Sangfor (China), SecurityScorecard (US), Sophos (UK), Broadcom (US), and Trellix (US), among others in the Generative AI cybersecurity market. The report also helps stakeholders understand the pulse of the Generative AI cybersecurity market and provides them with information on key market drivers, restraints, challenges, and opportunities.

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Table of Contents

1 INTRODUCTION 47
1.1 STUDY OBJECTIVES 47
1.2 MARKET DEFINITION 47
1.2.1 INCLUSIONS AND EXCLUSIONS 48
1.3 STUDY SCOPE 49
1.3.1 MARKET SEGMENTATION 49
1.3.2 YEARS CONSIDERED 53
1.4 CURRENCY CONSIDERED 53
1.5 STAKEHOLDERS 54
2 RESEARCH METHODOLOGY 55
2.1 RESEARCH DATA 55
2.1.1 SECONDARY DATA 57
2.1.2 PRIMARY DATA 57
2.1.2.1 Breakup of primary profiles 58
2.1.2.2 Key insights from industry experts 58
2.2 DATA TRIANGULATION 59
2.3 MARKET SIZE ESTIMATION 60
2.3.1 TOP-DOWN APPROACH 60
2.3.2 BOTTOM-UP APPROACH 61
2.4 MARKET FORECAST 65
2.5 RESEARCH ASSUMPTIONS 66
2.6 RESEARCH LIMITATIONS 68
3 EXECUTIVE SUMMARY 69
4 PREMIUM INSIGHTS 78
4.1 ATTRACTIVE OPPORTUNITIES FOR KEY PLAYERS IN GENERATIVE AI CYBERSECURITY MARKET 78
4.2 GENERATIVE AI CYBERSECURITY MARKET: TOP THREE SECURITY TYPES 79
4.3 NORTH AMERICA: GENERATIVE AI CYBERSECURITY MARKET, BY OFFERING
AND SECURITY TYPE 79
4.4 GENERATIVE AI CYBERSECURITY MARKET, BY REGION 80
 
5 MARKET OVERVIEW AND INDUSTRY TRENDS 81
5.1 INTRODUCTION 81
5.2 MARKET DYNAMICS 82
5.2.1 DRIVERS 82
5.2.1.1 Increased adoption of generative AI driving demand for cybersecurity solutions 82
5.2.1.2 Increased awareness of AI security needs 83
5.2.1.3 Stricter data regulations and compliance laws fueling demand for secure AI systems 83
5.2.1.4 Rising cyber threats spurring demand for generative AI cybersecurity solutions 84
5.2.2 RESTRAINTS 85
5.2.2.1 Rising privacy concerns hindering adoption of generative AI cybersecurity adoption 85
5.2.2.2 Lack of combined AI-cybersecurity expertise stifling market growth 85
5.2.3 OPPORTUNITIES 86
5.2.3.1 Rapid advancements in AI research fueling development of more powerful cybersecurity solutions 86
5.2.3.2 Increasing adoption of scalable and customizable generative AI cybersecurity solutions 86
5.2.3.3 Growing collaboration between AI and cybersecurity fostering innovation and market growth 87
5.2.4 CHALLENGES 87
5.2.4.1 Ethical and legal concerns around misuse and accountability 87
5.2.4.2 Evolving cyber threat landscape 88
5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 88
5.4 PRICING ANALYSIS 89
5.4.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY SOFTWARE TYPE 90
5.4.2 INDICATIVE PRICING ANALYSIS, BY OFFERING 92
5.5 SUPPLY CHAIN ANALYSIS 93
5.6 ECOSYSTEM ANALYSIS 96
5.6.1 GENERATIVE AI-BASED CYBERSECURITY TOOL PROVIDERS 98
5.6.2 CYBERSECURITY TOOL PROVIDERS FOR GENERATIVE AI 98
5.6.3 GENERATIVE AI CYBERSECURITY SERVICE PROVIDERS 99
5.6.4 CLOUD HYPERSCALERS 99
5.6.5 ENTERPRISE END USERS 99
5.6.6 GOVERNMENT AND REGULATORY BODIES 99
5.7 TECHNOLOGY ANALYSIS 100
5.7.1 KEY TECHNOLOGIES 100
5.7.1.1 Adversarial Machine Learning (AML) 100
5.7.1.2 Federated learning 100
5.7.1.3 Differential privacy 101
5.7.1.4 Homomorphic encryption 101
5.7.1.5 Secure Multi-Party Computation (SMPC) 101
5.7.2 COMPLEMENTARY TECHNOLOGIES 102
5.7.2.1 Blockchain 102
5.7.2.2 Zero-Trust Architecture (ZTA) 102
5.7.2.3 Endpoint Detection and Response (EDR) 102
5.7.2.4 Vulnerability management 103
5.7.3 ADJACENT TECHNOLOGIES 103
5.7.3.1 Quantum computing 103
5.7.3.2 DevSecOps 103
5.7.3.3 Forensics and incident response 104
5.7.3.4 Big data analytics 104
5.8 GENERATIVE AI CYBERSECURITY TECHNOLOGY ROADMAP 105
5.9 GENERATIVE AI CYBERSECURITY BUSINESS MODELS 107
5.9.1 BUSINESS MODELS: GENERATIVE AI-BASED CYBERSECURITY 107
5.9.1.1 Subscription-based model 107
5.9.1.2 AI licensing model 107
5.9.1.3 Consulting and implementation services model 108
