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到 2030 年網路安全中的人工智慧 (AI) 市場預測：依細分市場和地區分類的全球分析
市場調查報告書
商品編碼
1358955

到 2030 年網路安全中的人工智慧 (AI) 市場預測：依細分市場和地區分類的全球分析

Artificial Intelligence in Cybersecurity Market Forecasts to 2030 - Global Analysis By Component (Hardware, Software and Services), Security Type, Deployment Type, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球網路安全人工智慧 (AI) 市場預計到 2023 年將達到 224 億美元，到 2030 年將達到 1004 億美元，預測期內年複合成長率為 23.9%。

人工智慧 (AI) 使識別、預防和回應網路威脅變得更加容易，從而對網路安全產生重大影響。人工智慧系統即時分析大量資料，以發現指向網路攻擊的奇怪模式和行為。這包括惡意軟體、病毒和其他危險軟體。可以教導機器學習演算法檢測已知風險並適應新風險。人工智慧驅動的異常偵測系統提供典型網路行為的基線，並在違反該基線時發出警報。這使您能夠發現以前未發現的攻擊方法和內部風險。

根據消費者技術協會的數據，全球 44% 的組織已部署人工智慧應用程式來偵測和阻止安全入侵。

對更好的安全措施的需求不斷成長

隨著網路攻擊變得更加複雜和頻繁，組織迅速意識到需要改進的現代化安全解決方案。許多相關人員現在高度關注網路風險。因此，迫切需要對組織的系統、網路和資料實施安全措施，以減輕已識別的風險。網路攻擊和資料外洩的頻率不斷增加，增加了對安全解決方案的需求。此外，企業越來越認知到採取主動網路安全措施的必要性，包括更好的網路安全和威脅建模解決方案，這正在推動市場擴張。

誹謗攻擊造成的錯誤訊息

人工智慧驅動的安全系統存在產生誤報或無法識別真正威脅的風險。這些錯誤可能會導致時間和資源的損失以及無法識別漏洞。駭客可以利用人工智慧來發動專門設計的攻擊，以破壞基於人工智慧的安全系統。這些攻擊通常被稱為對抗性攻擊，可以偽造輸入資料，使人工智慧演算法得出錯誤的結論，從而阻礙市場成長。

法規遵從性和行業標準要求

威脅建模已成為由法規合規標準和行業標準驅動的安全計劃的有組織的一部分，例如通用資料保護規範(GDPR)、PCI-DSS（支付卡行業資料安全標準）和NIST（美國國家標準與技術研究院） ). 經常被要求。政府機構現在越來越需要改進的安全解決方案，促使網路安全領域的人工智慧市場蓬勃發展。上市公司和私人公司增加的技術投資也推動了人工智慧在網路安全市場的使用。

人工智慧無法應對現代複雜的危險

深度學習、神經網路、遺傳演算法和機器學習等人工智慧技術和方法都是基於過去的經驗。進階持續性威脅 (APT) 是一種網路攻擊，可讓使用者未經授權存取網路並在相當長的時間內保持隱藏狀態。雖然某些 APT 行為可能與 AI 可以偵測的過去事件類似，但新的 APT 缺乏過去的經驗，需要新穎的方式來呼叫應用程式介面 (API) 和系統 - 採用尖端的方法來存取資源。真正抵禦複雜的現代危險不能依賴過去的病毒和攻擊。這個市場受到人工智慧無法應對高階威脅的限制。

COVID-19 的影響：

許多頂級網路安全公司將當前的危機視為審查和重組當前策略並開發更複雜產品系列的機會。隨著公司擴大實施在家工作政策，COVID-19 的爆發正在推動對尖端解決方案的需求。在家工作的人們以及使用潛在風險網路和設備的其他用戶推動了對數位產品和服務的需求不斷成長，這促使公司投資於機器學習和深度學習演算法。它已經成為。

