While machine learning, an application of artificial intelligence, is not new, customers still struggle to understand how it will benefit their efforts to defend their critical assets. When evaluating this technology, here are the five key components that are critical to effective machine learning and successful protection of the endpoint.
Imagine for a moment you had a twin that you didn’t know about. A virtual copy of you that shopped where you shopped, read what you read, and was interested in exactly the same things you were. For all intents and purposes, this twin was you but with one big difference; this copy of you cared almost nothing about your privacy. Surprise! This copy of you exists and isn’t going away any time soon. So… now what? Well, for starters, you should read this Q&A between Jason Elrod and Sean Martin.
There has been a great deal of attention paid to the advantages of machine learning in security tools lately. And while it shows a great deal of promise, the reality is alone, machine learning is not enough to consistently and accurately detect, prevent or predict threats and is prone to false-positives. When considering how to reduce the overall threat exposure window, organizations need to understand how, only when combined with additional technologies, machine learning can be effective.
Of the top disruptive technologies that will benefit from quantum computing, self-driving cars look most imminent as a commercial prospect. But how does this impact the hackability of these vehicles? Scott Totzke explains in his latest ITSPmagazine Experts Corner.
We live in a technology-hungry society where consumers are accustomed to the convenience of technology without understanding the risks and vulnerabilities that come with it. In this part 1 of 2 InfoSec Life articles, Phil Agcaoili, CISO, discusses the five core issues of basic cyber hygiene.
Xuan Zhao, a female data scientist in the information security industry, explains how machine learning dramatically helps her work have a true impact on society, and vice versa.
Sometimes, it's all too easy to forget about the technology we surround ourselves with. In this ITSPmagazine article, artificial intelligence expert, Scott Scheferman, explores the realities of technology becoming ingrained in our everyday lives.
After years of discussion, expectation and experimental products, it looks like the smart home is finally having its moment - particularly with popular adoption of devices like Google Home and Amazon Echo. Of course, these convenient and exciting devices are still new, and that means there are still bugs to work out. Where does this leave us?
As systems become increasingly autonomous and capable of learning about and acting on environments without human input, how do we maximize their benefit to society while minimizing their risks? And who is liable for their actions?
Technology entrepreneur Vishal Gupta explains how living by the principles of empathizing with the individuals whose data his firm is charged with protecting frames the way he approaches his InfoSec Life.
If you believe the vendor hype, Artificial Intelligence is the greatest thing to ever happen to cybersecurity. Guess what? The vendors may be correct, but it’s not easy to determine what is useful technology and what is fluffy marketing.
We are now in the wake of two of the biggest and most catastrophic Distributed Denial of Service (DDoS) attacks that we have seen yet. As we have observed, the Internet of Things (IoT) are beginning to pose a real threat to our information security.
There’s tremendous excitement about Machine Learning and its Artificial Intelligence applications for cybersecurity. There’s a lot of confusion and vendor technobabble, too, that must be sorted out.
From Big Data to Behavioral Analytics to Machine Learning, Artificial Intelligence presents a confusing landscape, in large part because the terms are vague and defined inconsistently (and vendors like it this way).
Academia, public sector, and commercial enterprises are all looking to go digital and virtual in one fashion or another. What does this world look like? Expert Chuck Brooks gives us his view.
Xuan Zhao is a data scientist in the cybersecurity industry who shares her relatively unique experience of working in a nearly all-male world – she is part of a supportive, collaborative team where everyone is equal, and everyone’s idea is valued.