5.9.2 BUSINESS MODELS: CYBERSECURITY FOR GENERATIVE AI 108
5.9.2.1 Subscription-based model 108
5.9.2.2 One-time license fee model 109
5.9.2.3 Pay-as-you-go model 109
5.9.2.4 Managed services model 110
5.10 PATENT ANALYSIS 110
5.10.1 METHODOLOGY 110
5.10.2 PATENTS FILED, BY DOCUMENT TYPE 110
5.10.3 INNOVATION AND PATENT APPLICATIONS 111
5.10.3.1 Top 10 applicants in generative AI cybersecurity market 111
5.11 KEY CONFERENCES AND EVENTS, 2024–2025 116
5.12 REGULATORY LANDSCAPE 118
5.12.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS 118
5.12.2 REGULATIONS: GENERATIVE AI CYBERSECURITY 121
5.12.2.1 North America 121
5.12.2.1.1 US 121
5.12.2.1.1.1 Executive order on AI (US) 121
5.12.2.1.1.2 National Institute of Standards and Technology (NIST) 121
5.12.2.1.1.3 CISA’s AI roadmap 122
5.12.2.1.2 Canada 122
5.12.2.1.2.1 Artificial Intelligence and Data Act (AIDA) 122
5.12.2.1.2.2 Directive on automated decision-making 122
5.12.2.1.2.3 Canadian Centre for Cyber Security 122
5.12.2.1.2.4 Privacy guidelines 122
 
5.12.2.2 Europe 122
5.12.2.2.1 UK 122
5.12.2.2.1.1 Five cross-sectoral principles 122
5.12.2.2.1.2 AI cybersecurity code of practice 122
5.12.2.2.1.3 Generative AI Framework for HMG 123
5.12.2.2.2 Germany 123
5.12.2.2.2.1 General Data Protection Regulation (GDPR) 123
5.12.2.2.2.2 IT Security Act (IT-SiG 2.0) 123
5.12.2.2.2.3 AI strategy 123
5.12.2.2.3 France 123
5.12.2.2.3.1 AI for humanity strategy 123
5.12.2.2.3.2 National Commission for Informatics and Liberties (CNIL) 123
5.12.2.2.3.3 Cybersecurity framework 123
5.12.2.2.4 Italy 123
5.12.2.2.4.1 Italian Data Protection Code 123
5.12.2.2.4.2 National Cybersecurity Perimeter 123
5.12.2.2.4.3 AI strategy 124
5.12.2.2.5 Spain 124
5.12.2.2.5.1 Spanish Data Protection Agency (AEPD) 124
5.12.2.2.5.2 National Cybersecurity Strategy 124
5.12.2.2.5.3 AI strategy 124
5.12.2.2.6 Netherlands 124
5.12.2.2.6.1 Dutch Data Protection Authority (DPA) 124
5.12.2.2.6.2 National Cybersecurity Agenda (NCSA) 124
5.12.2.2.6.3 AI strategy 124
5.12.2.3 Asia Pacific 125
5.12.2.3.1 China 125
5.12.2.3.1.1 Interim Measures for Generative AI Services 125
5.12.2.3.1.2 Deep Synthesis and Algorithm Recommendation Measures 125
5.12.2.3.2 India 125
5.12.2.3.2.1 National Strategy on AI 125
5.12.2.3.2.2 Draft Personal Data Protection Bill 125
5.12.2.3.3 Japan 125
5.12.2.3.3.1 AI Strategy 2021 125
5.12.2.3.3.2 Act on Protection of Personal Information (APPI) 125
5.12.2.3.4 South Korea 126
5.12.2.3.4.1 AI National Strategy 126
5.12.2.3.4.2 Personal Information Protection Act (PIPA) 126
5.12.2.3.5 ASEAN 126
5.12.2.3.5.1 ASEAN framework on AI 126
5.12.2.3.5.2 National initiatives 126
 
5.12.2.3.6 Australia & New Zealand (ANZ) 126
5.12.2.3.6.1 Australia's AI ethics framework 126
5.12.2.3.6.2 New Zealand's AI principles 126
5.12.2.4 Middle East & Africa 126
5.12.2.4.1 United Arab Emirates (UAE) 126
5.12.2.4.1.1 UAE strategy for AI 2031 126
5.12.2.4.1.2 National AI programme 127
5.12.2.4.1.3 AI governance and regulatory frameworks 127
5.12.2.4.2 Kingdom of Saudi Arabia (KSA) 127
5.12.2.4.2.1 National Strategy for Data and AI (NSDAI) 127
5.12.2.4.2.2 Saudi Data and Artificial Intelligence Authority (SDAIA) 127
5.12.2.4.3 Kuwait 127
5.12.2.4.3.1 National AI and data strategy 127
5.12.2.4.3.2 Kuwait national cybersecurity strategy 127
5.12.2.4.4 Qatar 127
5.12.2.4.4.1 Qatar National Vision 2030 127
5.12.2.4.4.2 Qatar AI and cybersecurity initiatives 127
5.12.2.4.5 Turkey 128
5.12.2.4.5.1 National AI Strategy 128
5.12.2.4.5.2 Personal Data Protection Law (KVKK) 128
5.12.2.4.6 Egypt 128
5.12.2.4.6.1 National AI strategy 128
5.12.2.4.6.2 Egyptian cybersecurity regulations 128
5.12.2.4.7 Africa 128
5.12.2.4.7.1 African Union AI strategy 128
5.12.2.4.7.2 Country-specific initiatives 128
5.12.2.5 Latin America 128
5.12.2.5.1 Brazil 128
5.12.2.5.1.1 AI regulation framework 128