機器學習領域預計將在預測期內成為最大的領域

機器學習領域預計將出現利潤豐厚的成長，隨著這些深度學習在終端用途產業中迅速傳播，機器學習技術將急劇成長。 Google 和 IBM 等大公司開始使用機器學習進行威脅偵測和電子郵件過濾。公司正在利用機器學習和深度學習來加強其網路安全協議。此外，機器學習平台正日益成為自動化監控、識別異常以及導航安全系統產生的大量資料的首選工具。

詐欺偵測/詐欺領域預計在預測期內將經歷最高的年複合成長率。

人工智慧（AI）在網路安全中的使用將作為詐欺偵測和詐欺預防的預防措施得到推廣，因此詐欺偵測/詐欺預防領域預計在預測期內將以最高年複合成長率成長。由於詐欺發生率不斷增加，機器學習已成為政府和其他最終用戶增強預防詐欺能力的寶貴技術。因此，人工智慧工具可能會更頻繁地用於消除詐騙、電子郵件網路釣魚和詐欺記錄。企業正在轉向整合威脅管理，以保護其數位資產免受間諜軟體感染文件、網路釣魚攻擊、詐欺的網站訪問和特洛伊木馬 (UTM) 等威脅，從而推動市場發展。

佔比最大的地區：

由於物聯網、5G 和 Wi-Fi 6 的引入，網路連接設備數量增加，預計北美將在預測期內佔據最大的市場佔有率。 5G 網路的擴張是由汽車、醫療保健、政府、能源和採礦業的公司推動的，這些產業可能成為駭客的接入點。大公司可能會投資機器學習、進階分析、資產映射和即時估值視覺化平台。自然語言處理、機器學習（ML）和神經網路預計將在北美廣泛應用，以阻止攻擊、檢測奇怪的用戶行為並識別其他異常模式，並提高該地區的市場成長。

複合年複合成長率最高的地區：

由於經濟成長和數位化程度不斷提高，亞太地區已成為網路攻擊的熱點地區，預計在預測期內年複合成長率最高。為了防範新的威脅，現在對先進網路安全解決方案的需求不斷成長，特別是那些由人工智慧驅動的解決方案。亞太地區的許多政府已發起計劃，鼓勵在網路安全領域創建和使用人工智慧。此類項目通常包括研發資金和市場驅動的法規支援。

免費客製化服務：

訂閱此報告的客戶可以存取以下免費自訂選項之一：

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 家公司）
    • 主要企業SWOT分析（最多3家企業）
  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和年複合成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章 執行摘要

第2章 前言

  • 概述
  • 利害關係人
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 調查來源
    • 主要調查來源
    • 二次調查來源
    • 先決條件

第3章 市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 用途分析
  • 最終用戶分析
  • 新興市場
  • 新型冠狀病毒感染疾病（COVID-19）的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章 網路安全領域的全球人工智慧 (AI) 市場：依組成部分

  • 硬體
    • 處理器
      • 用途積體電路(ASIC)
      • 現場可程式閘陣列 (FPGA)
      • 圖形處理單元（GPU）
      • 記憶體保護單元 (MPU)
    • 記憶
    • 通訊網路
  • 軟體
    • 人工智慧解決方案
    • 人工智慧平台
      • 應用程式介面（API）
      • 機器學習框架
  • 服務
    • 支援與維護
    • 部署與整合

第6章 網路安全領域的全球人工智慧 (AI) 市場：依安全類型分類

  • 應用程式安全
  • 端點安全
  • 網路安全
  • 雲端安全

第7章 網路安全市場中的全球人工智慧 (AI)：依部署類型

  • 本地
  • 雲

第8章 網路安全領域的全球人工智慧 (AI) 市場：依技術分類

  • 上下文感知計算
  • 機器學習
    • 深度學習
    • 強化學習
    • 監督學習
    • 無監督學習
  • 自然語言處理（NLP）
  • 其他技術

第9章 網路安全領域的全球人工智慧 (AI) 市場：依用途

  • 防毒/惡意軟體
  • 防止資料損失預防
  • 詐欺偵測/詐欺預防
  • 身分和存取管理
  • 入侵偵測/預防系統
  • 風險與合規管理
  • 安全和漏洞管理
  • 威脅情報
  • 統一威脅管理
  • 其他用途

