首頁 > 市場調查報告書 > 通訊

IT安全性人工智能

市場調查報告書

商品編碼

1360032

全球安全市場人工智慧 (AI) - 2023-2030

Global Artificial Intelligence (AI) in Security Market - 2023-2030

出版日期: 2023年10月11日 | 出版商:

DataM Intelligence | 英文 204 Pages | 商品交期: 約2個工作天內

價格

※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

簡介目錄

概述：

2022年，全球人工智慧（AI）安全市場規模達到210億美元，預計2030年將達到542億美元，2023-2030年預測期間複合年成長率為19.1%。

網路威脅的數量和複雜性不斷增加，以及實體安全問題，正在推動組織尋求更先進和自動化的安全解決方案。數位時代產生的大量資料對於人類分析師來說難以有效處理。人工智慧對海量資料集的即時分析有助於發現漏洞和風險。

例如，2023 年 9 月 21 日，領先的網路安全公司麥克菲 (McAfee) 最近推出了一項創新的人工智慧詐騙防護功能，旨在即時識別和阻止詐騙。隨著網路威脅不斷發展並變得更加複雜，這項技術代表了網路安全的重大進步。由人工智慧驅動的詐騙防護系統利用機器學習演算法和即時資料分析來偵測詐欺活動。

亞太地區是全球人工智慧（AI）安全市場不斷成長的地區之一，佔據超過3/7的市場佔有率，近年來該地區網路威脅和攻擊激增。隨著對數位技術和網際網路的日益依賴，該地區的企業和政府面臨持續的網路安全挑戰。人工智慧提供了先進的威脅偵測和回應能力，使其成為應對這些威脅的重要工具。

動態：

政府措施提振市場

政府機構經常分配大量資金來支持安全領域的人工智慧研究和開發，這些投資可以資助人工智慧技術、網路安全解決方案和相關項目的創建。財政支持鼓勵創新並加速人工智慧在安全領域的採用。各國政府為人工智慧在安全領域的應用制定監管框架和標準，這些法規可以確保負責任的人工智慧使用、資料隱私和道德實踐。

根據卡內基國際和平基金會的報告，到2022年，中國政府實施了三種不同的人工智慧治理方法，每種方法都由官僚機構的不同部門倡導，而這個強大的監管機構專注於針對特定人工智慧應用的基於規則的治理。它發布了規範網路推薦演算法的規則草案，包括演算法可解釋性和用戶權利保護的規定。中國國家網際網路資訊辦公室正在製定為期三年的路線圖，以管理所有網際網路演算法，涉及多個監管機構。

利用人工智慧實施機器學習會引發威脅和惡意軟體

網路威脅和惡意軟體攻擊變得越來越複雜和適應性強。傳統的基於簽名的方法不再足以檢測和預防這些高級威脅。機器學習和人工智慧可以分析模式和行為來識別新的威脅。大型資料集的可用性對於訓練模型識別正常和惡意行為至關重要。

根據參議院軍事委員會的報告，美國參議院軍事委員會網路小組委員會於2022 年5 月舉行了一次國會聽證會，重點討論了在網路空間領域利用人工智慧（AI）和機器學習（ML）的重要性。來自谷歌和喬治城大學安全與新興技術中心的主要代表參加了聽證會。

技術進步推動市場發展

惡意軟體、勒索軟體和網路釣魚攻擊等網路威脅日益複雜，對人工智慧驅動的安全解決方案的成長產生了強烈需求。即時人工智慧可以準確、快速地分析大量資料，這對於識別表明安全漏洞的模式和異常至關重要。它還可以自動執行許多安全任務例程，例如監控網路流量和標記可疑活動。

例如，2022年9月20日，NVIDIA推出了用於高精度邊緣AI的NVIDIA IGX平台，旨在增強製造、物流和醫療保健等行業的安全性和安全性，該平台具有可編程性和可配置性，可為各種場景提供適應性強的解決方案。產業需求。它旨在改善物理世界環境中的人機協作和安全性。 IGX 專注於提高在製造和物流等監管嚴格的行業中運作的自主系統的安全性。

