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全球产生人工智慧网路安全市场规模研究（按产品、基于生成人工智慧的网路安全解决方案、产生人工智慧的网路安全解决方案、最终用户和区域预测 2022-2032）

Global Generative AI Cybersecurity Market Size Study by Offering, by Generative AI-based Cybersecurity Solutions, by Cybersecurity Solutions for Generative AI, by End-user and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 285 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2023 年全球生成式 AI 网路安全市场价值约为 53.2 亿美元，预计在 2024-2032 年预测期内将以超过 33.4% 的健康成长率成长。生成式人工智慧网路安全使用人工智慧模型，透过产生真实的威胁场景、模拟攻击和识别漏洞来预测、侦测和应对网路威胁。应用包括创建用于训练安全系统的合成资料、自动化威胁侦测和回应、增强入侵侦测系统以及开发针对复杂网路攻击的强大防御机制。这种方法透过利用人工智慧的预测和自适应能力来提高威胁情报、减少误报并加强整体网路安全态势。

在网路安全领域采用先进的生成式人工智慧解决方案正在迅速改变网路防御的格局。透过以前所未有的准确性预测、侦测和缓解网路威胁，生成式 AI 技术，尤其是生成对抗网路 (GAN)，正在增强威胁情报并自动化回应流程。这些技术越来越多地被用来保护云端服务和本地基础设施，从而增强端点安全和存取管理控制。生成式人工智慧在增强网路安全营运和保护生成式人工智慧本机工作负载免受资料中毒和复杂恶意软体等威胁方面的双重作用正在推动市场扩张。

传统方法无法应对的复杂网路威胁日益普遍，推动了市场的强劲成长。生成式人工智慧能够模拟现实的威胁场景、创建用于训练的合成资料以及自动化侦测和回应机制，从而显着增强网路安全措施。此外，生成式人工智慧在网路安全中的整合正在透过自动化重复性任务并允许僱用具有一般能力而不是专门培训的人员来解决行业中的技能差距。然而，对人工智慧治理的担忧以及与影子 IT 相关的风险等挑战需要强有力的监督和全面的员工培训，以防止滥用并确保遵守法规。

从地理位置来看，在技术进步、强大的医疗基础设施和网路威胁高发的推动下，北美预计将主导市场。另一方面，由于公共和私人对人工智慧研发的广泛投资以及网路犯罪事件的大幅增加，预计亚太地区将出现最快的成长，特别是在印度和中国等国家。

目录

第 1 章：全球生成人工智慧网路安全市场执行摘要

  • 全球生成式人工智慧网路安全市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 透过提供
    • 基于产生人工智慧的网路安全解决方案
    • 透过产生人工智慧的网路安全解决方案
    • 按最终用户
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球生成人工智慧网路安全市场定义与研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包容与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：全球生成人工智慧网路安全市场动态

  • 市场驱动因素
    • 生成式人工智慧在对抗进阶网路钓鱼攻击和深度伪造方面具有高效率
    • 网路威胁日益复杂
  • 市场挑战
    • 对人工智慧治理以及影子 IT 相关风险的担忧
    • 生成式人工智慧模型对劫持和资料中毒的敏感度
  • 市场机会
    • 生成式人工智慧有潜力解决网路安全产业持续存在的技能差距

第 4 章：全球生成人工智慧网路安全市场产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的五力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：全球生成式 AI 网路安全市场规模与预测：按产品分类 - 2022-2032 年

  • 细分仪表板
  • 全球生成式 AI 网路安全市场：提供 2022 年和 2032 年收入趋势分析
    • 软体
    • 服务

第 6 章：全球生成式 AI 网路安全市场规模与预测：按基于生成式 AI 的网路安全解决方案划分 - 2022-2032 年

  • 细分仪表板
  • 全球生成人工智慧网路安全市场：基于产生人工智慧的网路安全解决方案收入趋势分析，2022 年和 2032 年
    • 威胁侦测和情报软体
    • 风险评估软体
    • 曝光管理软体
    • 网路钓鱼模拟与预防软体
    • 修復指导软体
    • 威胁追踪平台
    • 程式码分析软体

