Securing vast and growing IoT environments may not seem to be a humanly possible task--and when the network hosts tens or hundreds of thousands of devices the task, indeed, may be unachievable. To solve this problem, vendors of security products have turned to a decidedly nonhuman alternative: artificial intelligence. "Cyberanalysts are finding it increasingly difficult to effectively monitor current levels of data volume, velocity and variety across firewalls," CapGemini noted in a survey research report, "Reinventing Cybersecurity With Artificial Intelligence." The report also noted that traditional methods may no longer be effective: "Signature-based cybersecurity solutions are unlikely to deliver the requisite performance to detect new attack vectors." In addition to conventional security software's limitations in IoT environments, CapGemini's report revealed a weakness in the human element of cybersecurity.

In any event, machine learning has already changed the rules of the IoT cybersecurity game, says Thomas Dinsmore, director of product marketing for data science at Cloudera, making it look more like a chess match that pits machine against machine. "For instance, segmenting vulnerable or potentially vulnerable IoT or other devices into a separate network, or limiting their Internet access, thereby creating hurdles for hackers and machines attempting to attack the network." At present, security operations are beginning to make greater use of machine-learning-based software to identify vulnerabilities, says Shaun Cooley, CTO of IoT and Industries at Cisco. "Again, it's the human element that is critical here--whether it is humans being lax when training machine learning cybersecurity algorithms, losing control over powerful cyberweapons, humans corrupting machine learning through malicious inputs undetectable by human eyes, or humans believing that a given technology will make them safe," McCleary says.

It's no wonder that artificial intelligence is hot in cybersecurity. As the number of IoT devices is projected to reach into the tens of billions in coming years, enterprise companies will be compelled to embrace AI, machine learning and automation tools to help secure and manage their networks. Doing it the old-fashioned way will simply not be feasible. As a result, the field of cybersecurity is beginning to look like an endless game of chess that pits human hackers against AI-enhanced security professionals. "Already, it is possible to automate cybersecurity responses with machine learning and AI, which demonstrates the edge of what's possible," says T.J. Laher, senior solutions marketing manager at Cloudera.