The Global Artificial Intelligence In Cybersecurity Market size is expected to reach $57.1 billion by 2028, rising at a market growth of 24.5% CAGR during the forecast period
New York, Oct. 25, 2022 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Global Artificial Intelligence In Cybersecurity Market Size, Share & Industry Trends Analysis Report By Offering, By Vertical, By Application, By Type, By Technology, By Regional Outlook and Forecast, 2022 – 2028” – https://www.reportlinker.com/p06352700/?utm_source=GNW
AI uses historical data to find patterns and trends in cyber security. Then, future attacks are predicted using this information.
AI-powered systems can be set up to automatically respond to dangers and combat online threats more quickly. Analyzing and improving cyber risks as well as cyber-attacks is no more a task on a human scale as the business attack surface develops and changes. To accurately quantify risk, up to highly-varying signals must be handled, based on the scale of the organization.
Neural networks as well as other AI tools and techniques have emerged in response to this unprecedented challenge to aid information security teams in protecting sensitive data, decrease the risk of breaches, and enhance their security posture through more efficient and effective threat detection as well as threat removal features.
Artificial intelligence (AI) is assisting under-resourced security tasks and operations analysts to keep ahead of threats as cyberattacks increase in volume and complexity. Artificial intelligence (AI) technologies, like machine learning or natural language processing, curate threat intelligence from various historical databases, blogs, and news articles to offer quick insights to break through the congestion of daily alerts, significantly lowering response times.
COVID-19 Impact Analysis
Widespread frauds involving the novel coronavirus and the spoofing of official institutions, like the WHO, present additional difficulties for organizations. For instance, Google discovered a very significant number of malware and phishing emails each day involving COVID-19 frauds during the initial 2020. In order to protect servers and databases from such hazards, the adoption of Artificial Intelligence in cybersecurity increased at a very rapid pace. Therefore, the growth of the Artificial Intelligence in cybersecurity market was propelled during the COVID-19 pandemic.
Market Growth Factors
Ensures A Higher Level Of Security From Bot Attacks And Spam
Nowadays, a significant portion of internet traffic is made up of harmful bots. Bots can be a serious threat, causing everything from account takeovers using stolen passwords to phony account creation as well as data fraud. Automated threats cannot be countered solely through manual reactions. With the aid of AI and machine learning, it is possible to differentiate between good bots (such as search engine crawlers) and bad bots as well as between humans and website visitors.
Ability To Predict And Prevent Breaches
The IT asset inventory, which is a precise and thorough list of all users, devices, and apps with various levels of access to different systems, is determined with the use of AI algorithms. AI-based solutions may now estimate how and where companies are most susceptible to being attacked based on the asset inventory or threat exposure, allowing them to plan and direct resources to regions with the greatest risks.
Market Restraining Factors
Increasing Prevalence And Complexities Of Data Poisoning
The adoption of artificial intelligence is exponentially increasing all over the world. Artificial intelligence has been employed to evaluate creditworthiness, identify faces, and forecast weather. At the same time, the sophistication of hacks has increased while adopting stealthier techniques. Given that all industries were looking for better tools and innovative uses for their technology, the fusion of AI and cybersecurity seemed inevitable.
Based on Type, the Artificial Intelligence in Cybersecurity Market is segmented into Network Security, Endpoint Security, Vertical Security, and Cloud Security. In 2021, the endpoint segment recorded a significant revenue share of AI in cybersecurity market. Organizations will push for continuous monitoring and risk-based application management, and automatic classification of the AI-based endpoint security. Endpoint security solutions frequently generate an allow list based on well-known software and a refuse list based on well-known malware automatically.
On the basis of Offerings, the Artificial Intelligence in Cybersecurity Market is segregated into Hardware, Software, and Services. In 2021, the services segment procured the largest revenue share of the Artificial Intelligence in cybersecurity market. The market for Artificial Intelligence in cybersecurity is anticipated to expand significantly due to the segment. The market’s expansion will be fueled by a strong need for application programming interfaces that include machine learning methods, speech, sensor data, and vision.