第10章 網路安全領域的全球人工智慧 (AI) 市場：依最終用戶分類

  • 銀行、金融服務和保險 (BFSI)
  • 汽車和交通
  • 公司
  • 政府和國防
  • 衛生保健
  • 基礎設施
  • 製造業
  • 零售
  • 其他最終用戶

第11章全球人工智慧（AI）網路安全市場：依地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第12章進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第13章公司簡介

  • Micron Technology, Inc.
  • Amazon Web Services, Inc.
  • Cylance Inc.（BlackBerry）
  • FireEye, Inc.
  • Fortinet, Inc.
  • Acalvio Technologies, Inc
  • Intel Corporation
  • IBM Corporation
  • LexisNexis
  • Darktrace
  • Microsoft Corporation
  • Samsung Electronics Co. Ltd.
  • Cisco Systems, Inc.
  • Gen Digital Inc.
  • NVIDIA Corporation
  • McAfee LLC
  • Palo Alto Networks Inc.
  • Cylance Inc.
Product Code: SMRC23827

According to Stratistics MRC, the Global Artificial Intelligence in Cybersecurity Market is accounted for $22.4 billion in 2023 and is expected to reach $100.4 billion by 2030 growing at a CAGR of 23.9% during the forecast period. Artificial intelligence (AI) has a big impact on cybersecurity, by making it easier to identify, stop, and respond to cyber threats. Massive amounts of data can be analysed in real-time by AI systems, which can then spot odd patterns or behaviors that can point to a cyberattack. Malware, viruses, and other dangerous software are among the things that can be found. Algorithms for machine learning can be taught to detect known risks and adjust to new ones. Anomaly detection systems powered by AI provide a baseline of typical network behavior and issue alarms when this baseline is violated. This can be used to find previously undiscovered attack methods or insider risks.

According to the Consumer Technology Association, 44% of organizations across the globe are implementing AI applications to detect and deter security intrusions.

Market Dynamics:

Driver:

Increase in demand for better security measures

As cyberattacks are becoming more sophisticated and frequent, organizations are rapidly feeling the need for improved and modern security solutions. Nowadays, a number of stakeholders are very concerned about cyber dangers. As a result, implementing safeguards to reduce the identified hazards is urgently needed for an organization's systems, networks, and data. Due to the increasing frequency of cyberattacks and data breaches, there is a growing need for security solutions. Additionally, the need of proactive cyber security measures, such as better cyber security and threat modelling solutions, is increasingly being recognized by enterprises, which is fuelling market expansion.

Restraint:

False alarms with defamatory attacks

Security systems powered by AI run the risk of producing false alarms or failing to identify genuine threats. These errors may result in the loss of time and resources or the failure to identify vulnerabilities. AI can be used by hackers to create attacks that are intended to especially harm AI-based security systems. These assaults, often referred to as adversarial attacks, might fudge the input data to lead AI algorithms to draw the wrong conclusions thus hampering the growth of the market.

Opportunity:

Requirements for regulatory compliance and industry standards

Threat modeling is frequently required of organizations as part of security programs by regulatory compliance standards and industry standards like the General Data Protection Regulation (GDPR), Payment Card Industry Data Security Standard (PCI-DSS), and National Institute of Standards and Technology (NIST). Government agencies now have an even greater need for improved security solutions, which in turn is fueling the market for AI in cybersecurity. The growing technical investment of both public and private companies is also encouraging the use of AI in the cybersecurity market.

Threat:

AI's inability to combat modern and complex dangers

AI techniques and methods, such as deep learning, neural networks, genetic algorithms, and machine learning, are founded on prior experiences. An advanced persistent threat (APT) is a network attack where a user gains access to a network without authorization and remains hidden for a considerable amount of time. While some APT behaviors may be similar to past events that AIs can detect them, new APTs have no prior experiences and are therefore equipped with novel ways to invoke application programming interfaces (APIs) and cutting-edge approaches to access system resources. Real defence against complex, modern dangers cannot rely on previous viruses or assaults. This market is being constrained by AI's incapacity to counter advanced threats.

