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到 2030 年网路安全中的人工智慧 (AI) 市场预测：按细分市场和地区分類的全球分析
市场调查报告书
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1358955

到 2030 年网路安全中的人工智慧 (AI) 市场预测：按细分市场和地区分類的全球分析

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个工作天内

价格

根据 Stratistics MRC 的数据，全球网路安全人工智慧 (AI) 市场预计到 2023 年将达到 224 亿美元，到 2030 年将达到 1004 亿美元，预测期内年复合成长率为 23.9%。

人工智慧 (AI) 使识别、预防和回应网路威胁变得更加容易，从而对网路安全产生重大影响。人工智慧系统即时分析大量资料，以发现指向网路攻击的奇怪模式和行为。这包括恶意软体、病毒和其他危险软体。可以教导机器学习演算法检测已知风险并适应新风险。人工智慧驱动的异常侦测系统提供典型网路行为的基线，并在违反该基线时发出警报。这使您能够发现以前未发现的攻击方法和内部风险。

根据消费者技术协会的数据，全球 44% 的组织已部署人工智慧应用程式来侦测和阻止安全入侵。

对更好的安全措施的需求不断增长

随着网路攻击变得更加复杂和频繁，组织迅速意识到需要改进的现代化安全解决方案。许多相关人员现在高度关注网路风险。因此，迫切需要对组织的系统、网路和资料实施安全措施，以减轻已识别的风险。网路攻击和资料外洩的频率不断增加，增加了对安全解决方案的需求。此外，企业越来越认识到采取主动网路安全措施的必要性，包括更好的网路安全和威胁建模解决方案，这正在推动市场扩张。

诽谤攻击造成的错误讯息

人工智慧驱动的安全系统存在产生误报或无法识别真正威胁的风险。这些错误可能会导致时间和资源的损失以及无法识别漏洞。骇客可以利用人工智慧来发动专门设计的攻击，以破坏基于人工智慧的安全系统。这些攻击通常被称为对抗性攻击，可以伪造输入资料，使人工智慧演算法得出错误的结论，从而阻碍市场成长。

法规遵从性和行业标准要求

威胁建模已成为由法规合规标准和行业标准驱动的安全计划的有组织的一部分，例如通用资料保护规范(GDPR)、PCI-DSS（支付卡行业资料安全标准）和NIST（美国国家标准与技术研究院） ). 经常被要求。政府机构现在越来越需要改进的安全解决方案，导致网路安全领域的人工智慧市场蓬勃发展。上市公司和私人公司增加的技术投资也推动了人工智慧在网路安全市场的使用。

人工智慧无法应对现代复杂的危险

深度学习、神经网路、遗传演算法和机器学习等人工智慧技术和方法都是基于过去的经验。进阶持续性威胁 (APT) 是一种网路攻击，可让使用者未经授权存取网路并在相当长的时间内保持隐藏状态。虽然某些 APT 行为可能与 AI 可以侦测的过去事件类似，但新的 APT 缺乏过去的经验，需要新颖的方式来呼叫应用程式介面 (API) 和系统 - 采用尖端的方法来存取资源。真正抵御复杂的现代危险不能依赖过去的病毒和攻击。这个市场受到人工智慧无法应对高阶威胁的限制。

COVID-19 的影响：

许多顶级网路安全公司将当前的危机视为审查和重组当前策略并开发更复杂产品系列的机会。随着公司越来越多地实施在家工作政策，COVID-19 的爆发正在推动对尖端解决方案的需求。在家工作的人们以及使用潜在风险网路和设备的其他用户推动了对数位产品和服务的需求不断增长，这促使公司投资于机器学习和深度学习演算法。它已经成为。

机器学习领域预计将在预测期内成为最大的领域

机器学习领域预计将出现利润丰厚的成长，随着这些深度学习在终端用途产业中迅速传播，机器学习技术将急剧成长。 Google 和 IBM 等大公司开始使用机器学习进行威胁侦测和电子邮件过滤。公司正在利用机器学习和深度学习来加强其网路安全协议。此外，机器学习平台正日益成为自动化监控、识别异常以及导航安全系统产生的大量资料的首选工具。

