Harnessing Artificial Intelligence & Emerging Technologies for Data Security

After the colossal LastPass data breach created a map for hackers on where to focus, organizations are starting to question the amount of trust they place in closed-source password management solutions, what to look for in a new solution, and what to do if their LastPass vault has been stolen. Exposed URLs from LastPass make it easier for hackers to identify users and launch phishing attacks against them. With AI like ChatGPT accelerating, the specter of next-gen phishing looms. With more convincing phishing emails, increased speed and efficiency, and even polymorphic malware code, an uncharted danger awaits just beyond the horizon.

In this webinar, we will dive into the evolution of ML platforms. We shed light on how to identify and define the right business use cases for AI deployment. The challenge for enterprises is to select the right tools often ranging from open-source, fit-to-purpose applications to end-to-end ML workbench. We will attempt to demystify the hype and provide our view on building ML applications with real-world examples.

So many questions still surround artificial intelligence (AI), data science and machine learning. Yet, the questions are getting far less theoretical as more organizations look to take advantage of these technologies now. Organizations are asking more about how they can apply these technologies, how long it will take to gain the benefits, and how to train staff -- or if they need to hire new staff.

Companies strive to have the hot, new app and are consistently working to make their mobile user experiences more cost-efficient and user-friendly. While app security is certainly important to companies and app developers, it often times gets deprioritized below the new, shiny widget. Apps are operated on consumers’ unmanaged devices and companies have no visibility into the mobile threats, which adds to the security challenges.