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.
Threat detection relies on signatures or the correlation of system events to identify indicators of compromise (IOCs). As such, it is primarily reactive and used to verify if a breach has occurred, and to assess the scope and spread of a threat. This article explains how proactive threat hunting can address this inherent weakness in threat detection by assuming a threat or threat actor has not been detected, yet may have targeted an organization.
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.
Move over chatbots - it is time for the empathetic bot. Say what?! In this new Experts Corner, Ashwin Krishnam explores the intersection of autonomous vehicles, bots, and machine learning. Where will technology take us in the future? Will be able to tell the difference between machine and human?
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.
Enterprises are struggling to find secure ways to allow trusted users access sensitive data. Traditional security models designed to protect limited entry points to the data are no longer viable. These best practices, presented by Gurucul’s CEO, Saryu Nayyar, can help address the challenges.
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.
IoT security is certainly a challenging landscape. It was difficult enough to secure a select few smartphone operating systems like IOS and Android, but IoT is a whole new world with an unlimited number of non-standard device operating systems. Michael Lynch explores this world and the future it holds for the IoT device manufacturers.
Want to learn why the $100 million attack on two U.S. Tech companies will accelerate the adoption of machine learning for information security? Then read this Experts Corner from InfoSec expert, Eyal Benishti.
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.
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.
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.
The hottest career of the year may have some technology and self-proclaimed data gurus second guessing their career choice.
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.