Top executives are invited to join a conference in San Francisco on July 11-12 to learn how to integrate and optimize AI investments for success. The use of machine learning/artificial intelligence (ML/AI) for cybersecurity practitioners is relatively new, but it has already shown promising results. One of the most common use cases for ML/AI in cybersecurity is endpoint detection and response (EDR), where it uses behavior analytics to pinpoint anomalous activities. It can use known good behavior to discern outliers, then identify and kill processes, lock accounts, trigger alerts, and more.
One new AI model that has generated buzz in the industry is ChatGPT, which is currently open to the public for testing. ChatGPT has already learned Splunk’s Search Processing Language (SPL) and can turn a junior analyst’s prompt into a query in just seconds, significantly lowering the bar for entry. It can also be used to automate daily tasks for an overextended IT team, such as identifying and disabling stale Active Directory accounts.
ChatGPT can also be used for purple teaming or a collaboration of red and blue teams to test and improve an organization’s security posture. It can build simple examples of scripts a penetration tester might use or debug scripts that may not be working as expected. However, there are limitations to its usefulness, and it can still produce false positives that need to be identified by a human being.
Despite these limitations, AI is an important tool that security practitioners can use to alleviate repetitive and mundane tasks, and it can also provide instructional aid for less experienced security professionals. While we’re witnessing the early days of AI technology, we have barely scratched the surface of possibilities for how ChatGPT and other ML/AI models will transform cybersecurity practices. The conference in San Francisco will provide top executives with the opportunity to learn from leaders who have successfully integrated and optimized AI investments for success.