5.12.2.5.1.2 General Data Protection Law (LGPD) 129
5.12.2.5.1.3 National AI strategy 129
5.12.2.5.2 Mexico 129
5.12.2.5.2.1 Federal Law on Protection of Personal Data Held by Private Parties (LFPDPPP) 129
5.12.2.5.2.2 National digital strategy 129
5.12.2.5.2.3 AI governance initiatives 129
5.12.2.5.3 Argentina 129
5.12.2.5.3.1 Personal Data Protection Law 129
5.12.2.5.3.2 National AI Plan 129
5.12.2.5.3.3 Cybersecurity regulations 129
 
5.13 PORTER’S FIVE FORCES ANALYSIS 130
5.13.1 THREAT OF NEW ENTRANTS 131
5.13.2 THREAT OF SUBSTITUTES 131
5.13.3 BARGAINING POWER OF SUPPLIERS 131
5.13.4 BARGAINING POWER OF BUYERS 131
5.13.5 INTENSITY OF COMPETITIVE RIVALRY 131
5.14 KEY STAKEHOLDERS AND BUYING CRITERIA 132
5.14.1 KEY STAKEHOLDERS IN BUYING PROCESS 132
5.14.2 BUYING CRITERIA 133
5.15 EVOLUTION OF GENERATIVE AI CYBERSECURITY 134
5.16 INVESTMENT LANDSCAPE AND FUNDING SCENARIO 136
5.16.1 MOST VALUED CYBERSECURITY START-UPS, JULY 2024 136
5.16.2 GENERATIVE AI-BASED CYBERSECURITY START-UPS 138
5.16.3 START-UPS PROVIDING CYBERSECURITY FOR GENERATIVE AI 139
5.17 GUARDRAILS FOR LARGE LANGUAGE MODELS 141
5.17.1 NEED TO GUARDRAIL LLMS 141
5.17.2 THREE PILLARS OF LLM GUARDRAILS 141
5.17.2.1 Policy enforcement 141
5.17.2.2 Contextual understanding 141
5.17.2.3 Continous adaptability 142
5.17.3 TYPES OF LLM GUARDRAILS 142
5.17.3.1 Ethical guardrails 142
5.17.3.2 Compliance guardrails 142
5.17.3.3 Contextual guardrails 142
5.17.3.4 Security guardrails 142
5.17.3.5 Adaptive guardrails 142
5.17.4 IMPLEMENTING LLM GUARDRAILS 143
5.18 CASE STUDY ANALYSIS 144
5.18.1 BFSI 144
5.18.1.1 ZeroFox provided timely, actionable intelligence to shore up Simply Business’s information security 144
5.18.1.2 Pomelo implemented several integrations to build end-to-end security program by deploying Snyk 144
5.18.2 TELECOMMUNICATIONS 145
5.18.2.1 Evocabank helped Nokia protect and engage with close to 28 million fans and followers online 145
5.18.2.2 Telenor reduced its vulnerability risk posture by integrating Snyk into its development process 145
5.18.3 HEALTHCARE 146
5.18.3.1 Sentara Healthcare determined most imminent threats by deploying Predictive Prioritization 146
5.18.4 CLOUD HYPERSCALERS 146
5.18.4.1 IBM enabled faster, more accurate threat detection and automated incident responses by using Palo Alto Networks’ solutions 146
5.18.4.2 Oracle collaborated with Stellar Cyber and implemented Open Extended Detection and Response (XDR) platform on Oracle Cloud Infrastructure to detect and remediate threats early 147
5.18.5 GENERATIVE AI PROVIDERS 148
5.18.5.1 OpenAI partnered with Okta to contribute valuable insights and concentrate on creating groundbreaking AI technologies 148
5.18.5.2 NVIDIA partnered with Check Point to help secure cloud infrastructures at scale 149
6 GENERATIVE AI CYBERSECURITY MARKET, BY OFFERING 150
6.1 INTRODUCTION 151
6.1.1 OFFERINGS: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 151
6.2 SOFTWARE, BY TYPE 152
6.2.1 GENERATIVE AI-BASED CYBERSECURITY SOFTWARE 154
6.2.1.1 Increasing sophistication of cyber threats and need for more adaptive and intelligent security measures to drive market 154
6.2.2 CYBERSECURITY SOFTWARE FOR GENERATIVE AI 155
6.2.2.1 Need for trustworthy and transparent AI systems and growing regulatory landscape around AI governance to propel market 155
6.3 SOFTWARE, BY DEPLOYMENT MODE 156
6.3.1 CLOUD 158
6.3.1.1 Increasing complexity and frequency of cyber threats, need for real-time security measures, and growing adoption of cloud computing and IoT technologies to foster market growth 158
6.3.2 ON-PREMISES 159
6.3.2.1 Growing complexity of cyber threats to drive on-premises deployment of generative AI cybersecurity solutions 159
6.4 SERVICES 160
6.4.1 PROFESSIONAL SERVICES 161
6.4.1.1 Increasing sophistication and frequency of cyber threats to fuel demand for professional services 161
