Statii News: How Machine Learning And Other Tech Trends Will Disrupt Cyber Security In 2018

Monday, 5 February 2018

How Machine Learning And Other Tech Trends Will Disrupt Cyber Security In 2018

Machine Learning And Other Tech Trends

Cyber Security is a rapidly evolving industry, projected to become a $232 billion global market by 2022.

This estimated valuation reflects a significant rise from last year, in which the market value reached $137.8 billion worldwide in 2017. marking an impressive Compound Annual Growth Rate of 11%.

The emergence of mobile platforms and cloud-based enterprise apps, coupled with the increased adoption of advanced technologies such as fingerprint identification and biometrics have collectively fueled a notable spike in the space. Although cyber security is attracting greater attention across the globe, the United States stands as the dominant force leading the charge for innovation.

Brian Beyer serves as the CEO of Red Canary, a cyber security company that combines machine learning and human intelligence to develop cutting edge detection and response software to mid-market businesses. Their service thoroughly monitors computer systems for cyber-attacks, alerting companies and shutting threats down before a potential security breach.

Founded in 2013, the Denver-based company has raised $8.6 million to date, including a $6.1 million Series A round of funding. Breaking away from strictly servicing massive Fortune 500 companies, Red Canary focuses on growing segments and carving out a new category of cyber security compatible with the changing industry.

I spoke with Brian about the vision behind his company, the future of cyber security and how top tech trends are impacting the industry in 2018.

What was the specific void or opportunity you identified that inspired the idea behind Red Canary?

Brian Beyer: We started Red Canary because we kept getting called to respond to data breaches, and we believed that businesses could do a better job stopping breaches. Our three founders had solved cyber security and massive satellite data processing problems together in the past, and they believed that a new approach was needed. To use the physical analogy, most businesses spend their time adding padlocks and door alarms to protect their sensitive data.They earnestly hope that adding more tools and systems will make them better, but often times it just results in more false alarms going off. Industry stats show that only 5% of those alarms actually get investigated. We believe that cyber security needs to evolve: organizations need to be able to continuously surveil and hunt for threats and stop them quickly.