COVID-19 Impact:

A lot of top cybersecurity organizations see the current crisis as a chance to review and restructure their current strategies and develop more complex product portfolios. The COVID-19 outbreak has boosted the demand for cutting-edge solutions as firms commit more to work-from-home policies. Due to a rise in demand for digital goods and services brought on by telecommuting workers and other users of potentially risky networks and devices, businesses have been pushed to invest money in machine learning and deep learning algorithms.

The machine learning segment is expected to be the largest during the forecast period

The machine learning segment is estimated to have a lucrative growth, as these deep learning spreads quickly throughout end-use industries, machine-learning technologies will grow dramatically. Leading corporations like Google and IBM are beginning to use machine learning for threat detection and email filtering. Businesses are making use of machine learning and deep learning to enhance cybersecurity protocols. Additionally, ML platforms are becoming more and more well-liked as a tool to automate monitoring, identify anomalies, and navigate the vast amounts of data generated by security systems.

The fraud detection/anti-fraud segment is expected to have the highest CAGR during the forecast period

The fraud detection/anti-fraud segment is anticipated to witness the highest CAGR growth during the forecast period, as the use of artificial intelligence (AI) in cybersecurity will be pushed as preventative measures for fraud detection and anti-fraud. As a result of an increase in fraud incidences, machine learning has become a beneficial technique for enhancing the capacity of governments and other end users to prevent fraudulent actions. AI tools may therefore be used more frequently to get rid of fraud, email phishing, and fraudulent records. To safeguard their digital assets from threats including spyware-infected files, phishing assaults, unauthorized website access, and trojans (UTM), businesses are more interested in unified threat management thereby encouraging the market.

Region with largest share:

North America is projected to hold the largest market share during the forecast period owing to the increase in network-connected devices brought on by the adoption of IoT, 5G, and Wi-Fi 6 is primarily responsible for the rise. The expansion of the 5G network has been driven by businesses in the automotive, healthcare, government, energy, and mining industries, which might be a point of access for hackers. Leading companies are likely to invest money in platforms for machine learning, sophisticated analytics, asset mapping, and visualization for a real-time evaluation. Natural language processing, machine learning (ML), and neural networks are expected to be widely used in North America to thwart assaults, detect odd user behaviour, and identify other anomalous patterns thus enhancing the growth of the market in this region.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR over the forecast period as this region has been a hotspot for cyberattacks because of its economic expansion and rising level of digitalisation. To protect against emerging threats, there is now a larger demand for advanced cybersecurity solutions, particularly those that are AI-powered. Numerous governments in the APAC area have started initiatives to encourage the creation and use of AI in cybersecurity because they understand how important it is. These projects frequently include financing for R&D as well as regulatory assistance which drive the market.

Key players in the market:

Some of the key players profiled in the Artificial Intelligence in Cybersecurity Market include: Micron Technology, Inc., Amazon Web Services, Inc., Cylance Inc. (BlackBerry), FireEye, Inc., Fortinet, Inc., Acalvio Technologies, Inc, Intel Corporation, IBM Corporation, LexisNexis, Darktrace, Microsoft Corporation, Samsung Electronics Co. Ltd., Cisco Systems, Inc., Gen Digital Inc., NVIDIA Corporation, McAfee LLC, Palo Alto Networks Inc. and Cylance Inc.

Key Developments:

In September 2023, Cylance Inc. (BlackBerry) Launches 'Intrinsically Safe' Certified Solution for Hazardous Materials Carriers the new series is backed by an 'Intrinsically Safe' certification designation, enabling BlackBerry Radar, an asset tracking solution, to target transportation and logistics companies that move hazardous materials, including fuel haulers, tank carriers, ocean shipping lines and railroads.

In September 2023, Intel presents a software-defined, silicon-accelerated approach built on a foundation of openness, choice, trust and security. which allows the hardware to process the data without it ever being decrypted. In essence, the processor performs calculations directly on the encrypted data.

