Automotive cyber security market

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Automotive Cyber Security Market Research Report- Global Forecast 2023 Market Highlights The growing security in the automotive industry have raise several distinct challenges around the connected vehicle. Cyber security in automotive industry has become prominent due to increase vehicles on roads and are vulnerable to hacking, both in the car and the back-end IT systems to which it connects. Hacking in cars have attracted a lot of media attention. OEMs are aware of the need to secure vehicles, and to comfort customers who fear that cars will be easily hacked. The security of automotive manufacturing plants is also a growing concern, the two important threats are vehicle integrity and production line availability. The challenges faced by Automotive Cyber Security Industry includes, connectivity security, in vehicle network architecture and data privacy. In connectivity security, there occur many wired and wireless communication interfaces in a vehicle such as infotainment, OBD-II and Bluetooth. These interfaces exposed the traditionally closed vehicular system, consisting of security vulnerabilities in the vehicle. The automotive cyber security market is growing rapidly over 9% of CAGR and is expected to reach at USD 32 Million by the end of forecast period. Automotive Cyber Security Market Players:  Argus Cyber Security (Israel)  Harman International Industries, Inc. (U.S.)  Karamba Security (Israel)  Intel Corporation (U.S.)  Cisco Systems Inc. (U.S.)  NNG Software Developing and Commercial LLC. (Hungary)  Intel Corporation (U.S.)  NXP Semiconductors N.V. (Netherlands)  Escrypt Embedded Systems (Germany)  Secunet AG (Germany) Request a Sample Report @ https://www.marketresearchfuture.com/sample_request/2970 Automotive Cyber Security Market Segmentation The automotive cyber security market has been segmented on the basis of application it includes communication channels. In securing communication channel, the original equipment manufacturers need to stop hackers from getting in communications channel. To solve this problem there is robust heuristic algorithms that can detect if a communication comes from an authentic source.


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