錯誤識別和資料洩露

人工智慧驅動的安全系統會產生不正確的識別威脅活動，稱為誤報和漏報（未能偵測到實際威脅）。在準確的威脅檢測和最大限度地減少誤報之間實現適當的平衡可能具有挑戰性。網路犯罪分子可以利用對抗性攻擊來操縱人工智慧演算法。他們可以製作旨在逃避檢測或誤導人工智慧系統的惡意輸入，從而降低其可靠性。

根據 IBM 2023 年的報告，全球資料外洩的平均成本升至 445 萬美元的歷史新高，比前三年成長了 15%。在同一三年期間，檢測和升級成本顯著增加了 42%，目前它們構成了違規費用的大部分，這表明違規調查已轉向更複雜的調查。

The increasing number and rising complexity for cyber threats, as well as physical security concerns, are pushing organizations to seek more advanced and automated security solutions. The sheer volume of data generated in the digital age is overwhelming for human analysts to process effectively. Real-time analysis of enormous data sets by AI could help to find vulnerabilities and risks.

For instance, on 21 September 2023, McAfee, a leading cybersecurity company, recently unveiled an innovative AI-powered scam protection feature designed to identify and block scams in real-time. As cyber threats continue to evolve and become more sophisticated, this technology represents a significant advancement in online security. The AI-powered scam protection system leverages machine learning algorithms and real-time data analysis to detect fraudulent activities.

Asia-Pacific is among the growing regions in the global artificial intelligence (AI) in security market covering more than 3/7th of the market and the region has witnessed a surge in cyber threats and attacks in recent years. With the growing reliance on digital technologies and the internet, businesses and governments in the region face constant cybersecurity challenges. AI offers advanced threat detection and response capabilities, making it a crucial tool for addressing these threats.

Dynamics:

Government Initiatives Boost the Market

Government agencies often allocate substantial funds to support AI research and development in the security domain and these investments can fund the creation of AI technologies, cybersecurity solutions and related projects. Financial support encourages innovation and accelerates the adoption of AI in security. Governments establish regulatory frameworks and standards for AI adoption in security, these regulations can ensure responsible AI usage, data privacy and ethical practices.

According to a report from the Carnegie Endowment for International Peace, in 2022, the Chinese government has implemented three distinct approaches to artificial intelligence governance, each championed by different branches of the bureaucracy and this powerful regulator focuses on rule-based governance for specific AI applications. It released draft rules for regulating internet recommendation algorithms, including provisions for algorithmic interpretability and user rights protection. The Cyberspace Administration of China is working on a three-year roadmap for governing all internet algorithms, involving multiple regulators.

Implementing Machine Learning with AI Enables Threats and Malware

Cyber threats and malware attacks have grown increasingly sophisticated and adaptive. Traditional signature-based approaches are no longer sufficient to detect and prevent these advanced threats. ML and AI can analyze patterns and behaviors to identify novel threats. The availability of large datasets is crucial for training models to recognize normal and malicious behavior.

According to a report from the Senate Committee on Armed Services, U.S. Senate Armed Services Committee's Subcommittee on Cyber held a congressional hearing in May 2022 focused on the significance of leveraging artificial intelligence (AI) and machine learning (ML) in the realm of cyberspace. The hearing featured key representatives from Google and the Center for Security and Emerging Technology at Georgetown University.

Technology Advancement Boosts the Market

The rising complexity of cyber threats like malware, ransomware and phishing attacks has created a strong demand for the growth of AI-powered security solutions. In real-time AI analyzes a large volume of data accurately and quickly which is essential for identifying patterns and anomalies that indicate security breaches. It also automates many routines of security tasks like monitoring network traffic and flagging suspicious activities.

For instance, on 20 September 2022, NVIDIA introduced the NVIDIA IGX platform for high-precision edge AI, designed to enhance security and safety in industries such as manufacturing, logistics and healthcare and this platform is programmable and configurable, providing an adaptable solution for various industries needs. It aims to improve human-machine collaboration and safety in physical-world environments. IGX focuses on improving the safety and security of autonomous systems operating in industries with stringent regulations, such as manufacturing and logistics.

