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(Wireless-NewsWire.Com, October 21, 2019 ) The global cybersecurity market size was valued at USD 137.63 billion in 2017 and is projected to reach USD 248.26 billion by 2023, growing at a Compound Annual Growth Rate (CAGR) of 10.2% during 2018-2023, as per a report by MarketsandMarkets.
Why lack of interoperability with the existing information systems remains a key challenge?
With the advancements of technologies, such as IoT, enterprises are facing the challenge of interoperability with the existing systems. In cybersecurity, interoperability is defined as the ability of the IT system and endpoint solutions to enable data communication, data exchange, and readily use information for effective delivery of security system to individuals and businesses. Various reasons lead to interoperability, which includes integration with devices from different manufacturers, devices from different batches, and operating systems support. Many associations and organizations are working toward resolving this issue. Interoperability remains the biggest security challenge, as it is associated with the exchange of information. There are few existing interoperability standards, such as MTConnect, EtherCAT, MDIS (MCS [Master Control System]–DCS [Distributed Control System]) Interface Standardization and promote data interchange across heterogeneous domains and industry verticals. However, there is a need for a common platform to communicate between all the information security systems for dealing with the current interoperability challenges.
How leveraging AI and machine learning for cyber defense could add more opportunities?
Cybersecurity vendors are incorporating Artificial Intelligence (AI) and machine learning concepts into their solutions for addressing critical threats related to the hyper-connected workplace, with faster threat detection, mitigation, and response capabilities. The advancements in technologies, such as AI and machine learning, are turning the tides against cybercriminals. AI and machine learning-based cybersecurity solutions analyze a huge amount of data from the past threat records and identify new threats to save enterprise networks from infiltration attempts. AI and machine learning techniques play an integral role when it comes to identifying and safeguarding against the advanced security threats.
The cyber threats are increasing in number day by day, and conventional security solutions are incapable of detecting malware, ransomware, and other sophisticated cyber threats. Hence, cybersecurity professionals are leveraging AI and machine learning technologies for responding to the evolving cyber threats faced by individuals, businesses, and governments. Additionally, vendors are also looking into leveraging modern day concepts such as blockchain into fortifying the capabilities of their cybersecurity solutions and services, thus offering better protection and remediation for the enterprises.
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Source: EmailWire.Com 
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