DevOps is about more than continuous delivery. Prasanna Singaraju, Chief of Engineering and Technology at Qentelli, explains how AI can help fill in the potential gaps to improve application quality and delivery speed as well as user satisfaction.
SIEMs currently fight the cybersecurity war ten miles from the front line, reviewing logs to show that an attack happened and replaying the steps required to prevent it from happening again. New tools such as Artificial Intelligence must move this battle closer to the front lines, allowing security teams to transition from threat detectives to threat hunters seeking out attacks before they happen.
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.
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.
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.
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.
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.
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?
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.
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).
Malcolm Harkins, CISO at Cylance, discusses the difference between leadership and management in the InfoSec space where 95% of a company leader’s time tends to be spent on preventing negative outcomes rather than promoting positive outcomes.