Online retailers are once again getting ready for the annual Black Friday to Cyber Monday surge in shopping traffic. Every year they prepare to combat the cybersecurity threats that go into overdrive during the holiday season. Increasingly, they’re getting help from cloud-based artificial intelligence (AI) and machine learning (ML) technology to fight back against the hacks.
U.S. consumers are set to spend a record $36.4 billion online during this year’s four-day shopping stretch, according to Digital Commerce 360. Record demand for ecommerce is expected to drive online spending to $207 billion globally in the 2021 holiday season, according to Adobe Analytics. That’s a 10% increase from last year. This all results in there being an increased amount of data that needs to be monitored and analyzed by security teams. This is too much data for people to manually process and traditional static security analysis techniques just arent good enough anymore.
AI and ML in cybersecurity significantly help in creating more effective security solutions that can better protect against both existing and unknown threats. AI-driven security can react to suspicious activity in real time and prevent attacks before they happen. AI and ML together can make sense of the huge amount of sensor and event data coming through to help detect and prevent fraud, botnet attacks, data loss and much more.
AI and ML improve over time as more and more data is analyzed. Some large security vendors now process trillions of signals per day. The more data processed, the more useful and valuable insights become. Those insights can drive automated security actions. This combination of AI, ML and automation helps to eliminate a lot of the noise, freeing up security teams to investigate the things that really matter.
AI and ML can help in identity management by considering many more signals than just username and password in deciding whether to grant a user access to a system. They may have learned a user's normal behavior and consider their location, IP address, posture of the end device and so on. This type of approach, commonly referred to as “zero trust,” improves security and makes it much harder for the bad guys to succeed.
There are several advantages of cloud-based AI/ML security solutions to keep in mind. As with most cloud-based services they can scale up for holiday or other high-load sales activity as required, rather than carry the costs of full-time capacity that winds up underutilized at other times of the year. Additionally, cloud-based solutions have much larger data sets to work with and learn from. All consumers of the service are feeding it more data and in turn benefitting from the improved insights gained from this aggregated data. Organizations of all sizes can benefit from these services.
The AI/ML approach to win cybersecurity wars
The use of AI and ML for security purposes is gaining traction within companies in all industries. In a DXC-sponsored cybersecurity survey conducted by Harvard Business Review Analytic Services, 63% of executives said that AI and ML is very important or somewhat important to their security operations, and 77% said the same for automation.
Systems integrators and managed security services providers like DXC can help with implementing and managing cloud-based security solutions that use AI and ML from companies including Microsoft with its Defender and Sentinel products.
When you employ the right modern security controls ahead of schedule, you’ll be ready for Black Friday, or whatever peak traffic event your industry is exposed to. You’ll start the new year off on the right foot.
About the author
Peter Scott is Director of security for DXC Technology. He is responsible for helping to secure DXC and its customers. Peter joined DXC from global telecommunications provider BT, where he most recently served as Director for Global IT Infrastructure, End User and Security Engineering.