6.4.1.1.1 Training & consulting services 163
6.4.1.1.2 System integration & implementation services 164
6.4.1.1.3 Support & maintenance services 165
6.4.2 MANAGED SERVICES 166
6.4.2.1 MSS to utilize generative AI to offer organizations proactive approach to cybersecurity 166
 
7 GENERATIVE AI CYBERSECURITY MARKET, BY GENERATIVE AI-BASED CYBERSECURITY SOFTWARE 168
7.1 INTRODUCTION 169
7.1.1 GENERATIVE AI-BASED CYBERSECURITY SOFTWARE: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 169
7.2 THREAT DETECTION & INTELLIGENCE SOFTWARE 171
7.2.1 THREAT DETECTION AND INTELLIGENCE SOFTWARE TO SPOT UNUSUAL PATTERNS AND POTENTIAL THREATS IN REAL TIME AND KEEP DATA SAFE AND SECURE 171
7.2.1.1 Automated threat analysis 172
7.2.1.2 Security Information & Event Management (SIEM) 173
7.2.1.3 AI-native security analysis 173
7.2.1.4 Threat correlation 173
7.2.1.5 Threat intelligence 173
7.3 RISK ASSESSMENT SOFTWARE 174
7.3.1 RISK ASSESSMENT SOFTWARE TO ANALYZE DATA, IDENTIFY POTENTIAL RISKS, AND SUGGEST PREVENTIVE MEASURES 174
7.3.1.1 Automated risk insights 175
7.3.1.2 Impact analysis 175
7.3.1.3 Risk intelligence 175
7.3.1.4 Compliance automation 176
7.3.1.5 Other risk assessment software 176
7.4 EXPOSURE MANAGEMENT SOFTWARE 177
7.4.1 EXPOSURE MANAGEMENT SOFTWARE TO HELP ORGANIZATIONS KEEP TRACK OF THEIR DIGITAL ASSETS AND POTENTIAL VULNERABILITIES 177
7.4.1.1 Vulnerability analysis 178
7.4.1.2 Exposure prioritization 178
7.4.1.3 Automated exposure detection 179
7.4.1.4 Incident response 179
7.4.1.5 Other exponential management software 179
7.5 PHISHING SIMULATION & PREVENTION SOFTWARE 180
7.5.1 REALISTIC PHISHING SIMULATION AND PREVENTION SOFTWARE TO RECOGNIZE PHISHING ATTEMPTS AND PREVENT THEM 180
7.5.1.1 Phishing simulation campaigns 181
7.5.1.2 Phishing attack analysis 181
7.5.1.3 Deepfake detection 181
7.5.1.4 Fraud prevention 182
7.5.1.5 Social engineering detection 182
 
7.6 REMEDIATION GUIDANCE SOFTWARE 182
7.6.1 REMEDIATION GUIDANCE SOFTWARE TO HELP ORGANIZATIONS QUICKLY FIGURE OUT HOW TO FIX SECURITY PROBLEMS 182
7.6.1.1 Automated remediation 183
7.6.1.2 Interactive remediation support 184
7.6.1.3 Proactive threat management 184
7.6.1.4 Compliance remediation 184
7.6.1.5 Other remediation guidance software 184
7.7 THREAT HUNTING PLATFORMS 185
7.7.1 THREAT HUNTING PLATFORMS TO AUTOMATE ROUTINE TASKS AND ENABLE SECURITY EXPERTS TO FOCUS ON MORE COMPLEX ISSUES 185
7.7.1.1 Real-time threat analysis 186
7.7.1.2 Natural language query interface 186
7.7.1.3 Behavior analysis 186
7.7.1.4 Response automation 186
7.7.1.5 Other threat hunting platforms 187
7.8 CODE ANALYSIS SOFTWARE 187
7.8.1 CODE ANALYSIS SOFTWARE POWERED BY GENERATIVE AI TO DETECT AND MITIGATE THREATS 187
7.8.1.1 Code snippet analysis 188
7.8.1.2 Source code protection 189
7.8.1.3 Vulnerability detection 189
7.8.1.4 Automated code review 189
7.8.1.5 Compliance checks 190
8 GENERATIVE AI CYBERSECURITY MARKET, BY CYBERSECURITY SOFTWARE FOR GENERATIVE AI 191
8.1 INTRODUCTION 192
8.1.1 CYBERSECURITY SOFTWARE FOR GENERATIVE AI: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 192
8.2 GENERATIVE AI TRAINING DATA SECURITY SOFTWARE 194
8.2.1 GENERATIVE AI TRAINING DATA SECURITY TO PROTECT DATA USED TO DEVELOP POWERFUL AI MODELS 194
8.2.1.1 Data integrity verification 195
8.2.1.2 Secure data augmentation 195
8.2.1.3 Automated data cleaning 195
8.2.1.4 Data quality monitoring 196
8.2.1.5 Data anonymization 196
8.3 GENERATIVE AI MODEL SECURITY SOFTWARE 196
8.3.1 GENERATIVE AI MODEL SECURITY SOFTWARE POISED TO MITIGATE RISKS ASSOCIATED WITH ITS ADOPTION 196
8.3.1.1 Model integrity 197
8.3.1.2 Adversarial training & testing 198
8.3.1.3 Secure model training environments 198
8.3.1.4 Model drift & bias detection 198
8.3.1.5 Robustness testing 199
8.4 GENERATIVE AI INFRASTRUCTURE SECURITY SOFTWARE 199
8.4.1 ORGANIZATIONS TO ENHANCE THEIR SECURITY POSTURE BY LEVERAGING GENERATIVE AI INFRASTRUCTURE SECURITY SOFTWARE 199