Incorrect Identification and Data Breaches

AI-powered security systems generate incorrect identification threat activity called false positives and false negatives (failing to detect actual threats). Achieving the right balance between accurate threat detection and minimizing false alarms can be challenging. Cybercriminals can use adversarial attacks to manipulate AI algorithms. They can craft malicious inputs designed to evade detection or mislead AI systems, making them less reliable.

According to an IBM report in 2023, the average cost of a data breach worldwide increased to an all-time high of US$ 4.45 Million, a 15% rise over the previous three years. Over the same three-year period, detection and escalation costs significantly increased by 42% and they now make up the majority of breach expenses, indicating a shift toward more involved breach investigations.

Segment Analysis:

The global artificial intelligence (AI) in security market is segmented based on offering, deployment type, security type, technology, application, end-user and region.

AI-Powered Security Solutions in Cloud Environments

Advanced security solutions are becoming more and more important as cyber threats become more complex and widespread. Massive volumes of data may be instantly analyzed by AI, enabling real-time danger detection and reaction. The size and complexity of cloud environments provide many opportunities for possible threats to enter. AI can handle the scale of cloud computing, continuously monitoring and analyzing network traffic, user behavior and system logs.

For instance, on 29 August 2023, Google Cloud leveraged its acquisition of cybersecurity firm Mandiant to offer managed threat-hunting services to its Chronicle Security Operations customers. The service, Mandiant Hunt for Chronicle Security Operations, will provide access to Mandiant's threat-hunting intelligence and personnel within customers' Chronicle environments.

Geographical Penetration:

Rising Cyber Threats Boost the Market

North America is dominating the global artificial intelligence (AI) in security market covering more than 1/3rd of the market particularly U.S. and Canada face a growing and evolving cyber threat landscape. The frequency and sophistication of cyberattacks, data breaches and ransomware incidents have increased. For efficiently identifying, reducing and responding to these dangers, AI is viewed as a crucial tool.

For instance, on 24 April 2023, North Dakota used artificial intelligence and machine learning to enhance its cybersecurity efforts. The state partnered with cybersecurity vendor Palo Alto Networks to build an autonomous security operations center (SOC) to protect 250,000 endpoints, including schools, government offices and police stations. AI and ML help automate low-level security incident resolution and address backlogged incidents, allowing human analysts to focus on more complex tasks.

Competitive Landscape

The major global players in the market include: Palo Alto Networks Inc., Trellix, Darktrace,Cyclance Inc., Fortinet, Inc., Nozomi Networks Inc., , ESET, s.r.o., ThreatMetrix, Inc. and Vectra AI, Inc..

COVID-19 Impact Analysis:

The lockdowns and social distancing measures in place organizations have turned to AI-driven surveillance and security solutions for remote monitoring of facilities and properties. AI-powered cameras and sensors can detect anomalies and potential security threats, reducing the need for physical security personnel on-site. AI-driven cybersecurity tools have become more critical as cyberattacks surged during the pandemic.

AI-driven cybersecurity tools have become more critical as cyberattacks surged during the pandemic. AI systems examine huge quantities of data to quickly identify and address dangers, assisting enterprises in safeguarding their networks and data. Security teams are able to focus on more complex and strategic aspects of security operations since AI has been used to automate regular security duties, such as security incident investigation and response.

Cyberattacks and cyber espionage activities tend to rise during periods of geopolitical crisis. Critical infrastructure, governmental institutions and private organizations may be the target of state-sponsored as well as non-state actors. Cybersecurity solutions powered by AI will be essential in identifying and countering these attacks. The conflict may lead to geopolitical tensions affecting international collaboration in AI research and development.