第 7 章：全球生成人工智慧网路安全市场规模与预测：按产生人工智慧网路安全解决方案 - 2022-2032

  • 细分仪表板
  • 全球生成式 AI 网路安全市场：生成式 AI 网路安全解决方案收入趋势分析，2022 年和 2032 年
    • 生成式人工智慧训练资料安全软体
    • 生成式 AI 模型安全软体
    • 生成式人工智慧基础设施安全软体
    • 生成式人工智慧应用安全软体

第 8 章：全球生成式 AI 网路安全市场规模与预测：按最终用户划分 - 2022-2032 年

  • 细分仪表板
  • 全球生成式人工智慧网路安全市场：2022 年和 2032 年最终用户收入趋势分析
    • BFSI
    • 资讯科技与资讯科技服务
    • 电信
    • 政府与国防
    • 医疗保健与生命科学
    • 製造业
    • 媒体与娱乐
    • 零售与电子商务
    • 能源与公用事业
    • 汽车、运输与物流
    • 其他企业

第 9 章：全球生成人工智慧网路安全市场规模与预测：按地区 - 2022-2032

  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 西班牙
    • 义大利
    • 欧洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 中东和非洲其他地区

第 10 章：竞争情报

  • 重点企业SWOT分析
  • 顶级市场策略
  • 公司简介
    • Microsoft (US)
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • 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)

第 11 章：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

The global Generative AI Cybersecurity Market is valued at approximately USD 5.32 billion in 2023 and is anticipated to grow with a healthy growth rate of more than 33.4% over the forecast period 2024-2032. Generative AI cybersecurity uses AI models to predict, detect, and counteract cyber threats by generating realistic threat scenarios, simulating attacks, and identifying vulnerabilities. Applications include creating synthetic data for training security systems, automating threat detection and response, enhancing intrusion detection systems, and developing robust defense mechanisms against sophisticated cyberattacks. This approach improves threat intelligence, reduces false positives, and strengthens overall cybersecurity posture by leveraging the predictive and adaptive capabilities of AI.

The adoption of advanced generative AI solutions in cybersecurity is rapidly transforming the landscape of cyber defense. By predicting, detecting, and mitigating cyber threats with unprecedented accuracy, generative AI technologies, especially Generative Adversarial Networks (GANs), are augmenting threat intelligence and automating response processes. These technologies are increasingly being leveraged to secure both cloud services and on-premise infrastructures, enhancing endpoint security and access management controls. The dual role of generative AI, in both enhancing cybersecurity operations and safeguarding generative AI-native workloads from threats like data poisoning and complex malware, is driving market expansion.

The market's robust growth is propelled by the rising prevalence of sophisticated cyber threats that traditional methods fail to counteract. Generative AI's ability to simulate realistic threat scenarios, create synthetic data for training, and automate detection and response mechanisms significantly bolsters cybersecurity measures. Furthermore, the integration of generative AI in cybersecurity is addressing the skills gap in the industry by automating repetitive tasks and enabling the employment of personnel with general aptitude rather than specialized training. However, challenges such as concerns over AI governance and the risks associated with shadow IT necessitate robust oversight and comprehensive employee training to prevent misuse and ensure compliance with regulations.

Geographically, North America is expected to dominate the market, driven by technological advancements, a strong healthcare infrastructure, and the high prevalence of cyber threats. The Asia Pacific region, on the other hand, is projected to witness the fastest growth, fueled by extensive public and private investments in AI research and development and a significant rise in cybercrime incidents, particularly in countries like India and China.

Major market players included in this report are:

  • 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)

The detailed segments and sub-segment of the market are explained below:

By Offering:

  • Software
  • Services

By Generative AI-based Cybersecurity Solutions:

  • 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 Solutions for Generative AI:

  • Generative AI Training Data Security Software
  • Generative AI Model Security Software
  • Generative AI Infrastructure Security Software
  • Generative AI Application Security Software

By End-user:

  • BFSI
  • IT & ITeS
  • Telecommunications
  • Government & Defense
  • Healthcare & Life Sciences
  • Manufacturing
  • Media & Entertainment
  • Retail & E-Commerce
  • Energy & Utilities
  • Automotive, Transportation & Logistics
  • Other Enterprises

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • RoLA
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • RoMEA

Years considered for the study are as follows:

  • Historical year - 2022
  • Base year - 2023
  • Forecast period - 2024 to 2032

Key Takeaways:

  • Market Estimates & Forecast for 10 years from 2022 to 2032.
  • Annualized revenues and regional level analysis for each market segment.
  • Detailed analysis of geographical landscape with Country level analysis of major regions.
  • Competitive landscape with information on major players in the market.
  • Analysis of key business strategies and recommendations on future market approach.
  • Analysis of competitive structure of the market.
  • Demand side and supply side analysis of the market.