By Technology, the Artificial Intelligence in Cybersecurity Market is classified into Machine Learning, Natural Language Processing (NLP), and Context-aware computing. In 2021, the machine learning segment witnessed the highest revenue share of the Artificial Intelligence in cybersecurity market. With deep learning becoming increasingly prevalent across end-use sectors, machine learning technology would experience rapid growth. Leading businesses have been employing machine learning for threat identification and email filtering.
Based on Application, the Artificial Intelligence in Cybersecurity Market is categorized into Identity & Access Management, Risk & Compliance Management, Data Loss Prevention, Unified Threat Management, and Fraud Detection/Anti-Fraud & Threat Intelligence. In 2021, the unified threat management segment registered a significant revenue share of the Artificial Intelligence in cybersecurity market. In order to stop email phishing, fraud, and phony records, AI techniques may become more popular. Unified threat management (UTM) has gained more momentum with businesses as a way to safeguard their digital assets from dangers like spyware-infected files, phishing scams, unauthorized website access, and trojans.
By Vertical, the Artificial Intelligence in Cybersecurity Market is divided into BFSI, Retail, Government & Defense, Manufacturing, Enterprise, Healthcare, and Others. In 2021, the BFSI sector procured a significant revenue share of the Artificial Intelligence in cybersecurity market. Industry insiders anticipate that the deployment of AI in the fintech industry will increase the market share of AI in cybersecurity. The adoption of AI-based solutions to detect and recognize financial crimes and fraud is largely credited for the reliable projection.
Region-Wise, the Artificial Intelligence in Cybersecurity Market is analyzed across North America, Europe, Asia-Pacific, and LAMEA. In 2021, North America accounted for the maximum revenue share of the artificial intelligence in cybersecurity market. The increase in network-connected devices brought on by the adoption of IoT, 5G, and Wi-Fi 6 is primarily attributed to the growth of the regional market. The expansion of the 5G network has been driven by businesses in the automotive, government, healthcare, energy, and mining industries, which might be a point of access for hackers.
The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Amazon Web Services, Inc. and Intel Corporation are the forerunners in the Artificial Intelligence In Cybersecurity Market. Companies such as IBM Corporation, Micron Technology, Inc., Fortinet, Inc., are some of the key innovators in Artificial Intelligence In Cybersecurity Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Amazon Web Services, Inc., FireEye, Inc., BlackBerry Limited, Fortinet, Inc., Intel Corporation, RELX PLC, Micron Technology, Inc., Acalvio Technologies, Inc., and Darktrace Holdings Limited.
Recent Strategies deployed in Artificial Intelligence In Cybersecurity Market
Partnerships, Collaborations and Agreements:
Aug-2022: Darktrace entered into a partnership with HackerOne, a leader in Attack Resistance Management. Under this partnership, the companies aimed to integrate the PREVENT/Attack Surface Management technology of Darktrace into HackerOne’s continuous security assessment capabilities.
Jul-2022: Acalvio Technologies partnered with Booz Allen Hamilton, an American management and information technology consulting firm. Following this partnership, the companies aimed to help federal government agencies in empowering cyber infrastructure by offering an autonomous deception platform of Acalvio in order to address advanced persistent threats, insider threats, and ransomware.
Jul-2022: Amazon Web Services came into a partnership with Siemens Energy, an energy company. This partnership aimed to integrate the Managed Detection and Response industrial cyber security solution of Siemens Energy into the AWS Marketplace to facilitate it for customers to search, compare, and quickly start leveraging services and software that run over AWS.
May-2021: Darktrace partnered with Microsoft, the leading software giant. This partnership aimed to offer enterprise-scale self-learning AI to mutual customers of companies in order to autonomously detect and respond to cyber threats.
