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全球產生人工智慧網路安全市場規模研究（按產品、基於生成人工智慧的網路安全解決方案、產生人工智慧的網路安全解決方案、最終用戶和區域預測 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個工作天內

價格
簡介目錄

2023 年全球生成式 AI 網路安全市場價值約為 53.2 億美元，預計在 2024-2032 年預測期內將以超過 33.4% 的健康成長率成長。生成式人工智慧網路安全使用人工智慧模型，透過產生真實的威脅場景、模擬攻擊和識別漏洞來預測、偵測和應對網路威脅。應用包括創建用於訓練安全系統的合成資料、自動化威脅偵測和回應、增強入侵偵測系統以及開發針對複雜網路攻擊的強大防禦機制。這種方法透過利用人工智慧的預測和自適應能力來提高威脅情報、減少誤報並加強整體網路安全態勢。

在網路安全領域採用先進的生成式人工智慧解決方案正在迅速改變網路防禦的格局。透過以前所未有的準確性預測、偵測和緩解網路威脅，生成式 AI 技術，尤其是生成對抗網路 (GAN)，正在增強威脅情報並自動化回應流程。這些技術擴大被用來保護雲端服務和本地基礎設施，從而增強端點安全和存取管理控制。生成式人工智慧在增強網路安全營運和保護生成式人工智慧本機工作負載免受資料中毒和複雜惡意軟體等威脅方面的雙重作用正在推動市場擴張。

傳統方法無法應對的複雜網路威脅日益普遍，推動了市場的強勁成長。生成式人工智慧能夠模擬現實的威脅場景、創建用於訓練的合成資料以及自動化偵測和回應機制，從而顯著增強網路安全措施。此外，生成式人工智慧在網路安全中的整合正在透過自動化重複性任務並允許僱用具有一般能力而不是專門培訓的人員來解決行業中的技能差距。然而，對人工智慧治理的擔憂以及與影子 IT 相關的風險等挑戰需要強力的監督和全面的員工培訓，以防止濫用並確保遵守法規。

從地理位置來看，在技術進步、強大的醫療基礎設施和網路威脅高發的推動下，北美預計將主導市場。另一方面，由於公共和私人對人工智慧研發的廣泛投資以及網路犯罪事件的大幅增加，預計亞太地區將出現最快的成長，特別是在印度和中國等國家。

目錄

第 1 章：全球生成人工智慧網路安全市場執行摘要

  • 全球生成式人工智慧網路安全市場規模及預測（2022-2032）
  • 區域概要
  • 分部摘要
    • 透過提供
    • 基於產生人工智慧的網路安全解決方案
    • 透過產生人工智慧的網路安全解決方案
    • 按最終用戶
  • 主要趨勢
  • 經濟衰退的影響
  • 分析師推薦與結論

第 2 章：全球生成人工智慧網路安全市場定義與研究假設

  • 研究目的
  • 市場定義
  • 研究假設
    • 包容與排除
    • 限制
    • 供給側分析
      • 可用性
      • 基礎設施
      • 監管環境
      • 市場競爭
      • 經濟可行性（消費者的角度）
    • 需求面分析
      • 監理框架
      • 技術進步
      • 環境考慮
      • 消費者意識和接受度
  • 估算方法
  • 研究涵蓋的年份
  • 貨幣兌換率

第 3 章：全球生成人工智慧網路安全市場動態

  • 市場促進因素
    • 生成式人工智慧在對抗進階網路釣魚攻擊和深度偽造方面具有高效率
    • 網路威脅日益複雜
  • 市場挑戰
    • 對人工智慧治理以及影子 IT 相關風險的擔憂
    • 生成式人工智慧模型對劫持和資料中毒的敏感度
  • 市場機會
    • 生成式人工智慧有潛力解決網路安全產業持續存在的技能差距

第 4 章：全球生成人工智慧網路安全市場產業分析

  • 波特的五力模型
    • 供應商的議價能力
    • 買家的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭競爭
    • 波特五力模型的未來方法
    • 波特的五力影響分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社會的
    • 技術性
    • 環境的
    • 合法的
  • 頂級投資機會
  • 最佳制勝策略
  • 顛覆性趨勢
  • 產業專家視角
  • 分析師推薦與結論

第 5 章：全球生成式 AI 網路安全市場規模與預測：按產品分類 - 2022-2032 年

  • 細分儀表板
  • 全球生成式 AI 網路安全市場：提供 2022 年和 2032 年收入趨勢分析
    • 軟體
    • 服務

第 6 章：全球生成式 AI 網路安全市場規模與預測：按基於生成式 AI 的網路安全解決方案分類 - 2022-2032 年

  • 細分儀表板
  • 全球生成人工智慧網路安全市場：基於產生人工智慧的網路安全解決方案收入趨勢分析，2022 年和 2032 年
    • 威脅偵測和情報軟體
    • 風險評估軟體
    • 曝光管理軟體
    • 網路釣魚模擬與預防軟體
    • 修復指導軟體
    • 威脅追蹤平台
    • 程式碼分析軟體

第 7 章：全球生成人工智慧網路安全市場規模與預測：按產生人工智慧網路安全解決方案 - 2022-2032

  • 細分儀表板
  • 全球生成式 AI 網路安全市場：生成式 AI 網路安全解決方案收入趨勢分析，2022 年和 2032 年
    • 生成式人工智慧訓練資料安全軟體
    • 生成式 AI 模型安全軟體
    • 生成式人工智慧基礎設施安全軟體
    • 生成式人工智慧應用安全軟體

第 8 章：全球生成式 AI 網路安全市場規模與預測：按最終用戶分類 - 2022-2032 年

  • 細分儀表板
  • 全球生成式人工智慧網路安全市場：2022 年和 2032 年最終用戶收入趨勢分析
    • BFSI
    • 資訊科技與資訊科技服務
    • 電信
    • 政府與國防
    • 醫療保健與生命科學
    • 製造業
    • 媒體與娛樂
    • 零售與電子商務
    • 能源與公用事業
    • 汽車、運輸與物流
    • 其他企業

第 9 章：全球生成人工智慧網路安全市場規模與預測：按地區 - 2022-2032

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 西班牙
    • 義大利
    • 歐洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 亞太地區其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 南非
    • 中東和非洲其他地區

第 10 章：競爭情報

  • 重點企業SWOT分析
  • 頂級市場策略
  • 公司簡介
    • Microsoft (US)
      • 關鍵訊息
      • 概述
      • 財務（視數據可用性而定）
      • 產品概要
      • 市場策略
    • 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：研究過程

  • 研究過程
    • 資料探勘
    • 分析
    • 市場預測
    • 驗證
    • 出版
  • 研究屬性
簡介目錄

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