Table of Contents

Chapter 1. Global Generative AI Cybersecurity Market Executive Summary

  • 1.1. Global Generative AI Cybersecurity Market Size & Forecast (2022- 2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By Offering
    • 1.3.2. By Generative AI-based Cybersecurity Solutions
    • 1.3.3. By Cybersecurity Solutions for Generative AI
    • 1.3.4. By End-user
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Generative AI Cybersecurity Market Definition and Research Assumptions

  • 2.1. Research Objective
  • 2.2. Market Definition
  • 2.3. Research Assumptions
    • 2.3.1. Inclusion & Exclusion
    • 2.3.2. Limitations
    • 2.3.3. Supply Side Analysis
      • 2.3.3.1. Availability
      • 2.3.3.2. Infrastructure
      • 2.3.3.3. Regulatory Environment
      • 2.3.3.4. Market Competition
      • 2.3.3.5. Economic Viability (Consumer's Perspective)
    • 2.3.4. Demand Side Analysis
      • 2.3.4.1. Regulatory frameworks
      • 2.3.4.2. Technological Advancements
      • 2.3.4.3. Environmental Considerations
      • 2.3.4.4. Consumer Awareness & Acceptance
  • 2.4. Estimation Methodology
  • 2.5. Years Considered for the Study
  • 2.6. Currency Conversion Rates

Chapter 3. Global Generative AI Cybersecurity Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. High efficiency of Generative AI in combating advanced phishing attacks and deepfakes
    • 3.1.2. Increasing sophistication of cyber threats
  • 3.2. Market Challenges
    • 3.2.1. Concerns about AI governance and the risks associated with shadow IT
    • 3.2.2. Susceptibility of generative AI models to hijacking and data poisoning
  • 3.3. Market Opportunities
    • 3.3.1. Generative AI's potential to address the persistent skills gap in the cybersecurity industry

Chapter 4. Global Generative AI Cybersecurity 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
    • 4.1.7. Porter's 5 Force Impact Analysis
  • 4.2. PESTEL Analysis
    • 4.2.1. Political
    • 4.2.2. Economical
    • 4.2.3. Social
    • 4.2.4. Technological
    • 4.2.5. Environmental
    • 4.2.6. Legal
  • 4.3. Top investment opportunity
  • 4.4. Top winning strategies
  • 4.5. Disruptive Trends
  • 4.6. Industry Expert Perspective
  • 4.7. Analyst Recommendation & Conclusion

Chapter 5. Global Generative AI Cybersecurity Market Size & Forecasts by Offering 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global Generative AI Cybersecurity Market: Offering Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 5.2.1. Software
    • 5.2.2. Services

Chapter 6. Global Generative AI Cybersecurity Market Size & Forecasts by Generative AI-based Cybersecurity Solutions 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global Generative AI Cybersecurity Market: Generative AI-based Cybersecurity Solutions Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 6.2.1. Threat Detection & Intelligence Software
    • 6.2.2. Risk Assessment Software
    • 6.2.3. Exposure Management Software
    • 6.2.4. Phishing Simulation & Prevention Software
    • 6.2.5. Remediation Guidance Software
    • 6.2.6. Threat Hunting Platforms
    • 6.2.7. Code Analysis Software

Chapter 7. Global Generative AI Cybersecurity Market Size & Forecasts by Cybersecurity Solutions for Generative AI 2022-2032

  • 7.1. Segment Dashboard
  • 7.2. Global Generative AI Cybersecurity Market: Cybersecurity Solutions for Generative AI Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 7.2.1. Generative AI Training Data Security Software
    • 7.2.2. Generative AI Model Security Software
    • 7.2.3. Generative AI Infrastructure Security Software
    • 7.2.4. Generative AI Application Security Software

Chapter 8. Global Generative AI Cybersecurity Market Size & Forecasts by End-user 2022-2032