8.4.1.1 Continuous monitoring 200
8.4.1.2 Automated security patching 200
8.4.1.3 Secure API management 201
8.4.1.4 Real-time threat detection 201
8.4.1.5 Security audits 201
8.5 GENERATIVE AI APPLICATION SECURITY SOFTWARE 202
8.5.1 GENERATIVE AI APPLICATION SECURITY SOFTWARE TO PROVIDE BETTER ENCRYPTION TECHNIQUES TO PROTECT DATA WITHIN APPLICATIONS 202
8.5.1.1 Prompt injection security 203
8.5.1.2 Data leakage prevention 203
8.5.1.3 User authentication & access control 203
8.5.1.4 Monitoring & anomaly detection 204
8.5.1.5 Ethical AI governance 204
9 GENERATIVE AI CYBERSECURITY MARKET, BY SECURITY TYPE 205
9.1 INTRODUCTION 206
9.1.1 SECURITY TYPES: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 206
9.2 DATABASE SECURITY 208
9.2.1 RISING DEMAND FOR DATABASE SECURITY DUE TO SURGE IN DATA BREACHES AND CYBERATTACKS TARGETING DATABASES TO FUEL MARKET GROWTH 208
9.2.1.1 Data Loss Prevention (DLP) 209
9.2.1.2 Data usage monitoring 210
9.2.1.3 Data compliance & governance 211
9.2.1.4 Data encryption 212
9.2.1.5 Data masking & tokenization 213
9.2.1.6 Access control 214
9.3 NETWORK SECURITY 215
9.3.1 RISE OF GENERATIVE AI TO ENHANCE NETWORK SECURITY MEASURES BY ENABLING MORE SOPHISTICATED THREAT DETECTION 215
9.3.1.1 Network Traffic Analysis (NTA) 216
9.3.1.2 Secure Access Service Edge (SASE) 217
9.3.1.3 Zero Trust Network Access (ZTNA) 218
9.3.1.4 Firewalls 219
9.3.1.5 Intrusion Detection/Prevention Systems (IDS/IPS) 220
9.3.1.6 VPNs & secure tunneling 221
 
9.4 ENDPOINT SECURITY 223
9.4.1 ENDPOINT SECURITY TO SAFEGUARD INDIVIDUAL DEVICES AND LEVERAGE ML ALGORITHMS TO PREDICT AND NEUTRALIZE THREATS IN REAL TIME 223
9.4.1.1 Endpoint Detection & Response (EDR) 224
9.4.1.2 Endpoint Protection Platforms (EPP) 225
9.5 APPLICATION SECURITY 226
9.5.1 DIFFUSION MODELS TO ENABLE GENERATION OF HIGHLY REALISTIC AND CONVINCING SYNTHETIC MEDIA 226
9.5.1.1 Static Application Security Testing (SAST) 227
9.5.1.2 Dynamic Application Security Testing (DAST) 228
9.5.1.3 LLM security 229
9.5.1.4 Runtime protection 231
9.5.1.5 Incident response & recovery 232
9.5.1.6 Governance, Risk, and Compliance (GRC) 233
10 GENERATIVE AI CYBERSECURITY MARKET, BY END USER 235
10.1 INTRODUCTION 236
10.1.1 END USERS: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 236
10.2 END USERS: GENERATIVE AI-BASED CYBERSECURITY 238
10.2.1 GOVERNMENT & DEFENSE 240
10.2.1.1 Generative AI becoming an essential tool for government agencies and defense organizations 240
10.2.2 BFSI 241
10.2.2.1 Significant increase in cyber threats targeting financial institutions and compliance to regulations to drive market 241
10.2.3 IT/ITES 242
10.2.3.1 Generative AI to automate routine security tasks by reducing reliance on human intervention and improving response times 242
10.2.4 HEALTHCARE & LIFE SCIENCES 244
10.2.4.1 Rise in cyberattacks targeting healthcare systems and implementation of Internet of Medical Things (IoMT) to boost market growth 244
10.2.5 RETAIL & ECOMMERCE 245
10.2.5.1 Exponential increase in online transactions and rising incidents of cyber threats to foster market growth 245
10.2.6 MANUFACTURING 246
10.2.6.1 Need to implement sophisticated cybersecurity protocols that can detect and prevent unauthorized access to sensitive data to propel market 246
10.2.7 ENERGY & UTILITIES 248
10.2.7.1 Need to protect critical infrastructure from cyberattacks to drive demand for generative AI cybersecurity 248
10.2.8 TELECOMMUNICATIONS 249
10.2.8.1 Proliferation of connected devices to demand advanced security measures to manage and mitigate real-time risks 249
 
10.2.9 AUTOMOTIVE, TRANSPORTATION, AND LOGISTICS 250
10.2.9.1 Rapid technological advancements and need to secure vehicle communication systems and software to drive market 250
10.2.10 MEDIA & ENTERTAINMENT 252
