A recent report from P&S Market Research pegs the growth in the cybersecurity artificial intelligence market at 36 percent annually from 2017 through 2023, when it expects the cybersecurity artificial intelligence market to reach $18 billion.
According to the research firm, the North American cybersecurity artificial intelligence market currently ranks as the single largest contributor in revenue to the global artificial intelligence in cybersecurity market. That’s not expected to change throughout the projected timeframe.
The research firm attributed mobility and cloud as key factors that are driving the interest in AI. Cloud is certainly a main driver, in addition to increasing the complexity in modern enterprises attackers have more attack vectors to try until they find something that works. Cloud systems are complex, so it’s of little surprise that cloud services providers will be early adaptors of artificial intelligence. “Also, implementation of artificial intelligence in cloud security services is further expected to fuel the growth of North American AI in cyber security market, during the forecast period. Rising number of cyber-crimes, such as ransomware are growing at an exorbitant pace, making business interruption and financial losses accruing at huge scale. Governments of the U.S and Canada are witnessing a 12%-17% rise in cybercrimes on yearly basis. Canada is also witnessing high increase in phishing emails and network breaches, which clearly depicts a plethora of opportunities for AI in cyber security in the North American market,” the release said.
Enterprises will both appreciate the use of AI by their cloud service providers, as well as the their ability to use it to protect their own environments. For instance, in my recent post, Despite Cloud Popularity, Enterprises Still Struggle with Compliance and Security, the global public cloud computing market reached $130 billion. And, according to the recent Frost & Sullivan IT Decision Maker Survey, the top three factors considered when choosing a cloud provider are, in order: security capabilities, reliability and cost.
In that post, we detailed how the vast majority of organizations said they were unable to identify anomalous behavior across cloud applications and that traditional security technologies don’t work or have limited functionality in the cloud.
One area where artificial intelligence should be able to help enterprises is modeling their architecture and defenses. While it’s impossible for a security analyst to understand every egress and egress point in their cloud environments, which often consist of variations of on-premises, public, and private clouds, traditional networks and software defined networks [link to Ericka] and hundreds of applications and thousands of endpoints, software versions, the impact of firewall settings, and so forth. Through machine learning, such environments will be able to be modelled from the perspective of the attacker. Analysts will be able to more effectively defend their systems based on the most vulnerable choke points, the business value of data, regulatory controls, and similar factors. Another is how machine learning and AI will enhance malware detection. It’s possible to rely on clustering and classifying algorithms to more accurately and rapidly determine if a file or activity is malicious or friendly.
This is how artificial intelligence will not replace enterprise security analysts but augment them. Of course, as is the case with all technology, artificial intelligence and machine learning are double-edged swords, and as we covered here, you can expect adversaries to use this same technology to try to infiltrate.