In August 2023, Micron Launches Memory Expansion Module Portfolio to Accelerate CXL 2.0 Adoption. Additionally, the CZ120 modules are capable of running up to 36GB/s memory read/write bandwidth1 and augment standard server systems when incremental memory capacity and bandwidth is required.

Components Covered:

  • Hardware
  • Software
  • Services

Security Types Covered:

  • Application Security
  • Endpoint Security
  • Network Security
  • Cloud Security

Deployment Types Covered:

  • On-Premises
  • Cloud

Technologies Covered:

  • Context-Aware Computing
  • Machine Learning
  • Natural Language Processing (NLP)
  • Other Technologies

Applications Covered:

  • Antivirus/ Malware
  • Data Loss Prevention
  • Fraud Detection/Anti-Fraud
  • Identity And Access Management
  • Intrusion Detection/ Prevention System
  • Risk And Compliance Management
  • Security & Vulnerability Management
  • Threat Intelligence
  • Unified Threat Management
  • Other Applications

End Users Covered:

  • BFSI
  • Automotive & Transportation
  • Enterprise
  • Government & Defense
  • Healthcare
  • Infrastructure
  • Manufacturing
  • Retail
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence in Cybersecurity Market, By Component

  • 5.1 Introduction
  • 5.2 Hardware
    • 5.2.1 Processors
      • 5.2.1.1 Application-Specific Integrated Circuit (ASIC)
      • 5.2.1.2 Field Programmable Gate Array (FPGA)
      • 5.2.1.3 Graphics Processing Unit (GPU)
      • 5.2.1.4 Memory Protection Unit (MPU)
    • 5.2.2 Memory
    • 5.2.3 Network
  • 5.3 Software
    • 5.3.1 AI Solutions
    • 5.3.2 AI Platform
      • 5.3.2.1 Application Program Interface (API)
      • 5.3.2.2 Machine Learning Framework
  • 5.4 Services
    • 5.4.1 Support & Maintenance
    • 5.4.2 Deployment & Integration

6 Global Artificial Intelligence in Cybersecurity Market, By Security Type

  • 6.1 Introduction
  • 6.2 Application Security
  • 6.3 Endpoint Security
  • 6.4 Network Security
  • 6.5 Cloud Security

7 Global Artificial Intelligence in Cybersecurity Market, By Deployment Type

  • 7.1 Introduction
  • 7.2 On-Premises
  • 7.3 Cloud

8 Global Artificial Intelligence in Cybersecurity Market, By Technology

  • 8.1 Introduction
  • 8.2 Context-Aware Computing
  • 8.3 Machine Learning
    • 8.3.1 Deep Learning
    • 8.3.2 Reinforcement Learning
    • 8.3.3 Supervised Learning
    • 8.3.4 Unsupervised Learning
  • 8.4 Natural Language Processing (NLP)
  • 8.5 Other Technologies

9 Global Artificial Intelligence in Cybersecurity Market, By Application

  • 9.1 Introduction
  • 9.2 Antivirus/ Malware
  • 9.3 Data Loss Prevention
  • 9.4 Fraud Detection/Anti-Fraud
  • 9.5 Identity And Access Management
  • 9.6 Intrusion Detection/ Prevention System
  • 9.7 Risk And Compliance Management
  • 9.8 Security & Vulnerability Management
  • 9.9 Threat Intelligence
  • 9.10 Unified Threat Management
  • 9.11 Other Applications

10 Global Artificial Intelligence in Cybersecurity Market, By End User

  • 10.1 Introduction
  • 10.2 Banking, Financial Services and Insurance (BFSI)
  • 10.3 Automotive & Transportation
  • 10.4 Enterprise
  • 10.5 Government & Defense
  • 10.6 Healthcare
  • 10.7 Infrastructure
  • 10.8 Manufacturing
  • 10.9 Retail
  • 10.10 Other End Users