10.2.10.1 Need for increasing digital content distribution and online streaming services to propel market 252
10.2.11 OTHER END USERS 253
10.3 END USERS: CYBERSECURITY FOR GENERATIVE AI 255
10.3.1 CLOUD HYPERSCALERS 256
10.3.1.1 Need for AI to help detect anomalies, assess risks, and respond to threats more efficiently to foster market growth 256
10.3.2 MANAGED SECURITY SERVICE PROVIDERS 257
10.3.2.1 Need for monitoring, threat detection, incident response, and compliance management to accelerate market growth 257
10.3.3 GENERATIVE AI PROVIDERS 258
10.3.3.1 Generative AI providers to offer advanced solutions to enhance detection, prevention, and response to cyber threats 258
10.3.3.1.1 Foundation model/LLM developers 259
10.3.3.1.2 Data annotators 260
10.3.3.1.3 Content creation platform providers 261
10.3.3.1.4 Generative AI-as-a-service provider 263
11 GENERATIVE AI CYBERSECURITY MARKET, BY REGION 264
11.1 INTRODUCTION 265
11.2 NORTH AMERICA 267
11.2.1 NORTH AMERICA: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 267
11.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK 267
11.2.3 US 277
11.2.3.1 Robust technological infrastructure and culture of innovation to drive market 277
11.2.4 CANADA 278
11.2.4.1 Technological advancements and presence of leading companies to propel market 278
11.3 EUROPE 279
11.3.1 EUROPE: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 279
11.3.2 EUROPE: MACROECONOMIC OUTLOOK 279
11.3.3 UK 288
11.3.3.1 UK's commitment to leveraging AI to stay ahead of evolving cyber threats to propel market 288
11.3.4 GERMANY 289
11.3.4.1 Rising incidents of cyberattacks and government initiatives to actively promote AI research to drive market 289
11.3.5 FRANCE 290
11.3.5.1 Strong focus on R&D and government initiatives to foster AI innovation to fuel market growth 290
11.3.6 ITALY 291
11.3.6.1 Increasing cyber threats, advancements in AI technology, and growing awareness of need for robust security measures to foster market growth 291
11.3.7 SPAIN 292
11.3.7.1 Rising focus on AI in cybersecurity to drive adoption of generative AI cybersecurity solutions 292
11.3.8 NETHERLANDS 293
11.3.8.1 Integration with advanced technologies and collaborative approach to foster innovation to accelerate market growth 293
11.3.9 REST OF EUROPE 294
11.4 ASIA PACIFIC 295
11.4.1 ASIA PACIFIC: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 295
11.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK 296
11.4.3 CHINA 306
11.4.3.1 Need for dynamic environment for developing sophisticated cybersecurity solutions to foster market growth 306
11.4.4 INDIA 307
11.4.4.1 Increasing cyber threats and urgent need for enhanced security measures to trigger market growth 307
11.4.5 JAPAN 308
11.4.5.1 Rising incidence of cyberattacks and need for advanced cybersecurity solutions to fuel market growth 308
11.4.6 SOUTH KOREA 309
11.4.6.1 Rising focus on synthetic media and AI technologies and investment in AI education and training programs to propel market 309
11.4.7 SINGAPORE 310
11.4.7.1 Robust digital infrastructure, supportive government policies, and emphasis on innovative technologies to drive market 310
11.4.8 AUSTRALIA & NEW ZEALAND 311
11.4.8.1 Changing regulatory landscape and increased emphasis on cybersecurity policies and frameworks to fuel market growth 311
11.4.9 REST OF ASIA PACIFIC 312
11.5 MIDDLE EAST & AFRICA 313
11.5.1 MIDDLE EAST & AFRICA: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 313
11.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK 314
11.5.3 SAUDI ARABIA 322
11.5.3.1 Establishment of Center of Excellence (CoE) on Generative AI and R&D efforts on creating generative AI models to drive market 322
11.5.4 UAE 326
11.5.4.1 Major organizations to leverage generative AI for threat detection, risk assessment, and incident response 326
11.5.5 QATAR 330