AI Impact

AI-powered security solutions analyze large amounts of data in real-time which allows for the rapid detection of security threats and anomalies. Machine learning algorithms identify patterns and behaviors associated with cyberattacks and enable quicker response times. Based on previous data and continuous network monitoring, AI may be used to anticipate potential security risks and this proactive approach helps organizations get ready for and stop cyberattacks before they happen.

AI-driven security tools can analyze user and entity behavior to identify suspicious activities. By understanding typical user behavior, AI can flag deviations that may indicate a security breach. AI can automate responses to security incidents, such as isolating compromised devices, blocking malicious traffic or initiating incident response procedures and this automation reduces the response time and minimizes human error.

For instance, on 11 September 2022, Lockheed Martin, in collaboration with the University of Iowa's Operator Performance Laboratory, successfully demonstrated the use of artificial intelligence (AI) in coordinating manned and unmanned aircraft in a simulated air-to-ground mission. The AI agents provided data for rapid decision-making and reduced pilot workload. The success of this demonstration could pave the way for AI-enabled collaboration in Joint All Domain Operations and autonomous mission completion.

Russia- Ukraine War Impact

The conflict may disrupt the global supply chain for technology components, including semiconductors and other hardware critical for AI infrastructure. Supply chain disruptions can lead to delays in AI projects and impact the availability of AI-powered security solutions. Organizations and governments reallocate resources and priorities in AI development and deployment based on evolving security threats and national interests and which leads to a shift in focus towards AI technologies with direct relevance to security and defense.

By Offering

Hardware
Software
Services

By Deployment Type

Cloud
On-Premise

By Security Type

Network Security
Endpoint Security
Application Security
Cloud Security

By Technology

Machine Learning
Natural Language Processing
Context-Aware Computing

By Application

Identity and Access Management
Risk and Compliance Management
Data Loss Prevention
Unified Threat Management
Security and Vulnerability Management
Others

By End-User

BFSI
Retail
Defense
Manufacturing
Enterprise
Others

By Region

North America
- U.S.
- Canada
- Mexico

Europe
- Germany
- UK
- France
- Italy
- Russia
- Rest of Europe

South America
- Brazil
- Argentina
- Rest of South America

Asia-Pacific
- China
- India
- Japan
- Australia
- Rest of Asia-Pacific

Middle East and Africa

Key Developments

In October 2022, UBS and Microsoft recently announced an expansion of their relationship. UBS intends to run more than 50% of its applications, including crucial workloads, on Azure during the following five years. This action intends to update UBS's global technological infrastructure and is consistent with the bank's "cloud first" policy.
In September 2022, Kyndryl, an independent company spun off from IBM's Managed Infrastructure Services business and Elastic, the company behind Elasticsearch and the Elastic Stack, announced an expanded partnership to enable data observability. The collaboration aims to help organizations gain better insights from their data by leveraging Kyndryl's expertise in data and AI operations alongside Elastic's solutions for search, observability and security.
In March 2022, in collaboration with Mastercard, Samsung is developing biometric credit cards with integrated fingerprint scanners and these cards will feature numerous distinct Samsung chips and be compatible with the majority of point-of-sale terminals that support Mastercard chip payments.

Why Purchase the Report?

To visualize the global artificial intelligence (AI) in security market segmentation based on offering, deployment type, security type, technology, application, end-user and region, as well as understand key commercial assets and players.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous data points of artificial intelligence (AI) in security market-level with all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
Product mapping available as excel consisting of key products of all the major players.

The global artificial intelligence (AI) in security market report would provide approximately 85 tables, 93 figures and 204 Pages.