11 Global Artificial Intelligence in Cybersecurity Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Micron Technology, Inc.
  • 13.2 Amazon Web Services, Inc.
  • 13.3 Cylance Inc. (BlackBerry)
  • 13.4 FireEye, Inc.
  • 13.5 Fortinet, Inc.
  • 13.6 Acalvio Technologies, Inc
  • 13.7 Intel Corporation
  • 13.8 IBM Corporation
  • 13.9 LexisNexis
  • 13.10 Darktrace
  • 13.11 Microsoft Corporation
  • 13.12 Samsung Electronics Co. Ltd.
  • 13.13 Cisco Systems, Inc.
  • 13.14 Gen Digital Inc.
  • 13.15 NVIDIA Corporation
  • 13.16 McAfee LLC
  • 13.17 Palo Alto Networks Inc.
  • 13.18 Cylance Inc.

List of Tables

  • Table 1 Global Artificial Intelligence in Cybersecurity Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Artificial Intelligence in Cybersecurity Market Outlook, By Component (2021-2030) ($MN)
  • Table 3 Global Artificial Intelligence in Cybersecurity Market Outlook, By Hardware (2021-2030) ($MN)
  • Table 4 Global Artificial Intelligence in Cybersecurity Market Outlook, By Processors (2021-2030) ($MN)
  • Table 5 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application-Specific Integrated Circuit (ASIC) (2021-2030) ($MN)
  • Table 6 Global Artificial Intelligence in Cybersecurity Market Outlook, By Field Programmable Gate Array (FPGA) (2021-2030) ($MN)
  • Table 7 Global Artificial Intelligence in Cybersecurity Market Outlook, By Graphics Processing Unit (GPU) (2021-2030) ($MN)
  • Table 8 Global Artificial Intelligence in Cybersecurity Market Outlook, By Memory Protection Unit (MPU) (2021-2030) ($MN)
  • Table 9 Global Artificial Intelligence in Cybersecurity Market Outlook, By Memory (2021-2030) ($MN)
  • Table 10 Global Artificial Intelligence in Cybersecurity Market Outlook, By Network (2021-2030) ($MN)
  • Table 11 Global Artificial Intelligence in Cybersecurity Market Outlook, By Software (2021-2030) ($MN)
  • Table 12 Global Artificial Intelligence in Cybersecurity Market Outlook, By AI Solutions (2021-2030) ($MN)
  • Table 13 Global Artificial Intelligence in Cybersecurity Market Outlook, By AI Platform (2021-2030) ($MN)
  • Table 14 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application Program Interface (API) (2021-2030) ($MN)
  • Table 15 Global Artificial Intelligence in Cybersecurity Market Outlook, By Machine Learning Framework (2021-2030) ($MN)
  • Table 16 Global Artificial Intelligence in Cybersecurity Market Outlook, By Services (2021-2030) ($MN)
  • Table 17 Global Artificial Intelligence in Cybersecurity Market Outlook, By Support & Maintenance (2021-2030) ($MN)
  • Table 18 Global Artificial Intelligence in Cybersecurity Market Outlook, By Deployment & Integration (2021-2030) ($MN)
  • Table 19 Global Artificial Intelligence in Cybersecurity Market Outlook, By Security Type (2021-2030) ($MN)
  • Table 20 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application Security (2021-2030) ($MN)
  • Table 21 Global Artificial Intelligence in Cybersecurity Market Outlook, By Endpoint Security (2021-2030) ($MN)
  • Table 22 Global Artificial Intelligence in Cybersecurity Market Outlook, By Network Security (2021-2030) ($MN)
  • Table 23 Global Artificial Intelligence in Cybersecurity Market Outlook, By Cloud Security (2021-2030) ($MN)
  • Table 24 Global Artificial Intelligence in Cybersecurity Market Outlook, By Deployment Type (2021-2030) ($MN)
  • Table 25 Global Artificial Intelligence in Cybersecurity Market Outlook, By On-Premises (2021-2030) ($MN)
  • Table 26 Global Artificial Intelligence in Cybersecurity Market Outlook, By Cloud (2021-2030) ($MN)