11.5.5.1 QFC Data Protection Regulations to encourage organizations to invest in advanced cybersecurity measures 330
 
11.5.6 TURKEY 331
11.5.6.1 Turkish government's regulatory initiatives further enhancing country’s readiness to tackle cybersecurity challenges effectively 331
11.5.7 REST OF MIDDLE EAST 332
11.5.8 AFRICA 333
11.5.8.1 Collaborative efforts between academia and industry to drive innovation and development of new AI models and surge in tech start-ups to foster market growth 333
11.6 LATIN AMERICA 334
11.6.1 LATIN AMERICA: GENERATIVE AI CYBERSECURITY MARKET DRIVERS 334
11.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK 334
11.6.3 BRAZIL 343
11.6.3.1 Rapid digital transformation and increasing awareness of cyber threats to accelerate market growth 343
11.6.4 MEXICO 344
11.6.4.1 Technological innovation, strategic regional initiatives, and technological advancements in AI to boost market growth 344
11.6.5 ARGENTINA 345
11.6.5.1 Rapid advancements in cybersecurity landscape and development of local start-ups focused on AI-driven security solutions to foster market growth 345
11.6.6 REST OF LATIN AMERICA 346
12 COMPETITIVE LANDSCAPE 347
12.1 OVERVIEW 347
12.2 KEY PLAYER STRATEGIES/RIGHT TO WIN 347
12.3 REVENUE ANALYSIS 350
12.4 MARKET SHARE ANALYSIS 351
12.4.1 MARKET SHARE OF KEY PLAYERS OFFERING GENERATIVE AI-BASED CYBERSECURITY 351
12.4.1.1 Degree of competition 352
12.4.2 MARKET SHARE OF KEY PLAYERS OFFERING CYBERSECURITY FOR GENERATIVE AI 353
12.4.2.1 Degree of competition 354
12.5 BRAND/PRODUCT COMPARISON 356
12.5.1 BRAND/PRODUCT COMPARISON: GENERATIVE AI-BASED CYBERSECURITY 356
12.5.1.1 Security Copilot (Microsoft) 357
12.5.1.2 Purple AI (SentinelOne) 357
12.5.1.3 Sec-PALM (Google) 357
12.5.1.4 Charlotte AI (CrowdStrike) 358
12.5.1.5 Prevent (DarkTrace) 358
12.5.1.6 ZDX Copilot (Zscaler) 358
12.5.1.7 FortiAI (Fortinet) 358
12.5.1.8 Precision AI (Palo Alto) 358
 
12.5.2 BRAND/PRODUCT COMPARISON: CYBERSECURITY FOR GENERATIVE AI 359
12.5.2.1 QRadar (IBM) 360
12.5.2.2 AI Runtime Security (Palo Alto) 360
12.5.2.3 Nitro Enclaves (AWS) 360
12.5.2.4 Zero Trust Exchange (Zscaler) 361
12.5.2.5 Defender Cloud (Microsoft) 361
12.5.2.6 Watsonx.governance (IBM) 361
12.5.2.7 Nemo LLM Guardrails (NVIDIA) 361
12.5.2.8 TruLens (True Era) 361
12.6 COMPANY VALUATION AND FINANCIAL METRICS 362
12.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 363
12.7.1 KEY PLAYERS OFFERING GENERATIVE AI-BASED CYBERSECURITY 363
12.7.1.1 Stars 363
12.7.1.2 Emerging leaders 363
12.7.1.3 Pervasive players 363
12.7.1.4 Participants 363
12.7.1.5 Company footprint: key players, 2023 365
12.7.1.5.1 Company footprint 365
12.7.1.5.2 Offering footprint 366
12.7.1.5.3 Security type footprint 367
12.7.1.5.4 End-user footprint 368
12.7.1.5.5 Regional footprint 369
12.7.2 KEY PLAYERS OFFERING CYBERSECURITY SOLUTIONS FOR GENERATIVE AI 370
12.7.2.1 Stars 370
12.7.2.2 Emerging leaders 370
12.7.2.3 Pervasive players 370
12.7.2.4 Participants 370
12.7.2.5 Company footprint: key players, 2023 372
12.7.2.5.1 Company footprint 372
12.7.2.5.2 Offering footprint 373
12.7.2.5.3 Security-type footprint 374
12.7.2.5.4 End-user footprint 375
12.7.2.5.5 Regional footprint 375
12.8 COMPANY EVALUATION MATRIX: START-UPS/SMES, 2023 376
12.8.1 PROGRESSIVE COMPANIES 376
12.8.2 RESPONSIVE COMPANIES 376
12.8.3 DYNAMIC COMPANIES 376
12.8.4 STARTING BLOCKS 376
12.8.5 COMPETITIVE BENCHMARKING: START-UPS/SMES, 2023 378
12.8.5.1 Detailed list of key start-ups/SMEs 378
12.8.5.2 Competitive benchmarking of key start-ups/SMEs 381
 
12.9 COMPETITIVE SCENARIO AND TRENDS 382
12.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS 382
12.9.2 DEALS 384
13 COMPANY PROFILES 389
13.1 INTRODUCTION 389
13.2 KEY PLAYERS 390
13.2.1 MICROSOFT 390
13.2.1.1 Business overview 390
13.2.1.2 Products/Solutions/Services offered 391
13.2.1.3 Recent developments 392
13.2.1.4 MnM view 392