Target Audience 2023

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Offering
3.2. Snippet by Deployment Type
3.3. Snippet by Security Type
3.4. Snippet by Technology
3.5. Snippet by Application
3.6. Snippet by End-User
3.7. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Government Initiatives Boost the Market
  - 4.1.1.2. Implementing Machine Learning with AI Enables Threats and Malware
  - 4.1.1.3. Technology Advancement Boosts the Market
- 4.1.2. Restraints
  - 4.1.2.1. Incorrect Identification and Data Breaches
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion

6. COVID-19 Analysis

6.1. Analysis of COVID-19
- 6.1.1. Scenario Before COVID
- 6.1.2. Scenario During COVID
- 6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion

7. By Offering

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
- 7.1.2. Market Attractiveness Index, By Offering
7.2. Hardware*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Software
7.4. Services

8. By Deployment Type

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 8.1.2. Market Attractiveness Index, By Deployment Type
8.2. Cloud*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. On-Premise

9. By Security Type

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Security Type
- 9.1.2. Market Attractiveness Index, By Security Type
9.2. Network Security*
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. Endpoint Security
9.4. Application Security
9.5. Cloud Security

10. By Technology

10.1. Introduction
- 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 10.1.2. Market Attractiveness Index, By Technology
10.2. Machine Learning*
- 10.2.1. Introduction
- 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
10.3. Natural Language Processing
10.4. Context-Aware Computing

11. By Application

11.1. Introduction
- 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.1.2. Market Attractiveness Index, By Application
11.2. Identity and Access Management*
- 11.2.1. Introduction
- 11.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
11.3. Risk and Compliance Management
11.4. Data Loss Prevention
11.5. Unified Threat Management
11.6. Security and Vulnerability Management
11.7. Others

12. By End-User

12.1. Introduction
- 12.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 12.1.2. Market Attractiveness Index, By End-User
12.2. BFSI*
- 12.2.1. Introduction
- 12.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
12.3. Retail
12.4. Defense
12.5. Manufacturing
12.6. Enterprise
12.7. Others

13. By Region

13.1. Introduction
- 13.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 13.1.2. Market Attractiveness Index, By Region
13.2. North America
- 13.2.1. Introduction
- 13.2.2. Key Region-Specific Dynamics
- 13.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
- 13.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 13.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Security Type
- 13.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 13.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 13.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 13.2.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 13.2.9.1. U.S.
  - 13.2.9.2. Canada
  - 13.2.9.3. Mexico
13.3. Europe
- 13.3.1. Introduction
- 13.3.2. Key Region-Specific Dynamics
- 13.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
- 13.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 13.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Security Type
- 13.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 13.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 13.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 13.3.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 13.3.9.1. Germany
  - 13.3.9.2. UK
  - 13.3.9.3. France
  - 13.3.9.4. Italy
  - 13.3.9.5. Russia
  - 13.3.9.6. Rest of Europe
13.4. South America
- 13.4.1. Introduction
- 13.4.2. Key Region-Specific Dynamics
- 13.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
- 13.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 13.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Security Type
- 13.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 13.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 13.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 13.4.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 13.4.9.1. Brazil
  - 13.4.9.2. Argentina
  - 13.4.9.3. Rest of South America
13.5. Asia-Pacific
- 13.5.1. Introduction
- 13.5.2. Key Region-Specific Dynamics
- 13.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
- 13.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 13.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Security Type
- 13.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 13.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 13.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 13.5.9. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 13.5.9.1. China
  - 13.5.9.2. India
  - 13.5.9.3. Japan
  - 13.5.9.4. Australia
  - 13.5.9.5. Rest of Asia-Pacific
13.6. Middle East and Africa
- 13.6.1. Introduction
- 13.6.2. Key Region-Specific Dynamics
- 13.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
- 13.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Type
- 13.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Security Type
- 13.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 13.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 13.6.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

14. Competitive Landscape

14.1. Competitive Scenario
14.2. Market Positioning/Share Analysis
14.3. Mergers and Acquisitions Analysis

15. Company Profiles

15.1. Palo Alto Networks Inc.*
- 15.1.1. Company Overview
- 15.1.2. Product Portfolio and Description
- 15.1.3. Financial Overview
- 15.1.4. Key Developments
15.2. Trellix
15.3. Darktrace
15.4. Cyclance Inc.
15.5. Fortinet, Inc.
15.6. Nozomi Networks Inc.
15.7. Bitdefender
15.8. ESET, s.r.o.
15.9. ThreatMetrix, Inc.
15.10. Vectra AI, Inc.

LIST NOT EXHAUSTIVE