诈欺侦测/诈欺领域预计在预测期内将经历最高的年复合成长率。

人工智慧（AI）在网路安全中的使用将作为诈欺侦测和诈欺预防的预防措施得到推广，因此诈欺侦测/诈欺预防领域预计在预测期内将以最高年复合成长率增长。由于诈欺发生率不断增加，机器学习已成为政府和其他最终用户增强预防诈欺能力的宝贵技术。因此，人工智慧工具可能会更频繁地用于消除诈骗、电子邮件网路钓鱼和诈欺记录。企业正在转向整合威胁管理，以保护其数位资产免受间谍软体感染文件、网路钓鱼攻击、诈欺的网站访问和特洛伊木马 (UTM) 等威胁，从而推动市场发展。

占比最大的地区：

由于物联网、5G 和 Wi-Fi 6 的引入，网路连接设备数量增加，预计北美将在预测期内占据最大的市场占有率。 5G 网路的扩张是由汽车、医疗保健、政府、能源和采矿业的公司推动的，这些产业可能成为骇客的接入点。大公司可能会投资机器学习、进阶分析、资产映射和即时估值视觉化平台。自然语言处理、机器学习（ML）和神经网路预计将在北美广泛应用，以阻止攻击、检测奇怪的用户行为并识别其他异常模式，并提高该地区的市场成长。

复合年复合成长率最高的地区：

由于经济成长和数数位化程度不断提高，亚太地区已成为网路攻击的热点地区，预计在预测期内年复合成长率最高。为了防范新的威胁，现在对先进网路安全解决方案的需求不断增长，特别是那些由人工智慧驱动的解决方案。亚太地区的许多政府已发起倡议，鼓励在网路安全领域创建和使用人工智慧。此类项目通常包括研发资金和市场驱动的法规支援。

免费客製化服务：

订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和年复合成长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第1章执行摘要

第2章前言

  • 概述
  • 利害关係人
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 调查来源
    • 主要调查来源
    • 二次调查来源
    • 先决条件

第3章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 用途分析
  • 最终用户分析
  • 新兴市场
  • 新型冠状病毒感染疾病（COVID-19）的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第5章网路安全领域的全球人工智慧 (AI) 市场：按组成部分

  • 硬体
    • 处理器
      • 用途积体电路(ASIC)
      • 现场可程式闸阵列 (FPGA)
      • 图形处理单元（GPU）
      • 记忆体保护单元 (MPU)
    • 记忆
    • 通讯网路
  • 软体
    • 人工智慧解决方案
    • 人工智慧平台
      • 应用程式介面（API）
      • 机器学习框架
  • 服务
    • 支援与维护
    • 部署与整合

第6章网路安全领域的全球人工智慧 (AI) 市场：按安全类型划分

  • 应用程式安全
  • 端点安全
  • 网路安全
  • 云端安全

第7章网路安全市场中的全球人工智慧 (AI)：按部署类型

  • 本地
  • 云

第8章网路安全领域的全球人工智慧 (AI) 市场：按技术分类

  • 上下文感知计算
  • 机器学习
    • 深度学习
    • 强化学习
    • 监督学习
    • 无监督学习
  • 自然语言处理（NLP）
  • 其他技术

第9章网路安全领域的全球人工智慧 (AI) 市场：按用途

  • 防毒/恶意软体
  • 防止资料损失预防
  • 诈欺侦测/诈欺预防
  • 身分和存取管理
  • 入侵侦测/预防系统
  • 风险与合规管理
  • 安全和漏洞管理
  • 威胁情报
  • 统一威胁管理
  • 其他用途

第10章网路安全领域的全球人工智慧 (AI) 市场：按最终用户分类

  • 银行、金融服务和保险 (BFSI)
  • 汽车和交通
  • 公司
  • 政府和国防
  • 卫生保健
  • 基础设施
  • 製造业
  • 零售
  • 其他最终用户

第11章全球人工智慧（AI）网路安全市场：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第12章进展

  • 合约、伙伴关係、协作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第13章公司简介

  • 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.