AI And Cybersecurity: Plague Or Promise? Posted on : Oct 28 - 2019

We hear from our teams every day regarding how cyberthreats to our enterprise are getting more frequent, more sophisticated and more targeted. Cyber intrusions, specifically publicly reported incidents, are on the rise.

It’s easy to tune the warnings out, but we must remain vigilant. Our responsibilities to our clients, shareholders, employees and other stakeholders depend on us remaining focused.

As cyberattacks grow in volume and complexity, it’s time to face a hard truth: Humans are already not able to keep up with the pace of threats, and companies can't afford to keep up manually. Many, if not most IT teams do not have the resources to protect their enterprises, certainly not in real time. And in a world where minutes matter and thoroughness is paramount, we need to look at artificial intelligence (AI) to support and augment what we need to combat the bad actors.

According to the Accenture Security Index, more than 70% of global organizations have difficulty identifying, let alone protecting, corporate high-value assets. At the same time, the financial impact of cyberattacks is growing. On average, the cost of cybercrime has gone up to $11.7 million per organization in 2017, an increase of 23% compared to the previous year based on a recent study by Accenture and the Ponemon Institute. (Full disclosure: Accenture is Avanade’s parent company.)

Technologies, some already being deployed and some in development, will help us gain the advantage we need. But it has already sparked conversation and debate. Do AI and machine learning present the promise of a more secure online infrastructure or a threat?

First, some definitions. Merriam-Webster defines artificial intelligence as "a branch of computer science that deals with the simulation of intelligent behavior in computers." In contrast, machine learning is "the process by which a computer is able to improve its own performance...by continuously incorporating new data into an existing statistical model." Think of machine learning as a subset of AI.

Detect And Prevent: Stop Malicious Activity Before It Starts

AI and machine learning can be leveraged throughout an enterprise’s security operations, most often in incident response or threat hunting. One of the biggest problems in the never-ending battle against cyberthreats is the large amount of data that must be processed to identify potential threats. Machine learning has the potential to sift through massive sets of data across many vectors to help combat that noise behind all the signals, as well as identify potentially malicious activities and take action. It can also weed out the false positives more effectively than humans alone and potentially take action before harm can occur.

Even better, the next evolution, where we will find untold additional value, is not just detection but prevention. Imagine if we could predict earlier how malware will spread and where. Aided by well-set-up AI systems, countermeasures could be in place before human operators even know a threat is about to happen. And in a world where minutes matter, this could be huge in managing global cyberattacks and cutting off the larger-scale impacts. View More