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Machine Learning in Vehicle CyberSecurity Market Size By Security Type (Network, Endpoint, Application, & User), By Vehicle Type (Electric Vehicles, Autonomous Vehicles, Conventional Vehicles), By Region (Europe, North America) - Global Industry Analyis & Forecast 2016-2024

Published On : 2018-03-21 Report Page : 280 Category: Automotive

Global Machine Learning Based Vehicle Cybersecurity Market Outlook

Market Overview

Machine learning systems have been applied in many fields  of  science  owing  to  their  exclusive  properties  like adaptability, scalability,  and flexibility that provide potential to  rapidly modify to new  and  unknown  challenges. New forms of cyber-attacks are becoming more and more possible as computers, networks, and codes grow in both the connected car and in “smart automotive factories.” Technology is accelerating the swiftness of transformation within the automotive industry. Rapidly evolving automotive technologies pushed the automotive industry players to address critical infrastructure and processes and to rethink machine learning and cyber security. Automotive industry is anticipated to be the second largest data generator across the globe, which will intensify the need for advanced cybersecurity techniques that will aid the growth of machine learning based vehicle cybersecurity market.

Goldstein Research analyst forecast the global machine learning based vehicle cybersecurity market to expand at a CAGR of 19.0% during the forecast period 2016-2024. Even before autonomous cars become commonplace, modern cars are already susceptible to hackers via in-car technologies such as telematics. These “connected cars” are becoming standard and will propel the growth of machine learning based cybersecurity market.

Covered in this machine learning based vehicle cybersecurity market report

The report covers the present ground scenario and the future growth prospects of the machine learning based vehicle cybersecurity market for 2016-2024 along with the identification of factors instrumental in changing the market scenario and rising prospective opportunities. We calculated the market size and revenue share on the basis of revenue generated per segment, regional and country level. The revenue forecast is given on the basis of number of machine learning based vehicle cybersecurity companies and current growth rate of the market.

Global Machine Learning Based Vehicle Cybersecurity Market Segmentation

By Security Type                                                                                  

  • Network (network traffic analysis and intrusion detection)
  • Endpoint (anti-malware)
  • Application (database firewalls)
  • User (anti-fraud)

By Vehicle Type

  • Electric Vehicles
  • Autonomous Vehicles
  • Conventional Vehicles

By Geography

  • North America (US, Canada) {Market Share (%), Market Size (USD Million)}
  • Europe (UK, France, Italy, Germany, Spain, Hungary, Sweden, Russia, Poland and Rest of Europe) {Market Share (%), Market Size (USD Million)}
  • Middle East and Africa (GCC Countries, North Africa, South Africa and Rest of Middle East & Africa) {Market Share (%), Market Size (USD Million)}
  • Latin America (Brazil, Mexico and Rest of Latin America) {Market Share (%), Market Size (USD Million)}
  • Asia Pacific (China, Japan, India, Singapore, South Korea, Australia, New Zealand and Rest of Asia-Pacific) {Market Share (%), Market Size (USD Million)}

Based on security type, the network security market size in the global cyber security market is expected to dominate the market during the forecast period. Moreover, machine learning based vehicle cybersecurity market for application based security is projected to witness growth at a significant rate during the forecast period.

Machine Learning Based Vehicle Cybersecurity Market Trends, Outlook, & Challenges

Global Machine Learning Based Vehicle Cybersecurity Market Outlook 2016-2024, has been prepared based on an in-depth market analysis from industry experts. The report covers the competitive landscape and current position of major players in the global machine learning based vehicle cybersecurity market. The report also includes porter’s five force model, SWOT analysis, company profiling, business strategies of market players and their business models. Global machine learning based vehicle cybersecurity market report also recognizes value chain analysis to understand the cost differentiation to provide competitive advantage to the existing and new entry players.

Our global machine learning based vehicle cybersecurity market report comprises of the following companies as the key players in the global machine learning based vehicle cybersecurity market: Argus Cyber Security, Harman International Industries, Karamba Security, IBM, Cisco Systems Inc., Arilou Technologies, Secunet AG and Intel Corporation. 

According to our global machine learning based vehicle cybersecurity market study on the basis of extensive primary and secondary research, one major trend in the market is growing need for cybersecurity in emerging autonomous vehicle technology as these vehicles consist of combination of high-tech sensors and innovative procedures to detect and respond to their surrounding environment, including radar, LIDARs, GPS, drive-by-wire control systems, and computer vision, which are highly prone to cyber-attacks and surge for highly advance cybersecurity technologies.

According to the report, major driver in global machine learning based vehicle cybersecurity market is growing automation and threat from cyber-attacks. Past few years have witnessed advancements in artificial intelligence in autonomous cars, Internet of Things (loT) and big data. However, that same time period also witnessed the rise of ransomware, botnets, and attack vectors as widespread forms of malware cyber-attack, with cybercriminals continually expanding their approaches of attack. Thus, with the rapid advancement of technology, the automotive industry also seeking to battle these challenges which is expected to drive the growth of machine learning based vehicle cybersecurity market.

Further, the report states that one challenge in global machine learning based vehicle cybersecurity market is the extreme and increasing shortage of skillful cybersecurity personnel to investigate and respond to incidents illumined by the exponential growth in data from business systems and the security sensors.

Geographically, North America and Western Europe are expected to dominate the challenge in global machine learning based vehicle cybersecurity market over the forecast period as the adoption of advanced connected car systems and emergence of autonomous vehicles in these regions. On the other hand, rapidly developing automotive markets such as China, India are likely to propel the automobile cyber security market owing to growing sales of connected cars and presence of largest electric vehicles market.

The study was conducted using an objective combination of primary and secondary information including inputs from key participants in the industry. The report contains a comprehensive market and vendor landscape in addition to a SWOT analysis of the key vendors.

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Key questions answered in this global machine learning based vehicle cybersecurity market report

  • What is the total market size by 2024 and what would be the expected growth rate of market?
  • What is the total revenue per segment and region in 2015-16 and what would be the expected revenue per segment and region over the forecast period?
  • What are the key market trends?
  • What are the factors which are driving this market?
  • What are the major barriers to market growth?
  • Who are the key vendors in this market space?
  • What are the market opportunities for the existing and entry level players?
  • What are the recent developments and business strategy of the key players?

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Machine Learning in Vehicle CyberSecurity Market Size By Security Type (Network, Endpoint, Application, & User), By Vehicle Type (Electric Vehicles, Autonomous Vehicles, Conventional Vehicles), By Region (Europe, North America) - Global Industry Analyis & Forecast 2016-2024

A complementary 2hrs free facility through which report buyers can interact with our pool of experienced analysts for any report related queries, clarifications or additional data requirements

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A complementary 2hrs free facility through which report buyers can interact with our pool of experienced analysts for any report related queries, clarifications or additional data requirements