13.2.1.4.1 Right to win 392
13.2.1.4.2 Strategic choices made 392
13.2.1.4.3 Weaknesses and competitive threats 393
13.2.2 IBM 394
13.2.2.1 Business overview 394
13.2.2.2 Products/Solutions/Services offered 395
13.2.2.3 Recent developments 396
13.2.2.4 MnM view 397
13.2.2.4.1 Right to win 397
13.2.2.4.2 Strategic choices made 397
13.2.2.4.3 Weaknesses and competitive threats 397
13.2.3 AWS 398
13.2.3.1 Business overview 398
13.2.3.2 Products/Solutions/Services offered 399
13.2.3.3 Recent developments 400
13.2.3.4 MnM view 400
13.2.3.4.1 Right to win 400
13.2.3.4.2 Strategic choices made 400
13.2.3.4.3 Weaknesses and competitive threats 400
13.2.4 GOOGLE 401
13.2.4.1 Business overview 401
13.2.4.2 Products/Solutions/Services offered 402
13.2.4.3 Recent developments 403
13.2.4.4 MnM view 404
13.2.4.4.1 Right to win 404
13.2.4.4.2 Strategic choices made 404
13.2.4.4.3 Weaknesses and competitive threats 405
 
13.2.5 SENTITELONE 406
13.2.5.1 Business overview 406
13.2.5.2 Products/Solutions/Services offered 407
13.2.5.3 Recent developments 408
13.2.5.4 MnM view 409
13.2.5.4.1 Right to win 409
13.2.5.4.2 Strategic choices made 409
13.2.5.4.3 Weaknesses and competitive threats 410
13.2.6 NVIDIA 411
13.2.6.1 Business overview 411
13.2.6.2 Products/Solutions/Services offered 412
13.2.6.3 Recent developments 413
13.2.7 CISCO 414
13.2.7.1 Business overview 414
13.2.7.2 Products/Solutions/Services offered 415
13.2.7.3 Recent developments 416
13.2.8 CROWDSTRIKE 417
13.2.8.1 Business overview 417
13.2.8.2 Products/Solutions/Services offered 418
13.2.8.3 Recent developments 419
13.2.9 FORTINET 421
13.2.9.1 Business overview 421
13.2.9.2 Products/Products/Solutions/Services offered 422
13.2.9.3 Recent developments 423
13.2.10 ZSCALER 424
13.2.10.1 Business overview 424
13.2.10.2 Products/Products/Solutions/Services offered 425
13.2.10.3 Recent developments 426
13.2.11 TREND MICRO 428
13.2.12 PALO ALTO NETWORKS 428
13.2.13 BLACKBERRY 429
13.2.14 DARKTRACE 430
13.2.15 F5 431
13.2.16 OKTA 431
13.2.17 SANGFOR TECHNOLOGIES 432
13.2.18 VERACODE 432
13.2.19 LEXISNEXIS 433
13.2.20 SECURITYSCORECARD 433
13.2.21 SOPHOS 434
13.2.22 BROADCOM 435
13.2.23 TRELLIX 436
13.2.24 TENABLE 437
13.2.25 COHESITY 438
13.2.26 ELASTIC NV 439
13.2.27 SNYK 440
13.3 START-UPS/SMES 441
13.3.1 ABNORMAL SECURITY 441
13.3.2 ADVERSA AI 442
13.3.3 AQUASEC 443
13.3.4 BIGID 444
13.3.5 CHECKMARX 445
13.3.6 CREDO AI 446
13.3.7 CYBEREASON 446
13.3.8 DEEPKEEP 447
13.3.9 FLASHPOINT 448
13.3.10 LAKERA 449
13.3.11 MOSTLY AI 450
13.3.12 RECORDED FUTURE 450
13.3.13 SECUREFRAME 451
13.3.14 SKYFLOW 452
13.3.15 SLASHNEXT 453
13.3.16 TROJAI 454
13.3.17 VIRUSTOTAL 455
13.3.18 XENONSTACK 456
13.3.19 ZEROFOX 457
14 ADJACENT AND RELATED MARKETS 458
14.1 INTRODUCTION 458
14.2 GENERATIVE AI MARKET – GLOBAL FORECAST TO 2030 458
14.2.1 MARKET DEFINITION 458
14.2.2 MARKET OVERVIEW 458
14.2.2.1 Generative AI market, by offering 459
14.2.2.2 Generative AI market, by data modality 460
14.2.2.3 Generative AI market, by application 461
14.2.2.4 Generative AI market, by vertical 462
14.2.2.5 Generative AI market, by region 464
14.3 ARTIFICIAL INTELLIGENCE IN CYBERSECURITY MARKET – GLOBAL FORECAST TO 2028 465
14.3.1 MARKET DEFINITION 465
14.3.2 MARKET OVERVIEW 465
14.3.2.1 Artificial intelligence in cybersecurity market, by offering 466
14.3.2.2 Artificial intelligence in cybersecurity market, by security type 467
14.3.2.3 Artificial intelligence in cybersecurity market, by technology 468
14.3.2.4 Artificial intelligence in cybersecurity market, by application 469
14.3.2.5 Artificial intelligence in cybersecurity market, by vertical 470
14.3.2.6 Artificial intelligence in cybersecurity market, by region 472
15 APPENDIX 473
15.1 DISCUSSION GUIDE 473
15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 480
15.3 CUSTOMIZATION OPTIONS 482
15.4 RELATED REPORTS 482
15.5 AUTHOR DETAILS 483