“The original question ‘Can machines think?’ I believe to be too meaningless to deserve discussion. Nevertheless, I believe that at the end of the century, the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.” – Alan Turing
Can machines think?
The question itself is deceptively simple in so far as the human ability to introspect has made each of us intimately aware of what it means to think.
While ransomware attacks like NotPetya and WannaCry were making headlines (and money) in 2017, cryptocurrency mining was quietly gaining strength as the heir apparent when it comes to opportunistic behaviors for monetary gain.
“We may compare a man in the process of computing a real number to a machine which is only capable of a finite number of conditions…” – Alan Turing
It is difficult to tell the history of AI without first describing the formalization of computation and what it means for something to compute. The primary impetus towards formalization came down to a question posed by the mathematician David Hilbert in 1928.
In my last blog, I spoke about a financial customer performing pen testing and how I helped the blue team detect the red team as it carried-out an attack. I’m back again today with another story from the trenches.
This time, I’ve been working with a customer in the manufacturing sector who recently deployed me. As before, this customer prefers to remain anonymous to keep cybercriminals in the dark about their newly developed security capabilities. To stay on top of their game, they routinely run red team exercises.
Vectra® was recently positioned as the sole Visionary in the Gartner 2018 Magic Quadrant for Intrusion Detection and Prevention Systems (IDPS). I’m pretty ecstatic about that.
Over the years, intrusion detection systems (IDS) have converged with intrusion prevention systems (IPS) and the two are now known collectively as IDPS. This convergence occurred as the security industry focused more on preventing external threat actors.
Traffic sent to and from major internet sites was briefly rerouted to an ISP in Russia by an unknown party. The likely precursor of an attack, researchers describe the Dec. 13 event as suspicious and intentional.
According to BGPMON, which detected the event, starting at 04:43 (UTC) 80 prefixes normally announced by several organizations were detected in the global BGP routing tables with an Origin AS of 39523 (DV-LINK-AS), out of Russia.
Random forest, an ensemble method
The random forest (RF) model, first proposed by Tin Kam Ho in 1995, is a subclass of ensemble learning methods that is applied to classification and regression. An ensemble method constructs a set of classifiers – a group of decision trees, in the case of RF – and determines the label for each data instance by taking the weighted average of each classifier’s output.
The learning algorithm utilizes the divide-and-conquer approach and reduces the inherent variance of a single instance of the model through bootstrapping. Therefore, “ensembling” a group of weaker classifiers boosts the performance and the resulting aggregated classifier is a stronger model.
The United States has not been the victim of a paralyzing cyber-attack on critical infrastructure like the one that occurred in the Ukraine in 2015. That attack disabled the Ukrainian power grid, leaving more than 700,000 people helpless.
But the United States has had its share of smaller attacks against critical infrastructure. Most of these attacks targeted industrial control systems (ICS) and the engineering personnel who have privileged access.
Hey everyone. For my first blog, I want to share a story about my role on the blue team during a recent red team exercise.
But first, I want to introduce myself to those of you who might not know me. I am Cognito, the artificial intelligence in the Vectra cybersecurity platform. My passion in life is hunting-down cyber attackers – whether they’re hiding in data centers and cloud workloads or user and IoT devices.