  • 8.1. Segment Dashboard
  • 8.2. Global Generative AI Cybersecurity Market: End-user Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 8.2.1. BFSI
    • 8.2.2. IT & ITeS
    • 8.2.3. Telecommunications
    • 8.2.4. Government & Defense
    • 8.2.5. Healthcare & Life Sciences
    • 8.2.6. Manufacturing
    • 8.2.7. Media & Entertainment
    • 8.2.8. Retail & E-Commerce
    • 8.2.9. Energy & Utilities
    • 8.2.10. Automotive, Transportation & Logistics
    • 8.2.11. Other Enterprises

Chapter 9. Global Generative AI Cybersecurity Market Size & Forecasts by Region 2022-2032

  • 9.1. North America Generative AI Cybersecurity Market
    • 9.1.1. U.S. Generative AI Cybersecurity Market
      • 9.1.1.1. Offering breakdown size & forecasts, 2022-2032
      • 9.1.1.2. Generative AI-based Cybersecurity Solutions breakdown size & forecasts, 2022-2032
      • 9.1.1.3. Cybersecurity Solutions for Generative AI breakdown size & forecasts, 2022-2032
      • 9.1.1.4. End-user breakdown size & forecasts, 2022-2032
    • 9.1.2. Canada Generative AI Cybersecurity Market
  • 9.2. Europe Generative AI Cybersecurity Market
    • 9.2.1. U.K. Generative AI Cybersecurity Market
    • 9.2.2. Germany Generative AI Cybersecurity Market
    • 9.2.3. France Generative AI Cybersecurity Market
    • 9.2.4. Spain Generative AI Cybersecurity Market
    • 9.2.5. Italy Generative AI Cybersecurity Market
    • 9.2.6. Rest of Europe Generative AI Cybersecurity Market
  • 9.3. Asia-Pacific Generative AI Cybersecurity Market
    • 9.3.1. China Generative AI Cybersecurity Market
    • 9.3.2. India Generative AI Cybersecurity Market
    • 9.3.3. Japan Generative AI Cybersecurity Market
    • 9.3.4. Australia Generative AI Cybersecurity Market
    • 9.3.5. South Korea Generative AI Cybersecurity Market
    • 9.3.6. Rest of Asia Pacific Generative AI Cybersecurity Market
  • 9.4. Latin America Generative AI Cybersecurity Market
    • 9.4.1. Brazil Generative AI Cybersecurity Market
    • 9.4.2. Mexico Generative AI Cybersecurity Market
    • 9.4.3. Rest of Latin America Generative AI Cybersecurity Market
  • 9.5. Middle East & Africa Generative AI Cybersecurity Market
    • 9.5.1. Saudi Arabia Generative AI Cybersecurity Market
    • 9.5.2. South Africa Generative AI Cybersecurity Market
    • 9.5.3. Rest of Middle East & Africa Generative AI Cybersecurity Market

Chapter 10. Competitive Intelligence

  • 10.1. Key Company SWOT Analysis
  • 10.2. Top Market Strategies
  • 10.3. Company Profiles
    • 10.3.1. Microsoft (US)
      • 10.3.1.1. Key Information
      • 10.3.1.2. Overview
      • 10.3.1.3. Financial (Subject to Data Availability)
      • 10.3.1.4. Product Summary
      • 10.3.1.5. Market Strategies
    • 10.3.2. IBM (US)
    • 10.3.3. Google (US)
    • 10.3.4. SentinelOne (US)
    • 10.3.5. AWS (US)
    • 10.3.6. NVIDIA (US)
    • 10.3.7. Cisco (US)
    • 10.3.8. CrowdStrike (US)
    • 10.3.9. Fortinet (US)
    • 10.3.10. Zscaler (US)
    • 10.3.11. Trend Micro (Japan)
    • 10.3.12. Palo Alto Networks (US)
    • 10.3.13. BlackBerry (Canada)
    • 10.3.14. Darktrace (UK)
    • 10.3.15. F5 (US)

Chapter 11. Research Process

  • 11.1. Research Process
    • 11.1.1. Data Mining
    • 11.1.2. Analysis
    • 11.1.3. Market Estimation
    • 11.1.4. Validation
    • 11.1.5. Publishing
  • 11.2. Research Attributes