Since CrowdStrike’s founding in 2011, we have pioneered the use of artificial intelligence (AI) and machine learning (ML) in cybersecurity to solve our customers’ most pressing challenges. Our application of AI has fit into three practical categories.
As a natural language processing model, ChatGPT - and other similar machine learning-based language models - is trained on huge amounts of textual data. Processing all this data, ChatGPT can produce written responses that sound like they come from a real human being. ChatGPT learns from the data it ingests. If this information includes your sensitive business data, then sharing it with ChatGPT could potentially be risky and lead to cybersecurity concerns.
The Artificial intelligence (AI) based language model, ChatGPT, has gained a lot of attention recently, and rightfully so. It is arguably the most widely popular technical innovation since the introduction of the now ubiquitous smart speakers in our homes that enable us to call out a question and receive an instant answer. But what is it, and why is it relevant to cyber security and data protection?
Doral, Florida UTMStack, a leading innovator in cybersecurity solutions, has announced a significant breakthrough in the field of cybersecurity – an Artificial Intelligence (AI) system that performs the job of a security analyst, promising to transform cybersecurity practices forever.
The cybersecurity industry is extremely dynamic and always finds a way to accommodate the latest and best technologies available into its systems. There are two major reasons: one, because cyberattacks are constantly evolving and organizations need to have the cutting edge technologies in place to detect sophisticated attacks; and two, because of the complexity of the network architecture of many organizations.
Generative Artificial Intelligence (AI) has revolutionized various fields, from creative arts to content generation. However, as this technology becomes more prevalent, it raises important considerations regarding data privacy and confidentiality. In this blog post, we will delve into the implications of Generative AI on data privacy and explore the role of Data Leak Prevention (DLP) solutions in mitigating potential risks.
I remember when the first iPhone was announced in 2007. This was NOT an iPhone as we think of one today. It had warts. A lot of warts. It couldn’t do MMS for example. But I remember the possibility it brought to mind. No product before had seemed like anything more than a product. The iPhone, or more the potential that the iPhone hinted at, had an actual impact on me. It changed my thinking about what could be.