Acquisition & Mergers:
Jun-2022: IBM took over Randori, an attack surface management, and offensive cybersecurity provider. This acquisition aimed to enable IBM to help customers in detecting external facing assets continuously in the cloud or on-premises. Moreover, the company also aimed to aid customers in prioritizing exposures posing significant risks.
Feb-2022: Darktrace acquired Cybersprint, an attack surface management company. Through this acquisition, the company aimed to further introduce a new European R&D Center throughout the Netherlands to leverage the expertise of software engineers and mathematicians of Cambridge.
Nov-2021: IBM acquired ReaQta, an endpoint detection and response provider. Through this acquisition, the company aimed to expand its cybersecurity threat detection and response capabilities by leveraging the endpoint security solutions of ReaQta.
Apr-2021: IBM completed its acquisition of Turbonomic, an application resource, and network performance management software provider. With this acquisition, the company aimed to aid businesses in their AIOps initiatives by providing full-stack application observability and management in order to enhance performance and reduce costs.
Nov-2020: FireEye took over Respond Software, an automated security incident investigations platform provider. This acquisition aimed to complement the XDR capabilities of the company in order to leverage the integrated capabilities of security professionals and the platform of Respond.
Product Launches and Product Expansion:
Jul-2022: Darktrace released the Darktrace PREVENT, an interconnected suite of AI products. With this launch, the company aimed to proactively protect businesses from high volume and complex cyber threats.
Jun-2022: Fortinet released FortiRecon, a complete Digital Risk Protection Service portfolio. With this launch, the company aimed to integrate automation capabilities, machine learning, and FortiGuard Labs?cybersecurity experts to offer a solution with the capability to manage the risk posture of the company and provide meaningful action to protect its brand reputation, data, and assets.
May-2022: Fortinet unveiled FortiNDR, a new self-learning AI capabilities solution into its network detection and response offering. The new solution aimed to leverage deep neural networks in combination with machine learning in order to more quickly recognize cyber-attacks according to their anomalies within network activity as well as limit exposure to threats.
Apr-2022: Fortinet introduced FortiOS 7.2, the latest upgrade into its flagship operating system and the foundation of the Fortinet Security Fabric. Through this product expansion, the company aimed to converge security at each network edge linked with the scale and performance required to identify and prevent threats throughout the entire infrastructure of an organization.
Jan-2022: Acalvio and Honewell launched the Honeywell Threat Defense Platform, an Acalvio-powered solution to detect known and unknown attacks. The new solution aimed to offer complex active defense through autonomous deception tactics to overpower attackers and deliver high-fidelity threat detection.
Jan-2022: BlackBerry Limited and Cylance rolled out the new ZTNA-as-a-service solution, an advanced AI-driven cybersecurity solution powered by CylanceGATEWAY. With this product launch, the companies aimed to offer a contextual correlation of device and network telemetry to businesses of all sizes in order to limit access to authenticated, trusted, and known devices and users.
Jan-2021: Fortinet released the FortiXDR, a new Extended Detection, and Response solution. The new solution aimed to lower complications, accelerate detection, and coordinate response to breaches and cyberattacks throughout the organization.
Scope of the Study
Market Segments covered in the Report:
• Government & Defense
• Fraud Detection/Anti-Fraud & Threat Intelligence
• Identity & Access Management
• Risk & Compliance Management
• Data Loss Prevention
• Unified Threat Management & Others
• Network Security
• Endpoint Security
• Vertical Security
• Cloud Security
• Machine Learning
• Natural Language Processing (NLP)
• Context-aware Computing
• North America
o Rest of North America
o Rest of Europe
• Asia Pacific
o South Korea
o Rest of Asia Pacific
o Saudi Arabia
o South Africa
o Rest of LAMEA
• IBM Corporation
• Amazon Web Services, Inc.
• FireEye, Inc.
• BlackBerry Limited
• Fortinet, Inc.
• Intel Corporation
• RELX PLC
• Micron Technology, Inc.
• Acalvio Technologies, Inc.
• Darktrace Holdings Limited
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