Layering Artificial Intelligence and Big Data

March 4, 2016

We all know that there is significant growth in the amount of data being created digitally each and every second — late last year, Gwava reported that since 2011, the global population of people using the Internet has grown 60 percent, from 2 billion Internet users to more than 3.2 billion people, and that number is continually growing.

The goal for IT and cyber security departments is to be able to quickly detect, study, analyze and predict patterns of potential tamper events, breaches and other cyber crimes. To successfully accomplish this, Big Data must not only be collected, but also used to see the bigger picture — a comprehensive view of all potential and emerging threats. The application of artificial intelligence, also dubbed “machine learning” by some, to the raw numerical and symbolic data being created can transform random information into logical explanations and reports.

Layering security-related Big Data with artificial intelligence means faster, personalized communication based on predictive analytics, which helps enable enterprises to develop meaning to all information being collected. It’s when the data has understandable meaning that it can be used to enhance overall cyber security practices and strategies.

Artificial intelligence has the capacity to:

  • Analyze data based on an established set of facts;
  • Cluster these facts together into patterns that make sense;
  • Evaluate these clusters to determine what is most or less important; and
  • Evaluate these clusters to determine what is most or less important; and

Applying artificial intelligence and its capabilities, especially its pattern recognition ability to network data can drastically reduce time to detect and discover a tamper event. Each tamper incident must be understood to quickly restore the environment so that system integrity is not diminished. Artificial intelligence and pattern recognition empowers CISOs to be able to identity where and when a breach has occurred, establishing known hotspots to monitor for future vulnerability. These established patterns also identify sets of “norms” that indicate potential threats, giving cyber security leaders commonalities to watch proactively.

Today’s challenges within cyber security as a whole make this topic critical to the future of the industry. Start-ups are being funded that focus on predictive analytics for cybersecurity and we are excited to have one of them — BRS Labs — as a sponsor of Connected Security Expo, taking place in conjunction with ISC West this year. We invite you to come and learn the latest trends that are bridging the gap between physical and IT security from thought leaders in the IT/cyber and physical security spaces.

We use cookies to operate this website and to improve its usability. Full details of what cookies are, why we use them and how you can manage them can be found by reading our Privacy & Cookies page. Please note that by using this site you are consenting to the use of cookies.