AI has evolved as a vital technology for augmenting the efforts of human information security teams

FREMONT, CA: The enterprise attack surface is huge and continuing to evolve rapidly. Depending on the size of the enterprise, there are up to many hundred billion time-varying signals that require to be analyzed to accurately calculate risk. In response to this challenge, Artificial Intelligence (AI) powered tools for cybersecurity have emerged to assist information security teams in mitigating breach risk and enhancing their security posture efficiently and effectively. AI and machine learning (ML) have become vital technologies in security, as they can quickly analyze millions of events and find different types of threats. Here is how.

AI is a very popular, often misused word at the moment. Unlike big data, the cloud, IoT, and every other, an increasing number of enterprises are looking for means to jump on the AI bandwagon. But several of today’s AI offerings don’t meet the AI test. While they leverage technologies that analyze data and allow results to drive certain outcomes, that’s not AI; pure AI is about reproducing cognitive potentials to automate tasks.

AI refers to technologies that can learn and act based on acquired and derived information. AI can be said to have some degree of human intelligence: a store of domain-specific knowledge, mechanisms to take new knowledge, and mechanisms to put that knowledge to use. Machine learning, neural networks, and deep learning are all instances or subsets of AI technology today. AI is suited to solve some of the most complex problems, and cybersecurity certainly falls into that category. With evolving cyber-attacks and the proliferation of devices, machine learning and AI can be leveraged to keep up with the hackers by automating threat identification and respond more efficiently than conventional software-driven approaches.

A self-learning, AI-powered cybersecurity posture management system can solve many of these challenges. Technologies exist to properly train a self-learning system to continuously and independently collect data from enterprise information systems. That data is then analyzed and leveraged to perform correlation patterns across billions of signals needed to the enterprise attack surface.