  • Table 27 Global Artificial Intelligence in Cybersecurity Market Outlook, By Technology (2021-2030) ($MN)
  • Table 28 Global Artificial Intelligence in Cybersecurity Market Outlook, By Context-Aware Computing (2021-2030) ($MN)
  • Table 29 Global Artificial Intelligence in Cybersecurity Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 30 Global Artificial Intelligence in Cybersecurity Market Outlook, By Deep Learning (2021-2030) ($MN)
  • Table 31 Global Artificial Intelligence in Cybersecurity Market Outlook, By Reinforcement Learning (2021-2030) ($MN)
  • Table 32 Global Artificial Intelligence in Cybersecurity Market Outlook, By Supervised Learning (2021-2030) ($MN)
  • Table 33 Global Artificial Intelligence in Cybersecurity Market Outlook, By Unsupervised Learning (2021-2030) ($MN)
  • Table 34 Global Artificial Intelligence in Cybersecurity Market Outlook, By Natural Language Processing (NLP) (2021-2030) ($MN)
  • Table 35 Global Artificial Intelligence in Cybersecurity Market Outlook, By Other Technologies (2021-2030) ($MN)
  • Table 36 Global Artificial Intelligence in Cybersecurity Market Outlook, By Application (2021-2030) ($MN)
  • Table 37 Global Artificial Intelligence in Cybersecurity Market Outlook, By Antivirus/ Malware (2021-2030) ($MN)
  • Table 38 Global Artificial Intelligence in Cybersecurity Market Outlook, By Data Loss Prevention (2021-2030) ($MN)
  • Table 39 Global Artificial Intelligence in Cybersecurity Market Outlook, By Fraud Detection/Anti-Fraud (2021-2030) ($MN)
  • Table 40 Global Artificial Intelligence in Cybersecurity Market Outlook, By Identity And Access Management (2021-2030) ($MN)
  • Table 41 Global Artificial Intelligence in Cybersecurity Market Outlook, By Intrusion Detection/ Prevention System (2021-2030) ($MN)
  • Table 42 Global Artificial Intelligence in Cybersecurity Market Outlook, By Risk And Compliance Management (2021-2030) ($MN)
  • Table 43 Global Artificial Intelligence in Cybersecurity Market Outlook, By Security & Vulnerability Management (2021-2030) ($MN)
  • Table 44 Global Artificial Intelligence in Cybersecurity Market Outlook, By Threat Intelligence (2021-2030) ($MN)
  • Table 45 Global Artificial Intelligence in Cybersecurity Market Outlook, By Unified Threat Management (2021-2030) ($MN)
  • Table 46 Global Artificial Intelligence in Cybersecurity Market Outlook, By Other Applications (2021-2030) ($MN)
  • Table 47 Global Artificial Intelligence in Cybersecurity Market Outlook, By End User (2021-2030) ($MN)
  • Table 48 Global Artificial Intelligence in Cybersecurity Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2021-2030) ($MN)
  • Table 49 Global Artificial Intelligence in Cybersecurity Market Outlook, By Automotive & Transportation (2021-2030) ($MN)
  • Table 50 Global Artificial Intelligence in Cybersecurity Market Outlook, By Enterprise (2021-2030) ($MN)
  • Table 51 Global Artificial Intelligence in Cybersecurity Market Outlook, By Government & Defense (2021-2030) ($MN)
  • Table 52 Global Artificial Intelligence in Cybersecurity Market Outlook, By Healthcare (2021-2030) ($MN)
  • Table 53 Global Artificial Intelligence in Cybersecurity Market Outlook, By Infrastructure (2021-2030) ($MN)
  • Table 54 Global Artificial Intelligence in Cybersecurity Market Outlook, By Manufacturing (2021-2030) ($MN)
  • Table 55 Global Artificial Intelligence in Cybersecurity Market Outlook, By Retail (2021-2030) ($MN)
  • Table 56 Global Artificial Intelligence in Cybersecurity Market Outlook, By Other End Users (2021-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.